This paper analyzes the relationship between rural finance and the rural economy of Sichuan Province from 1999 to 2009 by using the sequential growth rate of the gross value of farming, forestry, animal husbandry and ...This paper analyzes the relationship between rural finance and the rural economy of Sichuan Province from 1999 to 2009 by using the sequential growth rate of the gross value of farming, forestry, animal husbandry and fishery and the sequential growth rate of the per capital total income of rural households as the indicators of rural economic development; and taking the volume of deposit, volume of credit, volume of agricultural credit and the credit volume of township enterprises as the indicators of rural financial development; as well as the method of grey correlation analysis. The results show that there is an obvious positive correlation between them, and the development of country finance has the closest connection with the sequential growth rate of farming, forestry, animal husbandry, sideline production and fishery. The loan scale of township enterprises has the biggest influence on the increase of the rural economy. The countermeasures are put forward, covering optimizing investment structure; supporting the development of township enterprises; encouraging loan; actively lightening the financial difficulties in the process of developing rural economy; innovating and exploring; and promoting the diversified development of rural finance.展开更多
The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this vari...The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this variety.The winter water production test results of Anmai 1241 in 14 pilot sites of Henan Seed Management Station from 2016 to 2017 were summarized.The comprehensive performance of 11 agronomic traits of Anmai 1241 in different tests sites in Henan Province was evaluated by the grey correlation analysis and clustering analysis methods.The results showed that among the observed values of 11 traits,the variation coefficient,correlation degree and weight of black embryo rate were 181.64%,0.6679 and 0.1051,respectively.The clustering analysis showed that the 11 traits could be divided into 3 groups.The first type of traits(yield,number of grains per ear and 1000-grain weight)and the third group of traits(percentage of earbearing tillers,number of productive tillers and volume weight)belonged to the yield factor traits,and the sum of their weights was 0.5242.Yield and its related factors played an important role in the variety evaluation of Anmai 1241,and the effect of black embryo on yield should be eliminated in variety improvement.展开更多
Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usa...Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.展开更多
According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive p...According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.展开更多
The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isoton...The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isotonicity and interference factors independence,and it will not lead to changes of the sequence order relation because of the data transformation.Therefore,the new model keeps good stability.Finally,the incremental average correlation model is applied to failure model analysis of equipment,and an ideal diagnostic effect is obtained.展开更多
The future development of cities has a great relationship with economic vitality.To determine the size of the economic vitality and its main influencing factors.This article takes some cities in China as examples.Firs...The future development of cities has a great relationship with economic vitality.To determine the size of the economic vitality and its main influencing factors.This article takes some cities in China as examples.First,determine the main factors.Aiming at many factors,this paper starts from the perspective of population changes in different cities and changes in corporate vitality.After applying the rough set theory to objectively evaluate index weights,the main factors are screened out.Then,the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system,and then the cities are ranked using the gray correlation analysis method.Finally,we get the ranking of the economic vitality level of different cities.Finally,suggestions are made based on the weighting factors of major factors and economic vitality.展开更多
Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct ...Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.展开更多
Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness m...Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness modulus ratio(FMR) and the percentage loss index(PLI) were proposed. In addition, grey correlation analysis was conducted to discuss the relationship between particle agglomerations and RAP size,asphalt content(AC), and surface area. Two indexes indicate that the agglomeration degree increases in general as the RAP size reduces. This can be attributed to that particles are prone to agglomeration in the case of higher AC. Based on the SEM images and the material composition of RAP, the particle agglomeration in RAP can be classified into weak agglomeration and strong agglomeration. Grey correlation analysis shows that AC is the crucial factor affecting the agglomeration degree and RAP variability. In order to produce consistent and stable reclaimed mixtures, disposal measures of RAP are suggested to lower the AC of RAP.展开更多
In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes...In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.展开更多
