Henry A. Kautz, R. Dechter, L. Kaelbling, M. Kearns, V. Lifschitz
,
，
{"title":"Program committee","authors":"Henry A. Kautz, R. Dechter, L. Kaelbling, M. Kearns, V. Lifschitz","doi":"10.1109/SCAM.2005.21","DOIUrl":"https://doi.org/10.1109/SCAM.2005.21","url":null,"abstract":",","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121120156","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}
A. Choudhary, A. Chandra, André Luckow, Daniel Katz
Jan-Ayvind Aagedal, Telenor, Norway Witold Abramowicz, Poznan University of Economics, Poland Markus Aleksy, University of Mannheim, Germany Ilkay Altintas, University of California, San Diego, USA Joao Paulo A. Almeida, Federal University of Espirito Santo, Brazil Jose Enrique Armendariz-Inigo, Universidad Pública de Navarra, Spain Claudio Bartolini, Hewlett-Packard, USA James Bailey, University of Melbourne, Australia Hubert Baumeister, Technical University of Denmark, Denmark Andrew Berry, Deontik, Australia Jean Bezivin, University of Nantes, France Behzad Bordbar, Birmingham University, United Kingdom Barrett Bryant, University of Alabama-Birmingham, USA Coral Calero, University of Castilla-La Mancha, Spain Chia-Chu Chiang, University of Arkansas at Little Rock, USA Dickson Chiu, Dickson Computer Systems, Hong Kong Myra B. Cohen, University of Nebraska, Lincoln, USA Fred Cummins, EDS, USA Judith Cushing, Evergreen State College, USA Ernesto Damiani, University of Milan, Italy Remco Dijkman, Eindhoven University of Technology, Netherlands Gillian Dobbie, University of Auckland, New Zealand Boudewijn v. Dongen, Eindhoven University of Technology, Netherlands Dirk Draheim, Software Competence Center Hagenberg, Austria Keith Duddy, Queensland University of Technology, Australia Juergen Ebert, Universitaet Koblenz, Germany Dieter Fensel, Digital Enterprise Research Institute, Austria Stephane Gagnon, New Jersey Institute of Technology, USA Gerald Gannod, Arizona State University, USA Aniruddha Gokhale, Vanderbilt University, USA Claude Godart, Universite Henri Poincare, Nancy and INRIA, France Martin Gogolla, Universitaet Bremen, Germany Guido Governatori, University of Queensland, Australia Tyrone Grandison, IBM Research Almaden, USA Norbert Gronau, Universitaet Potsdam, Germany Giancarlo Guizzardi, Federal University of Espirito Santo, Brazil Jun Han, Swinburne University of Technology, Australia Patrick C. K. Hung, University of Ontario Institute of Technology, Canada Raj Jain, Washington University in St. Louis, USA Pontus Johnson, Royal Institute of Technology, Sweden Eleanna Kafeza, Athens University of Economics and Business, Greece Alexander Knapp, University of Augsburg, Germany Axel Korthaus, University of Mannheim, Germany Evangelos Kotsovinos, Morgan Stanley, United Kingdom
Jan-Ayvind Aagedal, Telenor，挪威Witold Abramowicz，波兰波兹南经济大学Markus Aleksy，曼海姆大学，德国Ilkay Altintas，加州大学圣地亚哥分校，美国Joao Paulo A. Almeida，圣埃斯皮里图联邦大学，巴西Jose Enrique Armendariz-Inigo，纳瓦拉大学Pública，西班牙Claudio Bartolini，惠普，美国James Bailey，澳大利亚墨尔本大学Hubert Baumeister，丹麦技术大学，丹麦Andrew Berry，Deontik，澳大利亚Jean Bezivin，南特大学，法国Behzad Bordbar，伯明翰大学，英国Barrett Bryant，阿拉巴马大学伯明翰分校，美国Coral Calero，卡斯蒂利亚-拉曼查大学，西班牙Chia-Chu Chiang，美国阿肯色大学小石城分校，美国Dickson Chiu, Dickson Computer Systems，香港Myra B. Cohen，美国内布拉斯加州大学林肯分校Fred Cummins，美国EDS，美国Judith Cushing，美国Evergreen State College，美国Ernesto Damiani，米兰大学意大利Remco