Partner selection is the key element for green supply chain management. The green and sustainability criteria should be considered in partner selection problem. In the paper, a green selection framework is described, and then a two-stage partner selection model is proposed with large number of potential companies and the complex selection processes. Hence the specific selection approach for each stage is designed. Especially at the accurate selection stage, in order to finish multi-objective optimization at the same time, A Pareto-cat swarm algorithm is programmed.
{"title":"Partner Selection Model for Green Supply Chain","authors":"Yumei Li, Jiang Zhou","doi":"10.1109/IHMSC.2015.51","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.51","url":null,"abstract":"Partner selection is the key element for green supply chain management. The green and sustainability criteria should be considered in partner selection problem. In the paper, a green selection framework is described, and then a two-stage partner selection model is proposed with large number of potential companies and the complex selection processes. Hence the specific selection approach for each stage is designed. Especially at the accurate selection stage, in order to finish multi-objective optimization at the same time, A Pareto-cat swarm algorithm is programmed.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"27 1","pages":"24-27"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84190527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Distance and velocity measurements are primary mission of radar in automobile anti-collision application. The signal processing procedure is established according to the principle of distance and velocity measurement. Signal processing platform are constructed based on two FIFOs for data sampling and 32bits DSP. By analyzing the relationship between safe distance and relative velocity in highway the measurement indexes are provided. According to above the signal processing technique indexes are established. System working parameters are restricted each other, to resolve this problem the radar system working parameters formulating method and steps are provided based on 10GHz carrier frequency. The time-frequency performance of 1024 FFT is analyzed and main algorithms of signal processing are accomplished.
{"title":"Automobile Anti-collision Millimeter-Wave Radar Signal Processing","authors":"Gang Zhou","doi":"10.1109/IHMSC.2015.260","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.260","url":null,"abstract":"Distance and velocity measurements are primary mission of radar in automobile anti-collision application. The signal processing procedure is established according to the principle of distance and velocity measurement. Signal processing platform are constructed based on two FIFOs for data sampling and 32bits DSP. By analyzing the relationship between safe distance and relative velocity in highway the measurement indexes are provided. According to above the signal processing technique indexes are established. System working parameters are restricted each other, to resolve this problem the radar system working parameters formulating method and steps are provided based on 10GHz carrier frequency. The time-frequency performance of 1024 FFT is analyzed and main algorithms of signal processing are accomplished.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"27 1","pages":"484-486"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83066698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In view of the hydrological time series data with both trends, jumping, and the cycle characteristics of the certainty together with randomness of the unique features, this paper comes up with wavelet analysis to analyze the main cycle and hidden cycle, then through the sliding window method to predict data based on each period for further testing. And verify this method with instance data. The experimental results show that multiple cycles of time series anomaly detection algorithm based on wavelet analysis can effectively complete the anomaly detection of hydrological time series data.
{"title":"Multiple Cycles of Time Series Anomaly Detection Algorithm Based on Wavelet Analysis","authors":"Danbo Chen, Xiaofeng Zhou","doi":"10.1109/IHMSC.2015.172","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.172","url":null,"abstract":"In view of the hydrological time series data with both trends, jumping, and the cycle characteristics of the certainty together with randomness of the unique features, this paper comes up with wavelet analysis to analyze the main cycle and hidden cycle, then through the sliding window method to predict data based on each period for further testing. And verify this method with instance data. The experimental results show that multiple cycles of time series anomaly detection algorithm based on wavelet analysis can effectively complete the anomaly detection of hydrological time series data.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"27 1","pages":"424-427"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83553508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To explain the adoption of two Online payment tools (Quick Pay, Union Pay Online), we use TAM and Trust Theories to extend the Valence Framework. Then we designed a questionnaire in accordance with the proposed model. With the data collected, we have discovered that perceived benefit and trust are the key factors determining users' adoption of e-payment tools, and users pay much less attention to perceived risk. Using the validated and modified model, we explained the adoption of the mentioned two e-payment tools. Quick Pay is more popular than Union Pay because Quick Pay has better performance in ease access, usability, reputation and secure protection.