Investigating the interrelation between snow and vegetation is essential to explain the response of alpine ecosystems to climate change.Based on the MOD10 A1 daily cloud-free snow product and MOD13 A1 NDVI(normalized ...Investigating the interrelation between snow and vegetation is essential to explain the response of alpine ecosystems to climate change.Based on the MOD10 A1 daily cloud-free snow product and MOD13 A1 NDVI(normalized difference vegetation index)data,this study analysed the spatial and temporal patterns of snow phenology including snow onset date,snow end date,snow cover days,and vegetation phenology including the start of growing season,the end of growing season and the length of growing season in the Chinese Tianshan Mountainous Region(CTMR)from 2002 to 2018,and then investigated the snow phenological effects on the vegetation phenology among different ecogeographic zones and diverse vegetation types.The results indicated that snow onset date was earlier at higher elevations and later at lower elevations,while snow end date showed opposite spatial distribution characteristics.The end of growing season occurred later on the northwest slope of the CTMR and the Yili Valley.The earliest end of growing season was in the middle part of the CTMR.A long growing season was mainly distributed along the northern slope and the Yili Valley,while a short growing season was concentrated in the middle part of the CTMR.The response of vegetation phenology to changes in snow phenology varied among vegetation types and ecogeographic zones.The effect of snow phenology on vegetation phenology was more significant in IID5(Yili Valley)than in the other ecogeographic zones.A negative correlation was observed between the start of growing season and snow end date in nearly 54.78%of the study area,while a positive correlation was observed between the start of growing season and the snow end date in 66.85%of the study area.The sensitivity of vegetation phenology to changes in snow cover varied among different vegetation types.Snow onset date had the greatest effect on the start of growing season in the four vegetation cover types(alpine meadows,alpine steppes,shrubs,and alpine sparse vegetation),whereas the snow cover days had the least impact.Snow end date had the greatest impact on the end of growing season in the alpine steppes and shrub areas.The study results are helpful for understanding the vegetation dynamics under ongoing climate change,and can benefit vegetation management and pasture development in the CTMR.展开更多
In order to reveal the effects of different altitudes on the nutritional quality of wild forage in Qinghai-Tibet Plateau,this study used Elymus nutans as the tested plants to evaluate the changes of nutrient contents ...In order to reveal the effects of different altitudes on the nutritional quality of wild forage in Qinghai-Tibet Plateau,this study used Elymus nutans as the tested plants to evaluate the changes of nutrient contents and the correlation between the nutrient contents and altitudes.Four sampling sites were set up at altitudes of 2562,2660,2775 and 2905 m with the vertical distance among each sampling point was about 100 m.The results showed that the crude protein,ash and phosphorus contents of Elymus nutans decreased significantly with an increase in altitudes.The crude protein contents decreased by 1.87%with each 100 m increase in altitudes.The variation rule of crude protein contents with altitudes in the simulated curve was"y=-0.0187x+63.244(R^(2)=0.9557)".The crude ash contents decreased by 1.77%with each 100 m increase in altitudes.The variation rule of crude ash contents with altitudes in the simulated curve was"y=-0.0177x+56.144(R^(2)=0.978)".Neutral detergent fiber(NDF)and acid detergent fiber(ADF)showed an overall increasing trend with the increase of altitudes,but the most obvious increase was at 2775 m.The contents of crude fat and Ca did not change regularly with altitudes.展开更多
Urban space expansion is the result of the interaction between internal and external forces of the urban. Based on the remote sensing image data of 1990, 2000, 2010, and 2020, and the social and economic development d...Urban space expansion is the result of the interaction between internal and external forces of the urban. Based on the remote sensing image data of 1990, 2000, 2010, and 2020, and the social and economic development data, this paper analyzes the driving mechanism of the Luoyang space expansion characteristics and its correlation characteristics. By using urban land use efficiency index, urban expansion elastic index;urban allometric growth index, and grey correlation analysis in 4 times sections and 3 periods. The research results show that the urban space expansion of Luoyang mainly comes from the needs and support of economic development, the coordination between urban space expansion and population development is poor, and urban space expansion effectively attracts the inflow of external funds, and the settlement of migrants, drives the development of the tertiary industry, and increases the local revenue.展开更多
The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,t...The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,the accuracy of its prediction time is low.After empirical analysis,this paper establishes a multi-factor synthesis by studying 7 factors:traffic flow,number of stops,traffic light duration,road network density,average speed,road area,and number of intersections the prediction function achieves the purpose of accurately predicting the transit time of congested road sections.The gray correlation coefficients of the seven factors obtained from the gray correlation analysis are:0.9827,0.9679,0.6747,0.8030,0.9445,0.8759,0.4328.The correlation coefficients of traffic volume,number of stops,average speed,and road congestion delay time were all about 95%,which were the main influencing factors of the study.The prediction needs to be based on functions.This paper fits the main influencing factors to the delay time of congested roads.It is found that the delay time varies parabolically with the traffic flow and the number of stops,and linearly with the average speed.Because the three impact factors have different weights on the delay time of congested roads,demand takes the weight of each factor.Therefore,the gray correlation coefficients occupied by the main influencing factors are normalized to obtain the weights of three of 0.340,0.334,and 0.326.The weighted fitting function is subjected to nonlinear summation processing to obtain a multi-factor comprehensive prediction function.By comparing the original data with the fitting data and calculating the accuracy of the fitting function,it is found that the accuracy of each fitting function is close to 0,the residual error,the relative error is small,and the accuracy is high.展开更多
