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Titlebook: Research and Development in Intelligent Systems XXXII; Incorporating Applic Max Bramer,Miltos Petridis Conference proceedings 2015 Springer

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書目名稱Research and Development in Intelligent Systems XXXII
副標題Incorporating Applic
編輯Max Bramer,Miltos Petridis
視頻videohttp://file.papertrans.cn/828/827886/827886.mp4
概述This volume contains new, refereed papers presented at AI-2015, the Thirty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence.Presents new and inn
圖書封面Titlebook: Research and Development in Intelligent Systems XXXII; Incorporating Applic Max Bramer,Miltos Petridis Conference proceedings 2015 Springer
描述.The papers in this volume are the refereed papers presented atAI-2015, the Thirty-fifth SGAI International Conference on InnovativeTechniques and Applications of Artificial Intelligence, held inCambridge in December 2015 in both the technical and the applicationstreams..They present new and innovative developments andapplications, divided into technical stream sections on KnowledgeDiscovery and Data Mining, Machine Learning and Knowledge Acquisition,and AI in Action, followed by application stream sections onApplications of Genetic Algorithms, Applications of Intelligent Agentsand Evolutionary Techniques, and AI Applications. The volume alsoincludes the text of short papers presented as posters at theconference..This is the thirty-second volume in the .Research and Development in Intelligent Systems. series, which also incorporates the twenty-third volume in the?.Applications and Innovations in Intelligent Systems. series. These series are essential reading for those who wish to keep up to date with developments in this important field...?.
出版日期Conference proceedings 2015
關(guān)鍵詞Artificial Intelligence; Data Mining; Intelligent Agents; Applications of Artificial Intelligence; Machi
版次1
doihttps://doi.org/10.1007/978-3-319-25032-8
isbn_softcover978-3-319-25030-4
isbn_ebook978-3-319-25032-8
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Sparse Covariance Matrix Adaptation Techniques for Evolution Strategiesnce the search space is often continuous, evolution strategies use a multivariate normal distribution as search distribution. This necessitates the tuning and adaptation of the covariance matrix. Modern evolution strategies apply covariance matrix adaptation mechanisms in order to achieve this end.
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A Replicator Dynamics Approach to Collective Feature Engineering in Random Forests of predictive accuracy. Motivated by the fact that each subsforest is built using a set of features that can overlap with those sets of features in other subforests, we hypothesise that using . can perform a collective feature engineering, by allowing subforests with better performance to grow and
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CLUB-DRF: A Clustering Approach to Extreme Pruning of Random Foreststechniques, it has proved its superiority. Many researchers, however, believe that there is still room for enhancing and improving its performance accuracy. This explains why, over the past decade, there have been many extensions of RF where each extension employed a variety of techniques and strate
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Fast Handwritten Digit Recognition with Multilayer Ensemble Extreme Learning Machinefer from long training times and their complex nature. An alternative learning algorithm called Extreme Learning Machine overcomes these shortcomings by determining the weights of a neural network analytically. In this paper, a novel classifier based on Extreme Learning Machine is proposed that achi
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