Dijkman，埃因霍温理工大学，荷兰Gillian Dobbie，奥克兰大学，新西兰Boudewijn v. Dongen，埃因霍温理工大学，荷兰Dirk Draheim, Hagenberg软件能力中心，奥地利Keith Duddy，昆士兰科技大学，澳大利亚Juergen Ebert，科布伦茨大学，德国Dieter Fensel，数字企业研究所，奥地利Stephane Gagnon，新泽西理工学院，美国Gerald Gannod，美国亚利桑那州立大学Aniruddha Gokhale、范德比尔特大学、美国Claude Godart、Henri Poincare大学、Nancy和INRIA大学、法国Martin Gogolla、不来梅大学、德国Guido Governatori、昆士兰大学、澳大利亚Tyrone Grandison、IBM Research Almaden、美国Norbert Gronau、波茨坦大学、德国Giancarlo Guizzardi、圣埃斯皮里图联邦大学、巴西Jun Han、斯威本科技大学、澳大利亚Patrick C. K. Hung、加拿大安大略理工大学Raj Jain、美国圣路易斯华盛顿大学Pontus Johnson、瑞典皇家理工学院Eleanna Kafeza、希腊雅典经济与商业大学Alexander Knapp、德国奥格斯堡大学Axel Korthaus、德国曼海姆大学Evangelos Kotsovinos、英国摩根士丹利
{"title":"Program committee","authors":"A. Choudhary, A. Chandra, André Luckow, Daniel Katz","doi":"10.1109/ICDE.2005.114","DOIUrl":"https://doi.org/10.1109/ICDE.2005.114","url":null,"abstract":"Jan-Ayvind Aagedal, Telenor, Norway Witold Abramowicz, Poznan University of Economics, Poland Markus Aleksy, University of Mannheim, Germany Ilkay Altintas, University of California, San Diego, USA Joao Paulo A. Almeida, Federal University of Espirito Santo, Brazil Jose Enrique Armendariz-Inigo, Universidad Pública de Navarra, Spain Claudio Bartolini, Hewlett-Packard, USA James Bailey, University of Melbourne, Australia Hubert Baumeister, Technical University of Denmark, Denmark Andrew Berry, Deontik, Australia Jean Bezivin, University of Nantes, France Behzad Bordbar, Birmingham University, United Kingdom Barrett Bryant, University of Alabama-Birmingham, USA Coral Calero, University of Castilla-La Mancha, Spain Chia-Chu Chiang, University of Arkansas at Little Rock, USA Dickson Chiu, Dickson Computer Systems, Hong Kong Myra B. Cohen, University of Nebraska, Lincoln, USA Fred Cummins, EDS, USA Judith Cushing, Evergreen State College, USA Ernesto Damiani, University of Milan, Italy Remco Dijkman, Eindhoven University of Technology, Netherlands Gillian Dobbie, University of Auckland, New Zealand Boudewijn v. Dongen, Eindhoven University of Technology, Netherlands Dirk Draheim, Software Competence Center Hagenberg, Austria Keith Duddy, Queensland University of Technology, Australia Juergen Ebert, Universitaet Koblenz, Germany Dieter Fensel, Digital Enterprise Research Institute, Austria Stephane Gagnon, New Jersey Institute of Technology, USA Gerald Gannod, Arizona State University, USA Aniruddha Gokhale, Vanderbilt University, USA Claude Godart, Universite Henri Poincare, Nancy and INRIA, France Martin Gogolla, Universitaet Bremen, Germany Guido Governatori, University of Queensland, Australia Tyrone Grandison, IBM Research Almaden, USA Norbert Gronau, Universitaet Potsdam, Germany Giancarlo Guizzardi, Federal University of Espirito Santo, Brazil Jun Han, Swinburne University of Technology, Australia Patrick C. K. Hung, University of Ontario Institute of Technology, Canada Raj Jain, Washington University in St. Louis, USA Pontus Johnson, Royal Institute of Technology, Sweden Eleanna Kafeza, Athens University of Economics and Business, Greece Alexander Knapp, University of Augsburg, Germany Axel Korthaus, University of Mannheim, Germany Evangelos Kotsovinos, Morgan Stanley, United Kingdom","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385100","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}
Pub Date : 2022-10-01DOI: 10.23919/acc.1984.4788341
S. Abe