This paper starts from the analysis of the connotation of low-carbon economy,and establishes the evaluation index system of regional low-carbon economic development level.The main research content is to determine the ...This paper starts from the analysis of the connotation of low-carbon economy,and establishes the evaluation index system of regional low-carbon economic development level.The main research content is to determine the index weight,judge the correlation degree and sort the decision-making units by entropy method,grey correlation analysis and TOPSIS method,and finally make a comprehensive evaluation of the low-carbon economic development level of Shandong Province.The conclusion shows that the development level of low-carbon economy in Shandong Province shows a good trend year by year,but the consumption dependence on high energy consumption resources and backward ecological benefits are increasingly becoming the bottleneck of the development of low-carbon economy in Shandong Province.展开更多
Confronting the contradiction between the rapid development of economy and the effective protection of environment, and developing low carbon economy by optimizing the industrial structure have become one of the effec...Confronting the contradiction between the rapid development of economy and the effective protection of environment, and developing low carbon economy by optimizing the industrial structure have become one of the effective way to attract more attention. In the paper, we made a research on the correlation between china's three main industries and carbon emission intensity to find out the main factors which affect the intensity of carbon emission in China by measuring the gross emission in china's 28 main provinces in 2003-2013 and using Grey correlation analysis based on the change tendency. The results indicate that the second industry has the largest correlation with carbon emission intensity; the tertiary industry helps reduce the intensity of carbon emission, but it is not very obvious; the first industry has the least impact on carbon emission intensity. In the last part, according to the characteristics of industrial structure and carbon emission, we put forward the suggestions and strategies on the adjustment of china's industrial structure in future with the results analysis.展开更多
The development of tourism is closely related to Sanya’s economic growth.In this paper,the correlation between tourism development and economic growth in Sanya city is studied.Itwas first measured with grey correlati...The development of tourism is closely related to Sanya’s economic growth.In this paper,the correlation between tourism development and economic growth in Sanya city is studied.Itwas first measured with grey correlation analysis.Then,tourism factors in Sanya was indicated,including tourism foreign exchange income,total value of accommodation and catering,the number of A-level and above scenic spots,tourism turnover,overnight domestic tourists,total passenger flow of airport and railway station and other factors.It is found that these factors have a significant impact on the output value of tourism in Sanya City.The analytical results show that tourism factors and economic growth in Sanya city is highly correlated.Improvement measures are put forward accordingly.展开更多
In the mobile crowd sensing(MCS)network environment,it is very important to establish an evolutionary process that can dynamically depict the trust degree of task participants.To address this issue,this paper proposes...In the mobile crowd sensing(MCS)network environment,it is very important to establish an evolutionary process that can dynamically depict the trust degree of task participants.To address this issue,this paper proposes a dynamic trust evaluation model for task participants.Firstly,according to the security requirements and trust strategy of the perceived tasks,the attribute reduction algorithm(ARA)based on rough set is used to obtain the multi-attribute indexes that affect the participants’trust information.Removing the redundant attributes can avoid the lag of trust evaluation and reduce the time cost.Secondly,the grey correlation analysis method is used to solve the correlation degree between the target sequence and the comparison sequence on the trust attributes by integrating the multi-attribute decision-making method,which avoids the distortion of the trust evaluation caused by human subjective factors and improves the quality of the perceived data.Finally,a dynamic trust evaluation model for participants in complex sensing network environment is established.The simulation results show that the proposed model can not only dynamically depict the trust degree of participants in real time,but also have higher accuracy and less time cost.展开更多
文摘This paper analyzes the relationship between rural finance and the rural economy of Sichuan Province from 1999 to 2009 by using the sequential growth rate of the gross value of farming, forestry, animal husbandry and fishery and the sequential growth rate of the per capital total income of rural households as the indicators of rural economic development; and taking the volume of deposit, volume of credit, volume of agricultural credit and the credit volume of township enterprises as the indicators of rural financial development; as well as the method of grey correlation analysis. The results show that there is an obvious positive correlation between them, and the development of country finance has the closest connection with the sequential growth rate of farming, forestry, animal husbandry, sideline production and fishery. The loan scale of township enterprises has the biggest influence on the increase of the rural economy. The countermeasures are put forward, covering optimizing investment structure; supporting the development of township enterprises; encouraging loan; actively lightening the financial difficulties in the process of developing rural economy; innovating and exploring; and promoting the diversified development of rural finance.
