Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks
Melin, Patricia, Ramirez, Martha, Castillo, Oscar
- 出版商: Springer
- 出版日期: 2024-09-28
- 售價: $2,170
- 貴賓價: 9.5 折 $2,062
- 語言: 英文
- 頁數: 74
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3031711009
- ISBN-13: 9783031711008
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商品描述
This book provides a new model for clustering, classification, and time series prediction by using artificial neural networks to computationally simulate the behavior of the cognitive functions of the brain is presented. This model focuses on the study of intelligent hybrid neural systems and their use in time series analysis and decision support systems. Therefore, through the development of eight case studies, multiple time series related to the following problems are analyzed: traffic accidents, air quality and multiple global indicators (energy consumption, birth rate, mortality rate, population growth, inflation, unemployment, sustainable development, and quality of life). The main contribution consists of a Generalized Type-2 fuzzy integration of multiple indicators (time series) using both supervised and unsupervised neural networks and a set of Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. The obtained results show the advantages of the proposed model of Generalized Type-2 fuzzy integration of multiple time series attributes. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic techniques for solving problems in classification and prediction. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
商品描述(中文翻譯)
本書提供了一個新的模型，用於聚類、分類和時間序列預測，透過人工神經網絡計算模擬大腦認知功能的行為。該模型專注於智能混合神經系統的研究及其在時間序列分析和決策支持系統中的應用。因此，通過發展八個案例研究，分析了與以下問題相關的多個時間序列：交通事故、空氣質量及多個全球指標（能源消耗、出生率、死亡率、人口增長、通貨膨脹、失業率、可持續發展和生活品質）。主要貢獻在於使用監督式和非監督式神經網絡以及一組類型1、區間類型2和廣義類型2模糊系統，對多個指標（時間序列）進行廣義類型2模糊整合。所獲得的結果顯示了所提議的廣義類型2模糊整合多個時間序列屬性的模型的優勢。本書旨在成為對於有興趣應用類型2模糊邏輯技術解決分類和預測問題的科學家和工程師的參考資料。我們認為本書也可以用來獲取新研究方向的新想法，或繼續作者所提出的研究方向。
作者簡介
Patricia Melin holds the Doctor in Science degree (Doctor Habilitatus D.Sc.) in Computer Science from the Polish Academy of Sciences. She is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico, since 1998. In addition, she is serving as Director of Graduate Studies in Computer Science and head of the research group on Hybrid Neural Intelligent Systems (2000-present). She is past President of NAFIPS (North American Fuzzy Information Processing Society) 2019-2020. Prof. Melin is the founding Chair of the Mexican Chapter of the IEEE Computational Intelligence Society. She is member of the IEEE Neural Network Technical Committee (2007 to present), the IEEE Fuzzy System Technical Committee (2014 to present) and is Chair of the Task Force on Hybrid Intelligent Systems (2007 to present) and she is currently Associate Editor of the Journal of Information Sciences and IEEE Transactions on Fuzzy Systems. She is member of NAFIPS, IFSA, and IEEE. She belongs to the Mexican Research System with level III. Her research interests are in Modular Neural Networks, Type-2 Fuzzy Logic, Pattern Recognition, Fuzzy Control, Neuro-Fuzzy and Genetic-Fuzzy hybrid approaches. She has published over 300 journal papers, 20 authored books, 50 edited books, and more than 300 papers in conference proceedings, for a total of more than 800 publications with h-index of 86 in Google Scholar. She is Editor-in-Chief of the Advances in Fuzzy Systems journal (Wiley). She has served as Guest Editor of several Special Issues in the past, in journals like: Applied Soft Computing, Intelligent Systems, Information Sciences, Non-Linear Studies, JAMRIS, Fuzzy Sets and Systems. She has been recognized as Highly Cited Researcher in 2017 and 2018 by Clarivate Analytics because of having multiple highly cited papers in Web of Science.
Martha Ramırez holds the B.S. in Computer Science, M.S. in Computer Science, and the Ph.D. in Computer Science from Tijuana Institute of Technology. Currently she works at Tecnologico Nacional de Mexico in Mexico City. Her current research interests include hybrid intelligent systems, neural networks and fuzzy systems. She has published more 10 papers in time series prediction, classification and clustering using supervised and unsupervised neural network models, in addition to type-1 and type-2 fuzzy logic for aggregation of responses in ensembles and modular neural networks.
Oscar Castillo holds the Doctor in Science degree (Doctor Habilitatus) in Computer Science from the Polish Academy of Sciences (with the Dissertation "Soft Computing and Fractal Theory for Intelligent and Manufacturing"). He is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico. In addition, he is serving as Research Director of Computer Science and head of the research group on Hybrid Fuzzy Intelligent Systems. Currently, he is President of HAFSA (Hispanic American Fuzzy Systems Association) and Past President of IFSA (International Fuzzy Systems Association). Prof.
