Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very impor...Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.展开更多
In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading,how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key probl...In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading,how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem.The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market,complete the intra-provincial consumption responsibility weight index,and consume renewable energy across provinces and regions.This paper combines power generation and consumption within the province,uses inter-provincial renewable energy trading tomeet the load demand within the province and completes the index of intra-provincial consumption responsibility weights.The intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the model.Under the two-level electricity market operation framework,the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility,while the lower-level model aims to minimize the inter-provincial renewable energy purchasing cost.Finally,the influence of inter-provincial transaction mechanism,risk aversion coefficient,voucher price,and responsibility weight on operating cost is analyzed.Simulation is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index,and promote the consumption of renewable energy.展开更多
In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be direc...In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be directly used for the clustering of functional data. In this paper, we propose a new unsupervised clustering algorithm based on adaptive weights. In the absence of initialization parameter, we use entropy-type penalty terms and fuzzy partition matrix to find the optimal number of clusters. At the same time, we introduce a measure based on adaptive weights to reflect the difference in information content between different clustering metrics. Simulation experiments show that the proposed algorithm has higher purity than some algorithms.展开更多
The objective of the research is to evaluate spatial groundwater quality based on improved fuzzy comprehensive assessment model with entropy weights(FCAEW)in geographical information system(GIS)environment.This paper ...The objective of the research is to evaluate spatial groundwater quality based on improved fuzzy comprehensive assessment model with entropy weights(FCAEW)in geographical information system(GIS)environment.This paper explores the method of comprehensive evaluation of groundwater and sets up an evaluation model applying GIS and FCAEW.Groundwater samples were collected and analyzed from 29 wells in Zhenping County,China.Six parameters were chosen including chloride,sulfate,total hardness,nitrate,fluoride and color.Better spatial interpolation methods for evaluated parameters are found out and selected according to the minimum cross-validation errors from the interpolation methods.FCAEW model was carried out with the help of GIS which makes the evaluating process simpler and easier and more automatically,effectively,efficiently and intelligently.The result embodies the feasibility and effectiveness of FCAEW in GIS when compared with other comprehensive evaluation methods.展开更多
It is shown in this paper that if the hidden layer units take a sinusoidalactivation function,the optimum weights of the three-layer feedforward neural networkcan be explicitly solved by relating the layered neural ne...It is shown in this paper that if the hidden layer units take a sinusoidalactivation function,the optimum weights of the three-layer feedforward neural networkcan be explicitly solved by relating the layered neural network with a truncated Fourier se-ries expansion.Based on this result,two approaches are presented of which one is suited tothe case that the detailed statistical information is available or can be easily estimated.An-other is of data-adaptive type,which can be treated as a solution of standardleast-squares.The later is best suited to realtime processing and slowly time-varying ap-plications since it can be straightforwardly implemented by the traditional LMS or RLSadaptive algorithms.It is also shown that for both the approaches,the resulting networksown an ability of forming arbitrary mappings.By using the present approaches,theconventional training procedure,which is usually very time-consuming,can be avoided.展开更多
This paper presents an improved approach based on the equivalent-weights particle filter(EWPF)that uses the proposal density to effectively improve the traditional particle filter.The proposed approach uses historical...This paper presents an improved approach based on the equivalent-weights particle filter(EWPF)that uses the proposal density to effectively improve the traditional particle filter.The proposed approach uses historical data to calculate statistical observations instead of the future observations used in the EWPF’s proposal density and draws on the localization scheme used in the localized PF(LPF)to construct the localized EWPF.The new approach is called the statistical observation localized EWPF(LEWPF-Sobs);it uses statistical observations that are better adapted to the requirements of real-time assimilation and the localization function is used to calculate weights to reduce the effect of missing observations on the weights.This approach not only retains the advantages of the EWPF,but also improves the assimilation quality when using sparse observations.Numerical experiments performed with the Lorenz 96 model show that the statistical observation EWPF is better than the EWPF and EAKF when the model uses standard distribution observations.Comparisons of the statistical observation localized EWPF and LPF reveal the advantages of the new method,with fewer particles giving better results.In particular,the new improved filter performs better than the traditional algorithms when the observation network contains densely spaced measurements associated with model state nonlinearities.展开更多