文摘The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this variety.The winter water production test results of Anmai 1241 in 14 pilot sites of Henan Seed Management Station from 2016 to 2017 were summarized.The comprehensive performance of 11 agronomic traits of Anmai 1241 in different tests sites in Henan Province was evaluated by the grey correlation analysis and clustering analysis methods.The results showed that among the observed values of 11 traits,the variation coefficient,correlation degree and weight of black embryo rate were 181.64%,0.6679 and 0.1051,respectively.The clustering analysis showed that the 11 traits could be divided into 3 groups.The first type of traits(yield,number of grains per ear and 1000-grain weight)and the third group of traits(percentage of earbearing tillers,number of productive tillers and volume weight)belonged to the yield factor traits,and the sum of their weights was 0.5242.Yield and its related factors played an important role in the variety evaluation of Anmai 1241,and the effect of black embryo on yield should be eliminated in variety improvement.
基金the Scientific Research Funding Project of Liaoning Education Department of China under Grant No.JDL2020005,No.LJKZ0485the National Key Research and Development Program of China under Grant No.2018YFA0704605.
文摘Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.
文摘According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.
基金supported by Marie Curie International Incoming Fellowship within the 7th European Community Framework Programme (Grant No.FP7-PIIF-GA-2013629051)the National Natural Science Foundation of China (No.91324003)Social Science Foundation of the China(10zd&014,12AZD102)
文摘The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isotonicity and interference factors independence,and it will not lead to changes of the sequence order relation because of the data transformation.Therefore,the new model keeps good stability.Finally,the incremental average correlation model is applied to failure model analysis of equipment,and an ideal diagnostic effect is obtained.
文摘The future development of cities has a great relationship with economic vitality.To determine the size of the economic vitality and its main influencing factors.This article takes some cities in China as examples.First,determine the main factors.Aiming at many factors,this paper starts from the perspective of population changes in different cities and changes in corporate vitality.After applying the rough set theory to objectively evaluate index weights,the main factors are screened out.Then,the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system,and then the cities are ranked using the gray correlation analysis method.Finally,we get the ranking of the economic vitality level of different cities.Finally,suggestions are made based on the weighting factors of major factors and economic vitality.
文摘Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.
基金Funded by the Postgraduate Research and Practice Innovation Program of Jiangsu Province (No.KYCX21_0496)the Fundamental Research Funds for the Central Universities (for student)+1 种基金the Fundamental Research Funds for the Central Universities (No.B210202050)the Scientific Research Project of Jiangsu Communications Holding Co.,Ltd (No.JETC-DLJS-2022-001)。
文摘Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness modulus ratio(FMR) and the percentage loss index(PLI) were proposed. In addition, grey correlation analysis was conducted to discuss the relationship between particle agglomerations and RAP size,asphalt content(AC), and surface area. Two indexes indicate that the agglomeration degree increases in general as the RAP size reduces. This can be attributed to that particles are prone to agglomeration in the case of higher AC. Based on the SEM images and the material composition of RAP, the particle agglomeration in RAP can be classified into weak agglomeration and strong agglomeration. Grey correlation analysis shows that AC is the crucial factor affecting the agglomeration degree and RAP variability. In order to produce consistent and stable reclaimed mixtures, disposal measures of RAP are suggested to lower the AC of RAP.