Ahmed N. Abdaiia, Universiti Malaysia Pahang, Malaysia Shigeo Abe, Kobe University, Japan Salem Adra, University of Sheffield, UK Igor Aizenberg, Texas A&M University-Texarkana, USA Kofi Appiah, University of Lincoln, United Kindom Sabri Arik, Istanbul University, Turkey Amir Atiya, Cairo University, Egypt Nicola Bellotto, University of Lincoln, UK Steve Billings, University of Sheffield, UK Sander Bohte, University of Leiden, T he Netherlands Ivo Bukovsky, Czech Technical University in Prague, Czech Edmund Burke, University of Nottingham, UK Anyela Camargo, University of East Anglia, United Kindom Ho-Lin Chen, California Inst Tech, USA Xiaochun Cheng, Middlesex University, UK Vladimir Cherkassky, University of Minnesota, USA Jose Alfredo F. Costa, Universidade Federal do Rio Grande do Norte, Brasil Vassilis Cutsuridis, Boston Univerisy, USA Darryl N. Davis, University of Hull, UK Marc de Kamps, University of Leeds, UK Alexandre Delbem, University of Sao Paulo, Brazil Mingcong Deng, Okayama University, Japan Konstantinos Dimopoulos, CITY Liberal Studies, Greece Tomoki Fukai, RIKEN Brain Science Institute, Japan Onofrio Gigliotta, CNR-ISTC, Italy Perry Groot, Radboud University Nijmegen, T he Netherlands Yuzhu Guo, University of Sheffield, UK Robert Harrison, University of Sheffield, UK Tom Heskes, Radboud University Nijmegen, T he Netherlands Matthew Hyde, University of Nottingham, UK Licheng Jiao, Xidian University, China
Ahmed N. Abdaiia，马来西亚Pahang大学，马来西亚Shigeo Abe，神户大学，日本Salem Adra，谢菲尔德大学，英国Igor Aizenberg，德克萨斯农工大学- texarkana，美国Kofi Appiah，林肯大学，英国Sabri Arik，伊斯坦布尔大学，土耳其Amir Atiya，开罗大学，埃及Nicola Bellotto，林肯大学，英国Steve Billings，谢菲尔德大学，英国Sander Bohte，莱顿大学，荷兰Ivo Bukovsky，捷克布拉格技术大学，捷克Edmund Burke、诺丁汉大学、英国Anyela Camargo、东安格利亚大学、英国陈浩林、加州理工学院、美国程晓春、米德尔塞克斯大学、英国Vladimir Cherkassky、明尼苏达大学、美国Jose Alfredo F. Costa、北里奥格兰德联邦大学、巴西Vassilis Cutsuridis、波士顿大学、美国Darryl N. Davis、赫尔大学、英国Marc de Kamps、利兹大学、英国Alexandre Delbem、圣保罗大学、巴西邓明聪、日本冈山大学Konstantinos Dimopoulos, CITY Liberal Studies，希腊Fukai Tomoki, RIKEN脑科学研究所，日本Onofrio Gigliotta, CNR-ISTC，意大利Perry Groot，奈梅亨大学，荷兰郭玉竹，谢菲尔德大学，英国Robert Harrison，谢菲尔德大学，英国Tom Heskes，奈梅亨大学，荷兰Matthew Hyde，诺丁汉大学，英国Licheng Jiao，西安电子科技大学，中国
{"title":"Program committee","authors":"S. Abe","doi":"10.23919/acc.1984.4788341","DOIUrl":"https://doi.org/10.23919/acc.1984.4788341","url":null,"abstract":"Ahmed N. Abdaiia, Universiti Malaysia Pahang, Malaysia Shigeo Abe, Kobe University, Japan Salem Adra, University of Sheffield, UK Igor Aizenberg, Texas A&M University-Texarkana, USA Kofi Appiah, University of Lincoln, United Kindom Sabri Arik, Istanbul University, Turkey Amir Atiya, Cairo University, Egypt Nicola Bellotto, University of Lincoln, UK Steve Billings, University of Sheffield, UK Sander Bohte, University of Leiden, T he Netherlands Ivo Bukovsky, Czech Technical University in Prague, Czech Edmund Burke, University of Nottingham, UK Anyela Camargo, University of East Anglia, United Kindom Ho-Lin Chen, California Inst Tech, USA Xiaochun Cheng, Middlesex University, UK Vladimir Cherkassky, University of Minnesota, USA Jose Alfredo F. Costa, Universidade Federal do Rio Grande do Norte, Brasil Vassilis Cutsuridis, Boston Univerisy, USA Darryl N. Davis, University of Hull, UK Marc de Kamps, University of Leeds, UK Alexandre Delbem, University of Sao Paulo, Brazil Mingcong Deng, Okayama University, Japan