Rational Bézier surface is a widely used surface fitting tool in CAD. When all the weights of a rational Bézier surface go to infinity in the form of power function, the limit of surface is the regular contr...Rational Bézier surface is a widely used surface fitting tool in CAD. When all the weights of a rational Bézier surface go to infinity in the form of power function, the limit of surface is the regular control surface induced by some lifting function, which is called toric degenerations of rational Bézier surfaces. In this paper, we study on the degenerations of the rational Bézier surface with weights in the exponential function and indicate the difference of our result and the work of Garc′?a-Puente et al. Through the transformation of weights in the form of exponential function and power function, the regular control surface of rational Bézier surface with weights in the exponential function is defined, which is just the limit of the surface.Compared with the power function, the exponential function approaches infinity faster, which leads to surface with the weights in the form of exponential function degenerates faster.展开更多
The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a tre...The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practical use.展开更多
Tuotuo River region(E91°-E93°,N33°-N 35°) is located in southwest Qinghai Province,P.R.China.It lies in one of the most important metallogenic belts in China—Northwest Sanjiang Metallogenic Belt,d...Tuotuo River region(E91°-E93°,N33°-N 35°) is located in southwest Qinghai Province,P.R.China.It lies in one of the most important metallogenic belts in China—Northwest Sanjiang Metallogenic Belt,due to which Tuotuo River region can be of very high metal mineral potential not only in Qinghai Province but also nationwide.In this research,multisource data sets including geological,geochemical,geophysical, and remotely sensed images were integrated for mineral potential analysis with GIS technology.Under the guidance of regional metallogenic features and deposit-forming geologic anomaly theories,evidential layers were obtained from these sets,which展开更多
Clinical examination data often have the features of carrying vague information,missing data and incomplete examination records,which lead to higher probabilities of misdiagnosis.A variational recursive-discriminant j...Clinical examination data often have the features of carrying vague information,missing data and incomplete examination records,which lead to higher probabilities of misdiagnosis.A variational recursive-discriminant joint model with fast weights(FWs)scheme is proposed.MIMIC-III data sets are trained and tested,and the results are used to diagnosing.Variational recurrent neural network(VRNN)with FWs can better obtain the temporal features with partly missing data,and discriminant neural network(DNN)is for decision.Moreover,layer regularization(LN)avoids the overflow of loss function and stabilize the dynamic parameters of each layer.For the simulations,10 laboratory tests were selected to predict 10 diseases,1600 samples and 400 samples were used for training and testing,respectively.The test accuracy of disease diagnosis without FWs is 72.55%,and that with FWs is 85.80%.Simulations reveal that the FWs mechanism can effectively optimize the system model,abstracting the features for diagnose,and significantly improve the accuracy of decision-making.展开更多
SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to fa...SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures.展开更多
The fast high-efficiency inspection for mining subsidence of mine area is a reliable way for forecasting accident and evaluating losing expense. In order to monitor mining subsidence of exploitation mine efficiently, ...The fast high-efficiency inspection for mining subsidence of mine area is a reliable way for forecasting accident and evaluating losing expense. In order to monitor mining subsidence of exploitation mine efficiently, LiDAR data were used and a novel strip division method was brought forward based on separating-treatment theory, which divided the mass of discrete three-dimensional point cloud data into a series of parallel strips and reduced the dimension in each strip. Polynomial fitting algorithm based on the adaptive weights, which located in the range of the strip, was used for classification complex terrain data of mine-area. The results show that LiDAR datamation can be greatly reduced. In the mean time, the time spending for calculation is shortened, and computational complexity is simplified. Therefore, high-efficiency terrain classification of LiDAR point cloud method can be great beneficial to monitoring environment of mine area.展开更多
