Computational Intelligence In Data Mining Volume 3
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Computational Intelligence In Data Mining Volume 3
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Author : Lakhmi C. Jain
language : en
Publisher: Springer
Release Date : 2014-12-11
Computational Intelligence In Data Mining Volume 3 written by Lakhmi C. Jain and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-11 with Technology & Engineering categories.
The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Data Mining With Computational Intelligence
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Author : Lipo Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-08
Data Mining With Computational Intelligence written by Lipo Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-08 with Computers categories.
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Computational Intelligence In Data Mining
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Author : Giacomo Della Riccia
language : en
Publisher: Springer
Release Date : 2014-05-04
Computational Intelligence In Data Mining written by Giacomo Della Riccia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-04 with Computers categories.
The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.
Computational Intelligence In Data Mining
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Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2019-08-17
Computational Intelligence In Data Mining written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-17 with Technology & Engineering categories.
This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.
Computational Intelligence In Data Mining
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Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2017-05-19
Computational Intelligence In Data Mining written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-19 with Technology & Engineering categories.
The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
Intelligent Data Mining
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Author : Da Ruan
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-08-24
Intelligent Data Mining written by Da Ruan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-24 with Mathematics categories.
"Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.
Machine Learning And Data Mining In Aerospace Technology
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2019-07-02
Machine Learning And Data Mining In Aerospace Technology written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-02 with Computers categories.
This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.
Computational Intelligence In Data Mining Volume 1
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Author : Himansu Sekhar Behera
language : en
Publisher: Springer
Release Date : 2015-12-08
Computational Intelligence In Data Mining Volume 1 written by Himansu Sekhar Behera and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Technology & Engineering categories.
The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
Emerging Technologies In Data Mining And Information Security
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Author : João Manuel R. S. Tavares
language : en
Publisher: Springer Nature
Release Date : 2021-05-04
Emerging Technologies In Data Mining And Information Security written by João Manuel R. S. Tavares and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Technology & Engineering categories.
This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of things (IoT), and information security.
Computational Intelligence In Data Mining Volume 1
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Author : Lakhmi C. Jain
language : en
Publisher: Springer
Release Date : 2014-12-10
Computational Intelligence In Data Mining Volume 1 written by Lakhmi C. Jain and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-10 with Technology & Engineering categories.
The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.