Konstantinos Dimopoulos, CITY Liberal Studies, Greece Tomoki Fukai, RIKEN Brain Science Institute, Japan Onofrio Gigliotta, CNR-ISTC, Italy Perry Groot, Radboud University Nijmegen, T he Netherlands Yuzhu Guo, University of Sheffield, UK Robert Harrison, University of Sheffield, UK Tom Heskes, Radboud University Nijmegen, T he Netherlands Matthew Hyde, University of Nottingham, UK Licheng Jiao, Xidian University, China","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123682250","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}
Pub Date : 2010-12-06DOI: 10.1109/ICICISYS.2010.5658276
Gaiwen Guo, Bing Zhao
In view of the contradictory unity of growth and whiting in natural trees, Tree Growth Competition Algorithm was presented in this paper. The algorithm searched from a simple status to complex statuses with quick convergence. Then, the algorithm was applied to designing novel tree-shaped line antennas. A software package on automated design of tree-shaped line antenna was developed. Making use of it, a kind of tree-shaped line antenna was designed at the center frequency of 2.45GHz and the model of coaxial feed. The simulation experiment shows its directive gain is higher than that of the traditional antennas in the same size.
{"title":"Tree Growth Competition Algorithm and its application in automated design of line antenna","authors":"Gaiwen Guo, Bing Zhao","doi":"10.1109/ICICISYS.2010.5658276","DOIUrl":"https://doi.org/10.1109/ICICISYS.2010.5658276","url":null,"abstract":"In view of the contradictory unity of growth and whiting in natural trees, Tree Growth Competition Algorithm was presented in this paper. The algorithm searched from a simple status to complex statuses with quick convergence. Then, the algorithm was applied to designing novel tree-shaped line antennas. A software package on automated design of tree-shaped line antenna was developed. Making use of it, a kind of tree-shaped line antenna was designed at the center frequency of 2.45GHz and the model of coaxial feed. The simulation experiment shows its directive gain is higher than that of the traditional antennas in the same size.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122980264","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}
Pub Date : 2010-09-23DOI: 10.1109/ICNC.2010.5583147
Shuangyan Li, Xinyu Xu, X. Tian
In this article, the main eigenvalues of the non-linear method of principle component analysis based on projection pursuit (PP-PCA) are used to analyze the multi-channels local field potentials (LFPs) in rat prefrontal cortex under the different states during Propofol anesthesia, and the results of PP-PCA and linear principal component analysis (PCA) are compared. The principles of 16-channels LFPs data are calculated with 100-ms window sliding and 40% overlap. Meanwhile, the changes of the PP-PCA eigenvalues during the states of wake and anesthesia are applied to analyzing. The result shows that, the first eigenvalues of PP-PCA are much larger than the others both during the periods of wake and anesthesia, whereas during anesthesia, the eigenvalues' values decrease rapidly, by contrast, they are characterized by a slower reducing during waking time. These prove that the method of PP-PCA effectively represents the characterization of better synchronization in LFPs during anesthesia.