基金supported by the project of science and technology of Henan province under Grant No.222102240024 and 202102210269the Key Scientific Research projects in Colleges and Universities in Henan Grant No.22A460013 and No.22B413004.
文摘In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.
基金supported by the National Natural Science Foundation of China(41761014)the“One Hundred Outstanding Young Talents Training Program”of Lanzhou Jiaotong University,the National Natural Science Foundation of China(41971094)the Youth Innovation Promotion Association CAS(2019414)。
文摘Investigating the interrelation between snow and vegetation is essential to explain the response of alpine ecosystems to climate change.Based on the MOD10 A1 daily cloud-free snow product and MOD13 A1 NDVI(normalized difference vegetation index)data,this study analysed the spatial and temporal patterns of snow phenology including snow onset date,snow end date,snow cover days,and vegetation phenology including the start of growing season,the end of growing season and the length of growing season in the Chinese Tianshan Mountainous Region(CTMR)from 2002 to 2018,and then investigated the snow phenological effects on the vegetation phenology among different ecogeographic zones and diverse vegetation types.The results indicated that snow onset date was earlier at higher elevations and later at lower elevations,while snow end date showed opposite spatial distribution characteristics.The end of growing season occurred later on the northwest slope of the CTMR and the Yili Valley.The earliest end of growing season was in the middle part of the CTMR.A long growing season was mainly distributed along the northern slope and the Yili Valley,while a short growing season was concentrated in the middle part of the CTMR.The response of vegetation phenology to changes in snow phenology varied among vegetation types and ecogeographic zones.The effect of snow phenology on vegetation phenology was more significant in IID5(Yili Valley)than in the other ecogeographic zones.A negative correlation was observed between the start of growing season and snow end date in nearly 54.78%of the study area,while a positive correlation was observed between the start of growing season and the snow end date in 66.85%of the study area.The sensitivity of vegetation phenology to changes in snow cover varied among different vegetation types.Snow onset date had the greatest effect on the start of growing season in the four vegetation cover types(alpine meadows,alpine steppes,shrubs,and alpine sparse vegetation),whereas the snow cover days had the least impact.Snow end date had the greatest impact on the end of growing season in the alpine steppes and shrub areas.The study results are helpful for understanding the vegetation dynamics under ongoing climate change,and can benefit vegetation management and pasture development in the CTMR.
基金Supported by the National Natural Fund(31872998)。
文摘In order to reveal the effects of different altitudes on the nutritional quality of wild forage in Qinghai-Tibet Plateau,this study used Elymus nutans as the tested plants to evaluate the changes of nutrient contents and the correlation between the nutrient contents and altitudes.Four sampling sites were set up at altitudes of 2562,2660,2775 and 2905 m with the vertical distance among each sampling point was about 100 m.The results showed that the crude protein,ash and phosphorus contents of Elymus nutans decreased significantly with an increase in altitudes.The crude protein contents decreased by 1.87%with each 100 m increase in altitudes.The variation rule of crude protein contents with altitudes in the simulated curve was"y=-0.0187x+63.244(R^(2)=0.9557)".The crude ash contents decreased by 1.77%with each 100 m increase in altitudes.The variation rule of crude ash contents with altitudes in the simulated curve was"y=-0.0177x+56.144(R^(2)=0.978)".Neutral detergent fiber(NDF)and acid detergent fiber(ADF)showed an overall increasing trend with the increase of altitudes,but the most obvious increase was at 2775 m.The contents of crude fat and Ca did not change regularly with altitudes.
文摘Urban space expansion is the result of the interaction between internal and external forces of the urban. Based on the remote sensing image data of 1990, 2000, 2010, and 2020, and the social and economic development data, this paper analyzes the driving mechanism of the Luoyang space expansion characteristics and its correlation characteristics. By using urban land use efficiency index, urban expansion elastic index;urban allometric growth index, and grey correlation analysis in 4 times sections and 3 periods. The research results show that the urban space expansion of Luoyang mainly comes from the needs and support of economic development, the coordination between urban space expansion and population development is poor, and urban space expansion effectively attracts the inflow of external funds, and the settlement of migrants, drives the development of the tertiary industry, and increases the local revenue.
