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Titlebook: Advances in Data Analysis with Computational Intelligence Methods; Dedicated to Profess Adam E Gaw?da,Janusz Kacprzyk,Gary G. Yen Book 2018

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發(fā)表于 2025-3-21 16:59:15 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Data Analysis with Computational Intelligence Methods
期刊簡稱Dedicated to Profess
影響因子2023Adam E Gaw?da,Janusz Kacprzyk,Gary G. Yen
視頻videohttp://file.papertrans.cn/148/147652/147652.mp4
發(fā)行地址Presents present and future challenges of computational intelligence.Presents Advances in Data Analysis and Systems Modeling with Computational Intelligence Methods.Dedicated book to Professor Jacek Z
學科分類Studies in Computational Intelligence
圖書封面Titlebook: Advances in Data Analysis with Computational Intelligence Methods; Dedicated to Profess Adam E Gaw?da,Janusz Kacprzyk,Gary G. Yen Book 2018
影響因子.This book is a tribute to Professor Jacek ?urada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek ?urada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few..At the same time, the book recognizes and honors Professor ?urada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields..The volume is divided into five major parts, the first of which addresses theoretic, algori
Pindex Book 2018
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,Institutionalizing a Ministry: 1922–1947,ts with real-world and synthetic data sets. Furthermore, we claim that the proper analysis of these neighborhoods could be the basis for developing new specialized algorithms for imbalanced data. To illustrate it, we study generalizations of over-sampling in pre-processing methods and neighbourhood based ensembles.
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https://doi.org/10.1057/9780230235458n of the onset of criticality in such networks. We discuss an unsupervised method based on Fisher information, which can be used to tune the network hyperparameters. With respect to standard supervised techniques, we show that the proposed approach offers several advantages and is effective on a number of tasks.
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Casting: An Analytical Approaches of rule bases are considered, with the emphasis on addressing the structure identified during modeling. Finally, main approaches to integration and interoperability of rule-based systems are given.
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