Due to the rapid development of electronic countermeasures(ECMs),the corresponding means of electronic counter countermeasures(ECCMs)are urgently needed.In this paper,an act-ive anti-jamming method based on frequency ...Due to the rapid development of electronic countermeasures(ECMs),the corresponding means of electronic counter countermeasures(ECCMs)are urgently needed.In this paper,an act-ive anti-jamming method based on frequency diverse array radar is proposed.By deriving the closed form of the phase center in a uniform line array FDA,we establish a model of the FDA signal based on adaptive weights and derive the effect of active anti-jamming in this regime.The pro-posed active anti-jamming method makes it difficult for jammers to detect or locate our radar.Fur-thermore,the effectiveness of the two frequency increment schemes in terms of anti-jamming is ana-lyzed by comparing the deviation of phase center.Finally,the simulation results verify the effective-ness and superiority of the proposed method.展开更多
In this paper, we establish the existence of at least four distinct solutions to an Kirchhoff type problems involving the critical Caffareli-Kohn-Niremberg exponent, concave term and sign-changing weights, by using th...In this paper, we establish the existence of at least four distinct solutions to an Kirchhoff type problems involving the critical Caffareli-Kohn-Niremberg exponent, concave term and sign-changing weights, by using the Nehari manifold and mountain pass theorem.展开更多
Objective: Abdominal weights was used to strengthen the diaphragm of a C6 ASIA (A) tetraplegic subject with the aim of studying the long term effect of the technique as a part of respiratory rehabilitation. Setting: D...Objective: Abdominal weights was used to strengthen the diaphragm of a C6 ASIA (A) tetraplegic subject with the aim of studying the long term effect of the technique as a part of respiratory rehabilitation. Setting: Department of Physical Medicine and Rehabilitation, Christian Medical College, Vellore, Tamil Nadu, India. Study Design: Prospective case study. Material and methods: The peak EMG amplitude of the diaphragm (DIA), intercostals (INT) and sternoclidomastiod (SCM) were assessed using a surface EMG and inspired lung volume (ILV) was assessed using an adjustable portable spirometer. The measurements were repeated after 3, 6, 9 and 12 months of inspiratory muscle training for a period of 15 minutes daily, 6 days a week for 12 months. Results and discussion: Peak amplitudes recorded by the EMG of DIA and SCM muscles showed a progressive increase, INT muscle did not show a consistent change. INV showed a gradual rise from 1772ml to 2760 ml over the study period. These values have the following significance: 1) Use of abdominal weights as a part of respiratory rehabilitation has beneficial long term effects;2) In patients with tetraplegia, respiratory muscles in particular the diaphragm, are trainable in terms of muscle efficiency;3) The improvement in the muscle efficiency obtained during the early rehabilitation can be maintained or improved using simple non sophisticated exercises like abdominal weights post discharge. Conclusions: Abdominal weights can be used as an effective adjunct to pulmonary rehabilitation in improving the efficiency of diaphragm on a long term basis, thereby reducing the risks associated with pulmonary complications.展开更多
The article is dedicated to the task of developing efficient means to analyze functioning of an information system of the cyclic type based on determining the integral performance criterion. We consider the subject ar...The article is dedicated to the task of developing efficient means to analyze functioning of an information system of the cyclic type based on determining the integral performance criterion. We consider the subject area related to the analysis of moments of peak loads in teaching (admissions, conducting tests and examinations, accreditation of a university, etc.). The criterion is developed based on the analysis of all the processes occurring in the information system (IS) of a university and based on the selection of main factors affecting the change in the effective functioning of the university departments. Certain qualitative and quantitative parameters affecting the integral index of efficiency are considered at various times, since functioning of the whole system is cyclical. A weight for each criterion is accounted for in the integral indicator of efficiency. The proposed approach will allow for simplification of the research of efficiency characteristics of the information systems of the cyclic type based on the analysis of the integral coefficient.展开更多