文摘The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,the accuracy of its prediction time is low.After empirical analysis,this paper establishes a multi-factor synthesis by studying 7 factors:traffic flow,number of stops,traffic light duration,road network density,average speed,road area,and number of intersections the prediction function achieves the purpose of accurately predicting the transit time of congested road sections.The gray correlation coefficients of the seven factors obtained from the gray correlation analysis are:0.9827,0.9679,0.6747,0.8030,0.9445,0.8759,0.4328.The correlation coefficients of traffic volume,number of stops,average speed,and road congestion delay time were all about 95%,which were the main influencing factors of the study.The prediction needs to be based on functions.This paper fits the main influencing factors to the delay time of congested roads.It is found that the delay time varies parabolically with the traffic flow and the number of stops,and linearly with the average speed.Because the three impact factors have different weights on the delay time of congested roads,demand takes the weight of each factor.Therefore,the gray correlation coefficients occupied by the main influencing factors are normalized to obtain the weights of three of 0.340,0.334,and 0.326.The weighted fitting function is subjected to nonlinear summation processing to obtain a multi-factor comprehensive prediction function.By comparing the original data with the fitting data and calculating the accuracy of the fitting function,it is found that the accuracy of each fitting function is close to 0,the residual error,the relative error is small,and the accuracy is high.
文摘This paper starts from the analysis of the connotation of low-carbon economy,and establishes the evaluation index system of regional low-carbon economic development level.The main research content is to determine the index weight,judge the correlation degree and sort the decision-making units by entropy method,grey correlation analysis and TOPSIS method,and finally make a comprehensive evaluation of the low-carbon economic development level of Shandong Province.The conclusion shows that the development level of low-carbon economy in Shandong Province shows a good trend year by year,but the consumption dependence on high energy consumption resources and backward ecological benefits are increasingly becoming the bottleneck of the development of low-carbon economy in Shandong Province.
文摘Confronting the contradiction between the rapid development of economy and the effective protection of environment, and developing low carbon economy by optimizing the industrial structure have become one of the effective way to attract more attention. In the paper, we made a research on the correlation between china's three main industries and carbon emission intensity to find out the main factors which affect the intensity of carbon emission in China by measuring the gross emission in china's 28 main provinces in 2003-2013 and using Grey correlation analysis based on the change tendency. The results indicate that the second industry has the largest correlation with carbon emission intensity; the tertiary industry helps reduce the intensity of carbon emission, but it is not very obvious; the first industry has the least impact on carbon emission intensity. In the last part, according to the characteristics of industrial structure and carbon emission, we put forward the suggestions and strategies on the adjustment of china's industrial structure in future with the results analysis.
文摘The development of tourism is closely related to Sanya’s economic growth.In this paper,the correlation between tourism development and economic growth in Sanya city is studied.Itwas first measured with grey correlation analysis.Then,tourism factors in Sanya was indicated,including tourism foreign exchange income,total value of accommodation and catering,the number of A-level and above scenic spots,tourism turnover,overnight domestic tourists,total passenger flow of airport and railway station and other factors.It is found that these factors have a significant impact on the output value of tourism in Sanya City.The analytical results show that tourism factors and economic growth in Sanya city is highly correlated.Improvement measures are put forward accordingly.
基金supported by National Natural Science Foundation of China(6120245861403109)+1 种基金Natural Science Foundation of Heilongjiang Province of China(F2017021)Harbin Science and Technology Innovation Research Funds(2016RAQXJ036)。
文摘In the mobile crowd sensing(MCS)network environment,it is very important to establish an evolutionary process that can dynamically depict the trust degree of task participants.To address this issue,this paper proposes a dynamic trust evaluation model for task participants.Firstly,according to the security requirements and trust strategy of the perceived tasks,the attribute reduction algorithm(ARA)based on rough set is used to obtain the multi-attribute indexes that affect the participants’trust information.Removing the redundant attributes can avoid the lag of trust evaluation and reduce the time cost.Secondly,the grey correlation analysis method is used to solve the correlation degree between the target sequence and the comparison sequence on the trust attributes by integrating the multi-attribute decision-making method,which avoids the distortion of the trust evaluation caused by human subjective factors and improves the quality of the perceived data.Finally,a dynamic trust evaluation model for participants in complex sensing network environment is established.The simulation results show that the proposed model can not only dynamically depict the trust degree of participants in real time,but also have higher accuracy and less time cost.
