This paper discusses the strategy for successfully predicting the location of potential hidden ore bodies in aged ore field, and presents the result of location prediction of hidden ore bodies in Fenghuangshan ore fie...This paper discusses the strategy for successfully predicting the location of potential hidden ore bodies in aged ore field, and presents the result of location prediction of hidden ore bodies in Fenghuangshan ore field, Tongling. Innovative conceptual targeting procedures based on a genetic understanding of mineralization systems, carefully geological investigation and correct deduction, together with new geochemical and geophysical technology and integrating of comprehensive information are all very important for the successful prediction. In the aged Fenghuangshan ore field, through researching by application of the metallogenic theory of polygenetic compound ore deposits and triple frequency induced polarization method and exploration tectono geochemical method, we predicted location and quality of hidden ore bodies. According to the prediction, hidden high quality Cu Au ore bodies of skarn type and porphyry type have been discovered.展开更多
The metallogenic theory of polygenetic compound ore deposit is the important basis for location prediction of hidden ore deposits in diwa regions. It can play an important role in each step of prediction research, tar...The metallogenic theory of polygenetic compound ore deposit is the important basis for location prediction of hidden ore deposits in diwa regions. It can play an important role in each step of prediction research, targeting procedure, acquiring information and integrating information. In this paper, the authors discusses how to construct geological concept by using of the metallogenic theory of polygenetic ore deposits for predicting targeting area, to arrange investigation and detection for getting enough useful information, and to analyze and integrate information for reaching a trustful prediction conclusion. According to these strategies, we conduct a successful prediction of location of hidden ore bodies in the outer of the Fenghuangshan copper mine, a principal producing mine in Tongling Cu Au district.展开更多
Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed...Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed,which in turn affects the accuracy of the prediction results.First,a new trajectory data expression method by associating the movement behavior information is given.The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region.The movement behavior features based on pre-association may not always be the best for the prediction model.Therefore,through association analysis and importance analysis,the final association feature is selected from the pre-association features.The trajectory data is input into the LSTM networks after associated features and genetic algorithm(GA)is used to optimize the combination of the length of time window and the number of hidden layer nodes.The experimental results show that compared with the original trajectory data,the trajectory data associated with the movement behavior information helps to improve the accuracy of location prediction.展开更多
Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Locat...Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Location based services (LBS) are one of the vital applications which are subdivided into two main categories: economical category and public category. Economic applications include mobile marketing, entertainment and tracking applications. Whereas, emergency cases, safety, traffic management, Muslims’ applications and public information applications are sort of public applications. The first part of the paper presents a new proposed system with developed procedure to recreate public and economic applications with high positioning accuracy and good authentication of users’ data. The developed system is created to enhance both location based services and network allocation resources within mobile network platform using either normal or GPS supported mobile equipment. The second part of the paper introduces future location prediction of mobile user dependent applications. New algorithm is developed depending on utilizing both intra-cell Movement Pattern algorithm (ICMP) [1] and hybrid uplink time Difference of Arrival and Assisted GPS technique (UTDOA_AGPS) [2]. It has been noticed that ICMP algorithm outperforms other future location prediction algorithms with high precision and within suitable time (less than 220) msec. However, UTDOA_AGPS guarantees high precession of mobile user independent of the surrounding environment. The proposed technique is used to enhance reliability and efficiency of location based services using cellular network platform.展开更多
Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related t...Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related to their types. The apoptosis proteins are categorized into the following four types: (1) Cytoplasmic protein;(2) Plasma membrane-bound protein;(3) Mitochondrial inner and outer proteins;(4) Other proteins. A novel method, the Hilbert-Huang transform, is applied for predicting the type of a given apoptosis protein with support vector machine. High success rates were obtained by the re-substitute test (98/98=100%), jackknife test (91/98 = 92.9%).展开更多