Randomized weights neural networks have fast learning speed and good generalization performance with one single hidden layer structure. Input weighs of the hidden layer are produced randomly. By employing certain acti...Randomized weights neural networks have fast learning speed and good generalization performance with one single hidden layer structure. Input weighs of the hidden layer are produced randomly. By employing certain activation function, outputs of the hidden layer are calculated with some randomization. Output weights are computed using pseudo inverse. Mutual information can be used to measure mutual dependence of two variables quantitatively based on the probability theory. In this paper, these hidden layer’s outputs that relate to prediction variable closely are selected with the simple mutual information based feature selection method. These hidden nodes with high mutual information values are maintained as a new hidden layer. Thus, the size of the hidden layer is reduced. The new hidden layer’s output weights are learned with the pseudo inverse method. The proposed method is compared with the original randomized algorithms using concrete compressive strength benchmark dataset.展开更多
In the present paper, an elliptic equation with Hardy-Sobolev critical exponent, Hardy-Sobolev-Maz’ya potential and sign-changing weights, is considered. By using the Nehari manifold and mountain pass theorem, the ex...In the present paper, an elliptic equation with Hardy-Sobolev critical exponent, Hardy-Sobolev-Maz’ya potential and sign-changing weights, is considered. By using the Nehari manifold and mountain pass theorem, the existence of at least four distinct solutions is obtained.展开更多
The teaching–learning-based optimisation (TLBO) algorithm is a population-based metaheuristic inspired on the teaching–learning process observed in a classroom. It has been successfully used in a wide range of appli...The teaching–learning-based optimisation (TLBO) algorithm is a population-based metaheuristic inspired on the teaching–learning process observed in a classroom. It has been successfully used in a wide range of applications. In this study, the authors present a variant version of TLBO. In the proposed version, different weights are assigned to students during the student phase, with higher weights being assigned to students with better solutions. Three different approaches to assign weights are investigated. Numerical experiments with benchmark instances of the flow-shop and the job-shop scheduling problems are carried out to investigate the performance of the proposed approaches. They compare the proposed approaches with the original TLBO algorithm and with two variants of TLBOs proposed in the literature in terms of solution quality, convergence speed and simulation time. The results obtained by the application of a Friedman statistical test showed that the proposed approaches outperformed the original version of TLBO in terms of convergence, with no significant losses in the average makespan. The additional simulation time required by the proposed approaches is small. The best performance was achieved with the approach of assigning a fixed weight to half the students with the best solutions and assigning zero to other students.展开更多
文摘Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.
基金supported by National Natural Science Foundation of China (51977127)Shanghai Municipal Science and Technology Commission (19020500800)“Shuguang Program” (20SG52)Shanghai Education Development Foundation and Shanghai Municipal Education Commission.
文摘In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading,how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem.The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market,complete the intra-provincial consumption responsibility weight index,and consume renewable energy across provinces and regions.This paper combines power generation and consumption within the province,uses inter-provincial renewable energy trading tomeet the load demand within the province and completes the index of intra-provincial consumption responsibility weights.The intra-provincial market trading and inter-provincial market clearing are respectively taken as the upper and lower levels of the model.Under the two-level electricity market operation framework,the upper-level model aims to minimize the expected total operating cost within the province considering the carbon emission cost and the weight of the consumption responsibility,while the lower-level model aims to minimize the inter-provincial renewable energy purchasing cost.Finally,the influence of inter-provincial transaction mechanism,risk aversion coefficient,voucher price,and responsibility weight on operating cost is analyzed.Simulation is used to verify that the proposed model can meet the requirements of the provincial load power consumption and the consumption responsibility weight index,and promote the consumption of renewable energy.
文摘In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be directly used for the clustering of functional data. In this paper, we propose a new unsupervised clustering algorithm based on adaptive weights. In the absence of initialization parameter, we use entropy-type penalty terms and fuzzy partition matrix to find the optimal number of clusters. At the same time, we introduce a measure based on adaptive weights to reflect the difference in information content between different clustering metrics. Simulation experiments show that the proposed algorithm has higher purity than some algorithms.
