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Titlebook: Data Mining for Design and Manufacturing; Methods and Applicat Dan Braha Book 2001 Springer Science+Business Media Dordrecht 2001 DES.class

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發(fā)表于 2025-3-21 19:18:17 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Data Mining for Design and Manufacturing
副標題Methods and Applicat
編輯Dan Braha
視頻videohttp://file.papertrans.cn/263/262948/262948.mp4
叢書名稱Massive Computing
圖書封面Titlebook: Data Mining for Design and Manufacturing; Methods and Applicat Dan Braha Book 2001 Springer Science+Business Media Dordrecht 2001 DES.class
描述.Data Mining for Design and Manufacturing: Methods andApplications. is the first book that brings together research andapplications for data mining within design and manufacturing. The aimof the book is 1) to clarify the integration of data mining inengineering design and manufacturing, 2) to present a wide range ofdomains to which data mining can be applied, 3) to demonstrate theessential need for symbiotic collaboration of expertise in design andmanufacturing, data mining, and information technology, and 4) toillustrate how to overcome central problems in design andmanufacturing environments. The book also presents formal toolsrequired to extract valuable information from design and manufacturingdata, and facilitates interdisciplinary problem solving for enhanceddecision making. ..Audience:. The book is aimed at both academic and practisingaudiences. It can serve as a reference or textbook for senior orgraduate level students in Engineering, Computer, and ManagementSciences who are interested in data mining technologies. The book willbe useful for practitioners interested in utilizing data miningtechniques in design and manufacturing as well as for computersoftware developers eng
出版日期Book 2001
關鍵詞DES; classification; data mining; genetic algorithm; information; knowledge; knowledge discovery; learning;
版次1
doihttps://doi.org/10.1007/978-1-4757-4911-3
isbn_softcover978-1-4419-5205-9
isbn_ebook978-1-4757-4911-3Series ISSN 1569-2698 Series E-ISSN 2468-8738
issn_series 1569-2698
copyrightSpringer Science+Business Media Dordrecht 2001
The information of publication is updating

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Terminology in fault detection and diagnosisting which design goals are achievable, and selecting a formulation of the search space. We use standard tree-induction algorithms (C4.5 and CART). We present results in two realistic engineering domains: racing yachts, and supersonic aircraft. Our experimental results show that using inductive lear
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Vaibhav K Arghode,Ashwani K. Gupta industry and on variety of databases from other application domains. The results achieved in the empirical comparison testing with well-known classification methods (like C4.5) indicate the superiority of the decomposition approach.
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John Buckmaster,Thomas L. Jackson,Ajay Kumare the proposed approach. It was found that the cost in conducting the acceptance tests and the production cycle time could be reduced remarkably without compromising the overall specifications of the acceptance tests.
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https://doi.org/10.1007/978-3-662-06297-5f the robot behaviors (tasks) at a trajectory generator level using off-line learning and the robot kinematics model only. The complete dynamics of the mobile base is taken into account by the TTC, and it’s learning is performed on a real mobile robot. Considering the advantages of genetic algorithm
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Learning to Set Up Numerical Optimizations of Engineering Designsting which design goals are achievable, and selecting a formulation of the search space. We use standard tree-induction algorithms (C4.5 and CART). We present results in two realistic engineering domains: racing yachts, and supersonic aircraft. Our experimental results show that using inductive lear
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