The method of infrared thermography to predict the temperature of the sulfide ores has a large error. To solve this problem, the temperature of the sulfide ores is measured by thermal infrared imager and recording the...The method of infrared thermography to predict the temperature of the sulfide ores has a large error. To solve this problem, the temperature of the sulfide ores is measured by thermal infrared imager and recording thermometric instrument contrastively. The main factors, including emissivity, distance, angle and dust concentration that affect the temperature measurement precision, are analyzed. The regression equations about the individual factors and comprehensive factors are obtained by analyzing test data. The application of the regression equations improves the precision of the thermal infrared imager. The geometric information lost in traditional infrared thermometry is determined by visualization grid method and interpolation method, the relationship between the infrared imager and geometry information is established. The geometry location can be measured exactly.展开更多
The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Con...The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Considering the standard of natural environment, society, traffic, power grid and economy, an evaluation system is created for electric vehicle charging station project through 15 sub-standards. Planning model of charging station is constructed based on BP neural network adopted in the analysis. It is used for location and capacity prediction of charging station planning. By analyzing the model with data samples, a stable network structure is established and the feasibility of the model is verified in the charging station planning.展开更多
The rapid production dynamic prediction of water-flooding reservoirs based on well location deployment has been the basis of production optimization of water-flooding reservoirs.Considering that the construction of ge...The rapid production dynamic prediction of water-flooding reservoirs based on well location deployment has been the basis of production optimization of water-flooding reservoirs.Considering that the construction of geological models with traditional numerical simulation software is complicated,the computational efficiency of the simulation calculation is often low,and the numerical simulation tools need to be repeated iteratively in the process of model optimization,machine learning methods have been used for fast reservoir simulation.However,traditional artificial neural network(ANN)has large degrees of freedom,slow convergence speed,and complex network model.This paper aims to predict the production performance of water flooding reservoirs based on a deep convolutional generative adversarial network(DC-GAN)model,and establish a dynamic mapping relationship between well location deployment and output oil saturation.The network structure is based on an improved U-Net framework.Through a deep convolutional network and deconvolution network,the features of input well deployment images are extracted,and the stability of the adversarial model is strengthened.The training speed and accuracy of the proxy model are improved,and the oil saturation of water flooding reservoirs is dynamically predicted.The results show that the trained DC-GAN has significant advantages in predicting oil saturation by the well-location employment map.The cosine similarity between the oil saturation map given by the trained DC-GAN and the oil saturation map generated by the numerical simulator is compared.In above,DC-GAN is an effective method to conduct a proxy model to quickly predict the production performance of water flooding reservoirs.展开更多
Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly...Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.展开更多
This paper presents MBITP, a novel method for an indoor target prediction through the sensor data which may be the Big Data. To predict target, a probability model is presented. In addition, a real-time error correcti...This paper presents MBITP, a novel method for an indoor target prediction through the sensor data which may be the Big Data. To predict target, a probability model is presented. In addition, a real-time error correction technique based on map feature is designed to enhance the estimation accuracy. Based on it, we propose an effective prediction algorithm. The practice evaluation shows that the method introduced in this paper has an acceptable performance in real-time target prediction.展开更多
当前的位置预测方法大多没有考虑到用户行为信息,由于用户的访问时间、行为模式等能够在很大程度上反映所处位置,因此在对位置潜在向量进行预训练时有必要使用该信息。进行位置预测时,采样粒度较细的序列长度较长,难以捕获长距离依赖。...当前的位置预测方法大多没有考虑到用户行为信息,由于用户的访问时间、行为模式等能够在很大程度上反映所处位置,因此在对位置潜在向量进行预训练时有必要使用该信息。进行位置预测时,采样粒度较细的序列长度较长,难以捕获长距离依赖。针对这2个问题,提出了基于用户行为和上下文语义的分层时空长短期记忆网络(Hierarchical Spatiotemporal Long Short-Term Memory Based on User Behavior and Contextual Semantics,CHST-LSTM)模型。该模型通过Transformer编码层处理轨迹数据,将用户相关行为信息考虑在内,融合位置的上下文语义信息,通过预训练得到位置的嵌入表征。根据用户的行为状态分割轨迹阶段,采用编码器-解码器方式对ST-LSTM进行分段分层扩展,利用BiLSTM对全局信息建模,同时处理轨迹的长短期变化,解决长序列的长距离依赖问题。对外卖员用户群体的真实移动轨迹数据进行分析和实验,通过聚类发现其特有的工作模式,在预训练时加入工作模式信息与到访时间信息,得到位置的特征向量并用于预测模型。结果表明CHST-LSTM模型在预测用户下一位置时精度更高。展开更多
基金Doctoral Foundation and University Key Teacher Foundation of Ministry of Education andby Tongling Group Corporation of Nonferrous Metals
文摘This paper discusses the strategy for successfully predicting the location of potential hidden ore bodies in aged ore field, and presents the result of location prediction of hidden ore bodies in Fenghuangshan ore field, Tongling. Innovative conceptual targeting procedures based on a genetic understanding of mineralization systems, carefully geological investigation and correct deduction, together with new geochemical and geophysical technology and integrating of comprehensive information are all very important for the successful prediction. In the aged Fenghuangshan ore field, through researching by application of the metallogenic theory of polygenetic compound ore deposits and triple frequency induced polarization method and exploration tectono geochemical method, we predicted location and quality of hidden ore bodies. According to the prediction, hidden high quality Cu Au ore bodies of skarn type and porphyry type have been discovered.