基金supported by the National Natural Science Foundation of China(No.41161020)the Introduction of Talent Project of Ningxia University(No.BQD2012013)the Natural Science Foundation of Ningxia University(No.ZR1209)
文摘The objective of the research is to evaluate spatial groundwater quality based on improved fuzzy comprehensive assessment model with entropy weights(FCAEW)in geographical information system(GIS)environment.This paper explores the method of comprehensive evaluation of groundwater and sets up an evaluation model applying GIS and FCAEW.Groundwater samples were collected and analyzed from 29 wells in Zhenping County,China.Six parameters were chosen including chloride,sulfate,total hardness,nitrate,fluoride and color.Better spatial interpolation methods for evaluated parameters are found out and selected according to the minimum cross-validation errors from the interpolation methods.FCAEW model was carried out with the help of GIS which makes the evaluating process simpler and easier and more automatically,effectively,efficiently and intelligently.The result embodies the feasibility and effectiveness of FCAEW in GIS when compared with other comprehensive evaluation methods.
基金This work was supported by grant 69102007 from the NSF of China the Ph.D Research Foundation of State Educational Commission of China.
文摘It is shown in this paper that if the hidden layer units take a sinusoidalactivation function,the optimum weights of the three-layer feedforward neural networkcan be explicitly solved by relating the layered neural network with a truncated Fourier se-ries expansion.Based on this result,two approaches are presented of which one is suited tothe case that the detailed statistical information is available or can be easily estimated.An-other is of data-adaptive type,which can be treated as a solution of standardleast-squares.The later is best suited to realtime processing and slowly time-varying ap-plications since it can be straightforwardly implemented by the traditional LMS or RLSadaptive algorithms.It is also shown that for both the approaches,the resulting networksown an ability of forming arbitrary mappings.By using the present approaches,theconventional training procedure,which is usually very time-consuming,can be avoided.
基金The National Basic Research Program of China under contract Nos 2017YFC1404100,2017YFC1404103 and 2017YFC1404104the National Natural Science Foundation of China under contract No.41676088。
文摘This paper presents an improved approach based on the equivalent-weights particle filter(EWPF)that uses the proposal density to effectively improve the traditional particle filter.The proposed approach uses historical data to calculate statistical observations instead of the future observations used in the EWPF’s proposal density and draws on the localization scheme used in the localized PF(LPF)to construct the localized EWPF.The new approach is called the statistical observation localized EWPF(LEWPF-Sobs);it uses statistical observations that are better adapted to the requirements of real-time assimilation and the localization function is used to calculate weights to reduce the effect of missing observations on the weights.This approach not only retains the advantages of the EWPF,but also improves the assimilation quality when using sparse observations.Numerical experiments performed with the Lorenz 96 model show that the statistical observation EWPF is better than the EWPF and EAKF when the model uses standard distribution observations.Comparisons of the statistical observation localized EWPF and LPF reveal the advantages of the new method,with fewer particles giving better results.In particular,the new improved filter performs better than the traditional algorithms when the observation network contains densely spaced measurements associated with model state nonlinearities.
基金Supported by the National Natural Science Foundation of China(11671068,11271060,11601064,11290143)Fundamental Research of Civil Aircraft(MJ-F-2012-04)the Fundamental Research Funds for the Central Universities(DUT16LK38)
文摘Rational Bézier surface is a widely used surface fitting tool in CAD. When all the weights of a rational Bézier surface go to infinity in the form of power function, the limit of surface is the regular control surface induced by some lifting function, which is called toric degenerations of rational Bézier surfaces. In this paper, we study on the degenerations of the rational Bézier surface with weights in the exponential function and indicate the difference of our result and the work of Garc′?a-Puente et al. Through the transformation of weights in the form of exponential function and power function, the regular control surface of rational Bézier surface with weights in the exponential function is defined, which is just the limit of the surface.Compared with the power function, the exponential function approaches infinity faster, which leads to surface with the weights in the form of exponential function degenerates faster.
文摘The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practical use.