{"title":"PP-PCA eigenvalues analysis of cerebral cortex local field potentials","authors":"Shuangyan Li, Xinyu Xu, X. Tian","doi":"10.1109/ICNC.2010.5583147","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583147","url":null,"abstract":"In this article, the main eigenvalues of the non-linear method of principle component analysis based on projection pursuit (PP-PCA) are used to analyze the multi-channels local field potentials (LFPs) in rat prefrontal cortex under the different states during Propofol anesthesia, and the results of PP-PCA and linear principal component analysis (PCA) are compared. The principles of 16-channels LFPs data are calculated with 100-ms window sliding and 40% overlap. Meanwhile, the changes of the PP-PCA eigenvalues during the states of wake and anesthesia are applied to analyzing. The result shows that, the first eigenvalues of PP-PCA are much larger than the others both during the periods of wake and anesthesia, whereas during anesthesia, the eigenvalues' values decrease rapidly, by contrast, they are characterized by a slower reducing during waking time. These prove that the method of PP-PCA effectively represents the characterization of better synchronization in LFPs during anesthesia.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114992363","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}
Pub Date : 2010-09-23DOI: 10.1109/ICNC.2010.5584326
Yunyan Wang, Mingtian Tang
This paper proposes a conditional autoregressive range model under random environment (RECARR) which is a generalization of the model of R. Y. Chou (2005). Since the sudden change of the outside environment is considered, this new model behaves more flexible than the original one in the real world. Some sufficient conditions for geometric ergodicity for the CARR model under random environment are obtained.
{"title":"On a geometric ergodicity of conditional autoregressive range model under random environment","authors":"Yunyan Wang, Mingtian Tang","doi":"10.1109/ICNC.2010.5584326","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5584326","url":null,"abstract":"This paper proposes a conditional autoregressive range model under random environment (RECARR) which is a generalization of the model of R. Y. Chou (2005). Since the sudden change of the outside environment is considered, this new model behaves more flexible than the original one in the real world. Some sufficient conditions for geometric ergodicity for the CARR model under random environment are obtained.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115013388","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}
Pub Date : 2010-09-23DOI: 10.1109/ICNC.2010.5583149
Jiayu Wu, Youbin Hu, Xiaowei Wang
In this paper, we propose an Event-Driven wireless Sensor Network Multi-Path routing protocol (EDWSNMP), which includes three parts: multi-path creation, data communication and route maintenance. In multi-path creation part, a Heuristic Local Gabriel Graph (HLGG) algorithm is proposed to do topology control. In data communication part, cluster header collects data of other nodes in the cluster and merges the data, and then it decides to use single-hop or multi-hop routing policy according to routing table. Route maintenance mainly includes responsible for power variation maintenance, power value maintenance and routing table maintenance.