Castillo is also Chair of the Mexican Chapter of the Computational Intelligence Society (IEEE). He is also a member of NAFIPS, IFSA and IEEE. He belongs to the Mexican Research System (SNI Level 3). His research interests are in Type-2 Fuzzy Logic, Fuzzy Control, Neuro-Fuzzy and Genetic-Fuzzy hybrid approaches. He has published over 300 journal papers, 20 authored books, 100 edited books, 300 papers in conference proceedings, and more than 300 chapters in edited books, in total more than 1180 publications (according to Scopus) with h index of 97 and more than 31000 citations according to Google Scholar. He has been Guest Editor of several successful Special Issues in the past, like in the following journals: Applied Soft Computing, Intelligent Systems, Information Sciences, Soft Computing, Non-Linear Studies, Fuzzy Sets and Systems, JAMRIS and Engineering Letters. He is currently Associate Editor of the Information Sciences Journal, Journal of Engineering Applications on Artificial Intelligence, International Journal of Fuzzy Systems, Journal of Complex Intelligent Systems, Granular Computing Journal and Intelligent Systems Journal (Wiley). He was Associate Editor of Journal of Applied Soft Computing and IEEE Transactions on Fuzzy Systems. He has been elected IFSA Fellow in 2015 and MICAI Fellow in 2016. Finally, he recently received the Recognition as Highly Cited Researcher in 2017 and 2018 by Clarivate Analytics and Web of Science.
作者簡介(中文翻譯)
**Patricia Melin** 擁有波蘭科學院的計算機科學博士學位（Doctor Habilitatus D.Sc.）。自1998年以來，她一直擔任墨西哥蒂華納科技學院研究生部的計算機科學教授。此外，她還擔任計算機科學研究生學業主任及混合神經智能系統研究小組的負責人（2000年至今）。她曾擔任北美模糊信息處理學會（NAFIPS）2019-2020年的會長。Melin教授是IEEE計算智能學會墨西哥分會的創始主席。她是IEEE神經網絡技術委員會的成員（2007年至今）、IEEE模糊系統技術委員會的成員（2014年至今），並擔任混合智能系統工作小組的主席（2007年至今），目前也是《信息科學期刊》和《IEEE模糊系統期刊》的副編輯。她是NAFIPS、IFSA和IEEE的成員，並屬於墨西哥研究系統的三級。她的研究興趣包括模塊化神經網絡、二型模糊邏輯、模式識別、模糊控制、神經模糊和遺傳模糊混合方法。她已發表超過300篇期刊論文、20本專著、50本編輯書籍，以及300多篇會議論文，總出版物超過800篇，Google Scholar的h指數為86。她是《模糊系統進展》期刊（Wiley）的主編。她曾擔任多個期刊的特刊客座編輯，如《應用軟計算》、《智能系統》、《信息科學》、《非線性研究》、《JAMRIS》、《模糊集與系統》。因為在Web of Science上有多篇高被引論文，她在2017年和2018年被Clarivate Analytics認定為高被引研究者。
**Martha Ramírez** 擁有計算機科學學士、碩士及博士學位，均來自蒂華納科技學院。她目前在墨西哥城的國立技術學院工作。她目前的研究興趣包括混合智能系統、神經網絡和模糊系統。她已發表超過10篇有關時間序列預測、分類和聚類的論文，使用監督式和非監督式神經網絡模型，以及用於集成和模塊化神經網絡的1型和2型模糊邏輯。
**Oscar Castillo** 擁有波蘭科學院的計算機科學博士學位（Doctor Habilitatus），其論文題目為「智能與製造的軟計算與分形理論」。他是墨西哥蒂華納科技學院研究生部的計算機科學教授。此外，他還擔任計算機科學研究主任及混合模糊智能系統研究小組的負責人。目前，他是HAFSA（西班牙裔美國模糊系統協會）的會長，並曾擔任IFSA（國際模糊系統協會）的前會長。Castillo教授也是IEEE計算智能學會墨西哥分會的主席。他是NAFIPS、IFSA和IEEE的成員，並屬於墨西哥研究系統（SNI三級）。他的研究興趣包括二型模糊邏輯、模糊控制、神經模糊和遺傳模糊混合方法。他已發表超過300篇期刊論文、20本專著、100本編輯書籍、300篇會議論文，以及300多篇編輯書籍中的章節，總出版物超過1180篇（根據Scopus），Google Scholar的h指數為97，引用次數超過31000。他曾擔任多個成功特刊的客座編輯，如《應用軟計算》、《智能系統》、《信息科學》、《軟計算》、《非線性研究》、《模糊集與系統》。