文摘Tuotuo River region(E91°-E93°,N33°-N 35°) is located in southwest Qinghai Province,P.R.China.It lies in one of the most important metallogenic belts in China—Northwest Sanjiang Metallogenic Belt,due to which Tuotuo River region can be of very high metal mineral potential not only in Qinghai Province but also nationwide.In this research,multisource data sets including geological,geochemical,geophysical, and remotely sensed images were integrated for mineral potential analysis with GIS technology.Under the guidance of regional metallogenic features and deposit-forming geologic anomaly theories,evidential layers were obtained from these sets,which
基金supported by National Natural Science Foundation of China“Research on non-orthogonal multiple access technology for unauthorized transmission”(No.61771051)“Research on a new emergency positioning system for the integration of visible-light communication and MEMS inertial navigation”(No.61675025)
文摘Clinical examination data often have the features of carrying vague information,missing data and incomplete examination records,which lead to higher probabilities of misdiagnosis.A variational recursive-discriminant joint model with fast weights(FWs)scheme is proposed.MIMIC-III data sets are trained and tested,and the results are used to diagnosing.Variational recurrent neural network(VRNN)with FWs can better obtain the temporal features with partly missing data,and discriminant neural network(DNN)is for decision.Moreover,layer regularization(LN)avoids the overflow of loss function and stabilize the dynamic parameters of each layer.For the simulations,10 laboratory tests were selected to predict 10 diseases,1600 samples and 400 samples were used for training and testing,respectively.The test accuracy of disease diagnosis without FWs is 72.55%,and that with FWs is 85.80%.Simulations reveal that the FWs mechanism can effectively optimize the system model,abstracting the features for diagnose,and significantly improve the accuracy of decision-making.
文摘SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures.
基金Project(2011CB707102)supported by the National Basic Research Program of ChinaProjects(41001302,40901220)supported by the National Natural Science Foundation of China+2 种基金Project(200903190)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(20090450305)supported by the China Postdoctoral Science FoundationProject(122025)supported by the Fok Ying Tong Education Foundation,China
文摘The fast high-efficiency inspection for mining subsidence of mine area is a reliable way for forecasting accident and evaluating losing expense. In order to monitor mining subsidence of exploitation mine efficiently, LiDAR data were used and a novel strip division method was brought forward based on separating-treatment theory, which divided the mass of discrete three-dimensional point cloud data into a series of parallel strips and reduced the dimension in each strip. Polynomial fitting algorithm based on the adaptive weights, which located in the range of the strip, was used for classification complex terrain data of mine-area. The results show that LiDAR datamation can be greatly reduced. In the mean time, the time spending for calculation is shortened, and computational complexity is simplified. Therefore, high-efficiency terrain classification of LiDAR point cloud method can be great beneficial to monitoring environment of mine area.
基金the National Natural Science Foundation of China(No.61971438)the Natural Science Founda-tion of Shaanxi Province(No.2019JM-155).
文摘Due to the rapid development of electronic countermeasures(ECMs),the corresponding means of electronic counter countermeasures(ECCMs)are urgently needed.In this paper,an act-ive anti-jamming method based on frequency diverse array radar is proposed.By deriving the closed form of the phase center in a uniform line array FDA,we establish a model of the FDA signal based on adaptive weights and derive the effect of active anti-jamming in this regime.The pro-posed active anti-jamming method makes it difficult for jammers to detect or locate our radar.Fur-thermore,the effectiveness of the two frequency increment schemes in terms of anti-jamming is ana-lyzed by comparing the deviation of phase center.Finally,the simulation results verify the effective-ness and superiority of the proposed method.
文摘In this paper, we establish the existence of at least four distinct solutions to an Kirchhoff type problems involving the critical Caffareli-Kohn-Niremberg exponent, concave term and sign-changing weights, by using the Nehari manifold and mountain pass theorem.