{"title":"Research on Event-Driven wireless Sensor Network Multi-Path routing protocol","authors":"Jiayu Wu, Youbin Hu, Xiaowei Wang","doi":"10.1109/ICNC.2010.5583149","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583149","url":null,"abstract":"In this paper, we propose an Event-Driven wireless Sensor Network Multi-Path routing protocol (EDWSNMP), which includes three parts: multi-path creation, data communication and route maintenance. In multi-path creation part, a Heuristic Local Gabriel Graph (HLGG) algorithm is proposed to do topology control. In data communication part, cluster header collects data of other nodes in the cluster and merges the data, and then it decides to use single-hop or multi-hop routing policy according to routing table. Route maintenance mainly includes responsible for power variation maintenance, power value maintenance and routing table maintenance.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115397049","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}
Pub Date : 2010-09-23DOI: 10.1109/ICNC.2010.5584561
Bo Fu, Zhenhong Xie, Zhong-li Wang
Combining GIS and RS technique in the study of ecological vulnerability assessment in Zhalong Wet Ecosystem, an improved Back-Propagation neural network was established to model and evaluate ecological vulnerability based on Press-State-Response model. The research educed that: the regions of moderate or severe vulnerability accounted for 18% while the regions of potential or minute vulnerability accounted for 63%; the potential fragility areas and the slight fragility areas with better health were all located in the internal marish while the moderate fragility areas and the serious fragility with poor health were mainly paddy fields; the vulnerability of the central area in the Reserve was not so obvious as the marginal area. The holistic ecological environment of Zhalong wetland was not optimistic. By modeling improved BP neural network and calculating the ecological vulnerability index EVI of each grid cell of Zhalong wetland, a reference of scientific significance was provided for the ecological environment protection and management of Zhalong wetland from the quantitative point of view.
{"title":"Improved back-propagation neural network in ecological vulnerability assessment of Zhalong wetland","authors":"Bo Fu, Zhenhong Xie, Zhong-li Wang","doi":"10.1109/ICNC.2010.5584561","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5584561","url":null,"abstract":"Combining GIS and RS technique in the study of ecological vulnerability assessment in Zhalong Wet Ecosystem, an improved Back-Propagation neural network was established to model and evaluate ecological vulnerability based on Press-State-Response model. The research educed that: the regions of moderate or severe vulnerability accounted for 18% while the regions of potential or minute vulnerability accounted for 63%; the potential fragility areas and the slight fragility areas with better health were all located in the internal marish while the moderate fragility areas and the serious fragility with poor health were mainly paddy fields; the vulnerability of the central area in the Reserve was not so obvious as the marginal area. The holistic ecological environment of Zhalong wetland was not optimistic. By modeling improved BP neural network and calculating the ecological vulnerability index EVI of each grid cell of Zhalong wetland, a reference of scientific significance was provided for the ecological environment protection and management of Zhalong wetland from the quantitative point of view.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432729","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 Idea of Non-negative Matrix Factorization (NMF) has been implemented in a wide variety of real world applications. To improve the usability of NMF, people usually add some regularization items to constrain the process of matrix factorization. The Regularized Non-negative Matrix Factorization (RNMF) mainly relies on prior knowledge to set the regularization parameter value. An improper regularization parameter value will directly influence the factorization result. Due to this reason, we propose a novel algorithm based on L-curve theory which is able to determine the regularization parameter value automatically, we name the algorithm as autoNMF. To testify the validity of autoNMF, we experiment the algorithm with the synthetic image data in blind source separation and compare it with other algorithms. Better unmixed results are gained indicating our algorithm outperforms other algorithms in several aspects.
{"title":"A method of automatically estimating the regularization parameter for Non-negative Matrix Factorization","authors":"Dalong Cheng, Zhenwei Shi, X. Tan, Zhanxing Zhu, Zhi-guo Jiang","doi":"10.1109/ICNC.2010.5583822","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583822","url":null,"abstract":"The Idea of Non-negative Matrix Factorization (NMF) has been implemented in a wide variety of real world applications. To improve the usability of NMF, people usually add some regularization items to constrain the process of matrix factorization. The Regularized Non-negative Matrix Factorization (RNMF) mainly relies on prior knowledge to set the regularization parameter value. An improper regularization parameter value will directly influence the factorization result. Due to this reason, we propose a novel algorithm based on L-curve theory which is able to determine the regularization parameter value automatically, we name the algorithm as autoNMF. To testify the validity of autoNMF, we experiment the algorithm with the synthetic image data in blind source separation and compare it with other algorithms. Better unmixed results are gained indicating our algorithm outperforms other algorithms in several aspects.","PeriodicalId":427056,"journal":{"name":"2010 Sixth International Conference on Natural Computation","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115722317","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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