基金Supported by the Doctoral Foundation (No980 53 3 0 2 ) and U niversity Key Teacher Foundation of Ministryof Education and Tongling Group Corporation of Nonferrous Metal
文摘The metallogenic theory of polygenetic compound ore deposit is the important basis for location prediction of hidden ore deposits in diwa regions. It can play an important role in each step of prediction research, targeting procedure, acquiring information and integrating information. In this paper, the authors discusses how to construct geological concept by using of the metallogenic theory of polygenetic ore deposits for predicting targeting area, to arrange investigation and detection for getting enough useful information, and to analyze and integrate information for reaching a trustful prediction conclusion. According to these strategies, we conduct a successful prediction of location of hidden ore bodies in the outer of the Fenghuangshan copper mine, a principal producing mine in Tongling Cu Au district.
基金supported by the Hunan University of Science and Technology Doctoral Research Foundation Project(E51873).
文摘Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed,which in turn affects the accuracy of the prediction results.First,a new trajectory data expression method by associating the movement behavior information is given.The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region.The movement behavior features based on pre-association may not always be the best for the prediction model.Therefore,through association analysis and importance analysis,the final association feature is selected from the pre-association features.The trajectory data is input into the LSTM networks after associated features and genetic algorithm(GA)is used to optimize the combination of the length of time window and the number of hidden layer nodes.The experimental results show that compared with the original trajectory data,the trajectory data associated with the movement behavior information helps to improve the accuracy of location prediction.
文摘Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Location based services (LBS) are one of the vital applications which are subdivided into two main categories: economical category and public category. Economic applications include mobile marketing, entertainment and tracking applications. Whereas, emergency cases, safety, traffic management, Muslims’ applications and public information applications are sort of public applications. The first part of the paper presents a new proposed system with developed procedure to recreate public and economic applications with high positioning accuracy and good authentication of users’ data. The developed system is created to enhance both location based services and network allocation resources within mobile network platform using either normal or GPS supported mobile equipment. The second part of the paper introduces future location prediction of mobile user dependent applications. New algorithm is developed depending on utilizing both intra-cell Movement Pattern algorithm (ICMP) [1] and hybrid uplink time Difference of Arrival and Assisted GPS technique (UTDOA_AGPS) [2]. It has been noticed that ICMP algorithm outperforms other future location prediction algorithms with high precision and within suitable time (less than 220) msec. However, UTDOA_AGPS guarantees high precession of mobile user independent of the surrounding environment. The proposed technique is used to enhance reliability and efficiency of location based services using cellular network platform.
文摘Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related to their types. The apoptosis proteins are categorized into the following four types: (1) Cytoplasmic protein;(2) Plasma membrane-bound protein;(3) Mitochondrial inner and outer proteins;(4) Other proteins. A novel method, the Hilbert-Huang transform, is applied for predicting the type of a given apoptosis protein with support vector machine. High success rates were obtained by the re-substitute test (98/98=100%), jackknife test (91/98 = 92.9%).
基金Project (51074181) supported by the National Natural Science Foundation of ChinaProject (2010ssxt241) supported by Precious Dissertation Innovation Foundation of Central South University, China
文摘The method of infrared thermography to predict the temperature of the sulfide ores has a large error. To solve this problem, the temperature of the sulfide ores is measured by thermal infrared imager and recording thermometric instrument contrastively. The main factors, including emissivity, distance, angle and dust concentration that affect the temperature measurement precision, are analyzed. The regression equations about the individual factors and comprehensive factors are obtained by analyzing test data. The application of the regression equations improves the precision of the thermal infrared imager. The geometric information lost in traditional infrared thermometry is determined by visualization grid method and interpolation method, the relationship between the infrared imager and geometry information is established. The geometry location can be measured exactly.