文摘Objective: Abdominal weights was used to strengthen the diaphragm of a C6 ASIA (A) tetraplegic subject with the aim of studying the long term effect of the technique as a part of respiratory rehabilitation. Setting: Department of Physical Medicine and Rehabilitation, Christian Medical College, Vellore, Tamil Nadu, India. Study Design: Prospective case study. Material and methods: The peak EMG amplitude of the diaphragm (DIA), intercostals (INT) and sternoclidomastiod (SCM) were assessed using a surface EMG and inspired lung volume (ILV) was assessed using an adjustable portable spirometer. The measurements were repeated after 3, 6, 9 and 12 months of inspiratory muscle training for a period of 15 minutes daily, 6 days a week for 12 months. Results and discussion: Peak amplitudes recorded by the EMG of DIA and SCM muscles showed a progressive increase, INT muscle did not show a consistent change. INV showed a gradual rise from 1772ml to 2760 ml over the study period. These values have the following significance: 1) Use of abdominal weights as a part of respiratory rehabilitation has beneficial long term effects;2) In patients with tetraplegia, respiratory muscles in particular the diaphragm, are trainable in terms of muscle efficiency;3) The improvement in the muscle efficiency obtained during the early rehabilitation can be maintained or improved using simple non sophisticated exercises like abdominal weights post discharge. Conclusions: Abdominal weights can be used as an effective adjunct to pulmonary rehabilitation in improving the efficiency of diaphragm on a long term basis, thereby reducing the risks associated with pulmonary complications.
文摘The article is dedicated to the task of developing efficient means to analyze functioning of an information system of the cyclic type based on determining the integral performance criterion. We consider the subject area related to the analysis of moments of peak loads in teaching (admissions, conducting tests and examinations, accreditation of a university, etc.). The criterion is developed based on the analysis of all the processes occurring in the information system (IS) of a university and based on the selection of main factors affecting the change in the effective functioning of the university departments. Certain qualitative and quantitative parameters affecting the integral index of efficiency are considered at various times, since functioning of the whole system is cyclical. A weight for each criterion is accounted for in the integral indicator of efficiency. The proposed approach will allow for simplification of the research of efficiency characteristics of the information systems of the cyclic type based on the analysis of the integral coefficient.
文摘Randomized weights neural networks have fast learning speed and good generalization performance with one single hidden layer structure. Input weighs of the hidden layer are produced randomly. By employing certain activation function, outputs of the hidden layer are calculated with some randomization. Output weights are computed using pseudo inverse. Mutual information can be used to measure mutual dependence of two variables quantitatively based on the probability theory. In this paper, these hidden layer’s outputs that relate to prediction variable closely are selected with the simple mutual information based feature selection method. These hidden nodes with high mutual information values are maintained as a new hidden layer. Thus, the size of the hidden layer is reduced. The new hidden layer’s output weights are learned with the pseudo inverse method. The proposed method is compared with the original randomized algorithms using concrete compressive strength benchmark dataset.
文摘In the present paper, an elliptic equation with Hardy-Sobolev critical exponent, Hardy-Sobolev-Maz’ya potential and sign-changing weights, is considered. By using the Nehari manifold and mountain pass theorem, the existence of at least four distinct solutions is obtained.
文摘The teaching–learning-based optimisation (TLBO) algorithm is a population-based metaheuristic inspired on the teaching–learning process observed in a classroom. It has been successfully used in a wide range of applications. In this study, the authors present a variant version of TLBO. In the proposed version, different weights are assigned to students during the student phase, with higher weights being assigned to students with better solutions. Three different approaches to assign weights are investigated. Numerical experiments with benchmark instances of the flow-shop and the job-shop scheduling problems are carried out to investigate the performance of the proposed approaches. They compare the proposed approaches with the original TLBO algorithm and with two variants of TLBOs proposed in the literature in terms of solution quality, convergence speed and simulation time. The results obtained by the application of a Friedman statistical test showed that the proposed approaches outperformed the original version of TLBO in terms of convergence, with no significant losses in the average makespan. The additional simulation time required by the proposed approaches is small. The best performance was achieved with the approach of assigning a fixed weight to half the students with the best solutions and assigning zero to other students.