{"title":"An Empirical Study on the Impact of Perceived Benefit, Risk and Trust on E-Payment Adoption: Comparing Quick Pay and Union Pay in China","authors":"Yanli Pei, Shan Wang, Jing Fan, Min Zhang","doi":"10.1109/IHMSC.2015.148","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.148","url":null,"abstract":"To explain the adoption of two Online payment tools (Quick Pay, Union Pay Online), we use TAM and Trust Theories to extend the Valence Framework. Then we designed a questionnaire in accordance with the proposed model. With the data collected, we have discovered that perceived benefit and trust are the key factors determining users' adoption of e-payment tools, and users pay much less attention to perceived risk. Using the validated and modified model, we explained the adoption of the mentioned two e-payment tools. Quick Pay is more popular than Union Pay because Quick Pay has better performance in ease access, usability, reputation and secure protection.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"5 1","pages":"198-202"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84812184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shaojian Song, Yao Wang, Xiaofeng Lin, Qingbao Huang
In view of the prediction accuracy of Extreme Learning Machine's (ELM) is affected by its input weights and hidden layer neurons thresholds, an improved training method for ELM with Genetic Algorithms (GA-ELM) is proposed in this paper. In GA-ELM, after selection, crossover and mutation of Genetic Algorithm (GA), we will get the optimal weights and thresholds, in initial which are randomly obtained by ELM, then to enhance the generalization performance of ELM. The simulation results show that, compared with other algorithms, the GA-ELM has better prediction accuracy.
{"title":"Study on GA-based Training Algorithm for Extreme Learning Machine","authors":"Shaojian Song, Yao Wang, Xiaofeng Lin, Qingbao Huang","doi":"10.1109/IHMSC.2015.156","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.156","url":null,"abstract":"In view of the prediction accuracy of Extreme Learning Machine's (ELM) is affected by its input weights and hidden layer neurons thresholds, an improved training method for ELM with Genetic Algorithms (GA-ELM) is proposed in this paper. In GA-ELM, after selection, crossover and mutation of Genetic Algorithm (GA), we will get the optimal weights and thresholds, in initial which are randomly obtained by ELM, then to enhance the generalization performance of ELM. The simulation results show that, compared with other algorithms, the GA-ELM has better prediction accuracy.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"126 1","pages":"132-135"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77309561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intelligent Decision Analysis Platform is an advanced application of decision and analysis based on the construction of "State Grid 186" in China. The platform is committed to achieve the goal of all kinds of business managements and developments. It mainly focuses on providing scientific decisions by data mining and predicting after status data being analyzed. With the auxiliary support of the platform, power enterprises are capable of making better strategies and increasing revenue eventually. According to the characteristics of smart grid monitoring and the requirements of management efficiently as well as the demand of reliable storage of massive grid data, this paper puts forward the decision and analysis platform based on the parallel processing framework which is called Spark and the fault-tolerant abstraction for in-memory cluster computing embedded in Spark as it is known as Resilient Distributed Datasets (RDDs). This paper gives detailed analysis of the feasibility and the advantages of the new method, as well as some unsolved problems.
{"title":"The Application of Spark in the Power Grid Intelligent Decision Analysis Platform","authors":"Wei Li, Q. Niu, Weijia Zhang, Jin Pang","doi":"10.1109/IHMSC.2015.200","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.200","url":null,"abstract":"Intelligent Decision Analysis Platform is an advanced application of decision and analysis based on the construction of \"State Grid 186\" in China. The platform is committed to achieve the goal of all kinds of business managements and developments. It mainly focuses on providing scientific decisions by data mining and predicting after status data being analyzed. With the auxiliary support of the platform, power enterprises are capable of making better strategies and increasing revenue eventually. According to the characteristics of smart grid monitoring and the requirements of management efficiently as well as the demand of reliable storage of massive grid data, this paper puts forward the decision and analysis platform based on the parallel processing framework which is called Spark and the fault-tolerant abstraction for in-memory cluster computing embedded in Spark as it is known as Resilient Distributed Datasets (RDDs). This paper gives detailed analysis of the feasibility and the advantages of the new method, as well as some unsolved problems.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"1 1","pages":"216-219"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91101705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Module division is the basis for product modularization. The rationality of the product module division directly affects the function, performance, development time, cost, general degree of module, convenience of maintenance and so on. A module partition method has been proposed based on the interface relationship of Pros and Cons. It parted the module using fuzzy theory, based on the qualitative hierarchy decomposition of the function, considering the interface depending factors of the parts at the same time in this method. And it introduced "information entropy" concept to evaluate the different module partition schemes, then choose the best module partition scheme. Finally, an example validated the method.
{"title":"Research on Module Partition and Solution Evaluation Method Based on the Interface Relationship","authors":"Junyan Zhao, Liang Yin, Keyun Wang, Lichen Shi","doi":"10.1109/IHMSC.2015.269","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.269","url":null,"abstract":"Module division is the basis for product modularization. The rationality of the product module division directly affects the function, performance, development time, cost, general degree of module, convenience of maintenance and so on. A module partition method has been proposed based on the interface relationship of Pros and Cons. It parted the module using fuzzy theory, based on the qualitative hierarchy decomposition of the function, considering the interface depending factors of the parts at the same time in this method. And it introduced \"information entropy\" concept to evaluate the different module partition schemes, then choose the best module partition scheme. Finally, an example validated the method.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"46 1","pages":"32-35"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78535939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Convolutional neural network is a model of deep neural network, which uses the convolution and sub sampling to realize feature extraction. However, the network is easy to over fitting. In this paper, the denoising method is used to corrupt the sample and force the network to learn the better representations to overcome the over fitting problem. The generalization of the convolutional neural network will be enhanced by this. The simulations exhibit the learning process.
