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Titlebook: Hybrid Artificial Intelligence Systems; 9th International Co Marios Polycarpou,André C. P. L. F. Carvalho,Emili Conference proceedings 2014

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發(fā)表于 2025-3-21 16:42:30 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Hybrid Artificial Intelligence Systems
副標(biāo)題9th International Co
編輯Marios Polycarpou,André C. P. L. F. Carvalho,Emili
視頻videohttp://file.papertrans.cn/431/430050/430050.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Hybrid Artificial Intelligence Systems; 9th International Co Marios Polycarpou,André C. P. L. F. Carvalho,Emili Conference proceedings 2014
描述This volume constitutes the proceedings of the 9th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2014, held in Salamanca, Spain, in June 2014. The 61 papers published in this volume were carefully reviewed and selected from 199 submissions. They are organized in topical sessions on HAIS applications; data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications and classification and cluster analysis.
出版日期Conference proceedings 2014
關(guān)鍵詞anomaly detection; augmented reality; bayesian network; computer vision; data mining; hybrid system; image
版次1
doihttps://doi.org/10.1007/978-3-319-07617-1
isbn_softcover978-3-319-07616-4
isbn_ebook978-3-319-07617-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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0302-9743 amanca, Spain, in June 2014. The 61 papers published in this volume were carefully reviewed and selected from 199 submissions. They are organized in topical sessions on HAIS applications; data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation;
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Wind Power Ramp Event Prediction with Support Vector Machines. Recursive feature selection illustrates how the number of neighbored turbines affects this approach. The problem of imbalanced training and test sets w.r.t. the number of no-ramp events is analyzed experimentally and the implications on practical ramp detection scenarios are discussed.
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Developing Adaptive Agents Situated in Intelligent Virtual Environmentsnt the look of the real or physical world, allowing to simulate physical phenomena such as gravity or collision detection. The paper also includes a case study which illustrates the use of the proposed framework.
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0302-9743 learning algorithms; hybrid intelligent systems for data mining and applications and classification and cluster analysis.978-3-319-07616-4978-3-319-07617-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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