文摘The construction of charging service facilities is a very important factor in the popularization of electric vehicles. Therefore, the planning problems of electric vehicle charging station are urgent to be solved. Considering the standard of natural environment, society, traffic, power grid and economy, an evaluation system is created for electric vehicle charging station project through 15 sub-standards. Planning model of charging station is constructed based on BP neural network adopted in the analysis. It is used for location and capacity prediction of charging station planning. By analyzing the model with data samples, a stable network structure is established and the feasibility of the model is verified in the charging station planning.
基金supports from the National Natural Science Foundation of China(No.52104017)the Open Foundation of Cooperative Innovation Center of Unconventional Oil and Gas(Ministry of Education&Hubei Province)(No.UOG2022-14)the open fund of the State Center for Research and Development of Oil Shale Exploitation(33550000-21-ZC0611-0008).
文摘The rapid production dynamic prediction of water-flooding reservoirs based on well location deployment has been the basis of production optimization of water-flooding reservoirs.Considering that the construction of geological models with traditional numerical simulation software is complicated,the computational efficiency of the simulation calculation is often low,and the numerical simulation tools need to be repeated iteratively in the process of model optimization,machine learning methods have been used for fast reservoir simulation.However,traditional artificial neural network(ANN)has large degrees of freedom,slow convergence speed,and complex network model.This paper aims to predict the production performance of water flooding reservoirs based on a deep convolutional generative adversarial network(DC-GAN)model,and establish a dynamic mapping relationship between well location deployment and output oil saturation.The network structure is based on an improved U-Net framework.Through a deep convolutional network and deconvolution network,the features of input well deployment images are extracted,and the stability of the adversarial model is strengthened.The training speed and accuracy of the proxy model are improved,and the oil saturation of water flooding reservoirs is dynamically predicted.The results show that the trained DC-GAN has significant advantages in predicting oil saturation by the well-location employment map.The cosine similarity between the oil saturation map given by the trained DC-GAN and the oil saturation map generated by the numerical simulator is compared.In above,DC-GAN is an effective method to conduct a proxy model to quickly predict the production performance of water flooding reservoirs.
基金This project is supported by National Electric Power Corporation Foundation of China(No.SPKJ010-27).
文摘Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.
基金This work is supported in part by the National Natural Science Foundation of China (NSFC) under Grant No.61370222 and No.61070193, Heilongjiang Province Founds for Distinguished Young Scientists under Grant No.JC201104, Technology Innovation of Heilongjiang Educational Committee under grant No.2013TD012, Program for Group of Science Harbin technological innovation found under grant No.2011RFXXG014.
文摘This paper presents MBITP, a novel method for an indoor target prediction through the sensor data which may be the Big Data. To predict target, a probability model is presented. In addition, a real-time error correction technique based on map feature is designed to enhance the estimation accuracy. Based on it, we propose an effective prediction algorithm. The practice evaluation shows that the method introduced in this paper has an acceptable performance in real-time target prediction.
文摘当前的位置预测方法大多没有考虑到用户行为信息,由于用户的访问时间、行为模式等能够在很大程度上反映所处位置,因此在对位置潜在向量进行预训练时有必要使用该信息。进行位置预测时,采样粒度较细的序列长度较长,难以捕获长距离依赖。针对这2个问题,提出了基于用户行为和上下文语义的分层时空长短期记忆网络(Hierarchical Spatiotemporal Long Short-Term Memory Based on User Behavior and Contextual Semantics,CHST-LSTM)模型。该模型通过Transformer编码层处理轨迹数据,将用户相关行为信息考虑在内,融合位置的上下文语义信息,通过预训练得到位置的嵌入表征。根据用户的行为状态分割轨迹阶段,采用编码器-解码器方式对ST-LSTM进行分段分层扩展,利用BiLSTM对全局信息建模,同时处理轨迹的长短期变化,解决长序列的长距离依赖问题。对外卖员用户群体的真实移动轨迹数据进行分析和实验,通过聚类发现其特有的工作模式,在预训练时加入工作模式信息与到访时间信息,得到位置的特征向量并用于预测模型。结果表明CHST-LSTM模型在预测用户下一位置时精度更高。