{"title":"Convolutional Neural Network with Corrupted Input","authors":"Qingyang Xu, Li Zhang","doi":"10.1109/IHMSC.2015.69","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.69","url":null,"abstract":"Convolutional neural network is a model of deep neural network, which uses the convolution and sub sampling to realize feature extraction. However, the network is easy to over fitting. In this paper, the denoising method is used to corrupt the sample and force the network to learn the better representations to overcome the over fitting problem. The generalization of the convolutional neural network will be enhanced by this. The simulations exhibit the learning process.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"23 1","pages":"77-80"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84506620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The coupler is a connecting device in railway vehicles, used for passing the traction and the impact. The dimension error of the traction platform and impact platform in coupler knuckle is the main factor that affects the smooth connection and safety performance. Use coordinate measuring technology to detect the coupler knuckle, obtaining the dimension of every surface efficiently and accurately. However, the traction platform and the impact platform are eccentric arcs relative to the measuring datum, with non-complete large radius short arcs. So with little collection scale, there're many factors that affect the measurement accuracy. This paper takes a research on the influence of the measurement error of the traction platform and impact platform by coupler knuckle special measuring machine, including location error, sampling method and data processing method. Firstly, based on the character of knuckle and fixture, eliminate the fit tolerance between locating pin and knuckle pinhole by the radius compensation method. And then, analyze the uncertainty of the three-point-circle algorithm and the multi-point-circle algorithm, choosing a reasonable sampling method. At last, with center-fixed method, eliminate the eccentric error of traction and impact platform relative to measurement datum. The research results above provide the theoretical basis for improving the measurement accuracy of the traction platform and the impact platform.
{"title":"Analysis of the Measurement Error of Coupler Knuckle Special Measuring Machine","authors":"Z. Shi, Zhengjing Wang, Liang Yang","doi":"10.1109/IHMSC.2015.155","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.155","url":null,"abstract":"The coupler is a connecting device in railway vehicles, used for passing the traction and the impact. The dimension error of the traction platform and impact platform in coupler knuckle is the main factor that affects the smooth connection and safety performance. Use coordinate measuring technology to detect the coupler knuckle, obtaining the dimension of every surface efficiently and accurately. However, the traction platform and the impact platform are eccentric arcs relative to the measuring datum, with non-complete large radius short arcs. So with little collection scale, there're many factors that affect the measurement accuracy. This paper takes a research on the influence of the measurement error of the traction platform and impact platform by coupler knuckle special measuring machine, including location error, sampling method and data processing method. Firstly, based on the character of knuckle and fixture, eliminate the fit tolerance between locating pin and knuckle pinhole by the radius compensation method. And then, analyze the uncertainty of the three-point-circle algorithm and the multi-point-circle algorithm, choosing a reasonable sampling method. At last, with center-fixed method, eliminate the eccentric error of traction and impact platform relative to measurement datum. The research results above provide the theoretical basis for improving the measurement accuracy of the traction platform and the impact platform.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"14 1","pages":"369-372"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88879227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper considers the leaderless consensus problem of linear multi-agent systems with static and dynamic consensus controllers. The communication topology is modeled by a directed graph which contains a spanning tree. A special type of matrix decomposition is performed on the graph Laplacian matrix which can be factored into the product of two specific matrices. Base on this property of graph Laplacian matrix, a novel analysis approach for leaderless consensus problem is introduced in which the consensus problem can be converted into a stabilization problem of a system with lower dimensions by performing a proper variable transformation. Sufficient conditions are obtained based on Lyapunov stability analyses and algebraic graph theory. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.
{"title":"Leaderless Consensus of Linear Multi-agent Systems: Matrix Decomposition Approach","authors":"Shaolei Zhou, Wei Liu, Qingpo Wu, Gao-yang Yin","doi":"10.1109/IHMSC.2015.225","DOIUrl":"https://doi.org/10.1109/IHMSC.2015.225","url":null,"abstract":"This paper considers the leaderless consensus problem of linear multi-agent systems with static and dynamic consensus controllers. The communication topology is modeled by a directed graph which contains a spanning tree. A special type of matrix decomposition is performed on the graph Laplacian matrix which can be factored into the product of two specific matrices. Base on this property of graph Laplacian matrix, a novel analysis approach for leaderless consensus problem is introduced in which the consensus problem can be converted into a stabilization problem of a system with lower dimensions by performing a proper variable transformation. Sufficient conditions are obtained based on Lyapunov stability analyses and algebraic graph theory. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"14 1","pages":"327-331"},"PeriodicalIF":0.0,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78904527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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