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Titlebook: Engineering Applications of Neural Networks; 11th International C Dominic Palmer-Brown,Chrisina Draganova,Haris Mour Conference proceedings

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書目名稱Engineering Applications of Neural Networks
副標(biāo)題11th International C
編輯Dominic Palmer-Brown,Chrisina Draganova,Haris Mour
視頻videohttp://file.papertrans.cn/311/310714/310714.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Engineering Applications of Neural Networks; 11th International C Dominic Palmer-Brown,Chrisina Draganova,Haris Mour Conference proceedings
描述A cursory glance at the table of contents of EANN 2009 reveals the am- ing range of neural network and related applications. A random but revealing sample includes: reducing urban concentration, entropy topography in epil- tic electroencephalography, phytoplanktonic species recognition, revealing the structure of childhood abdominal pain data, robot control, discriminating angry and happy facial expressions, ?ood forecasting, and assessing credit worthiness. The diverse nature of applications demonstrates the vitality of neural comp- ing and related soft computing approaches, and their relevance to many key contemporary technological challenges. It also illustrates the value of EANN in bringing together a broad spectrum of delegates from across the world to learn from each other’s related methods. Variations and extensions of many methods are well represented in the proceedings, ranging from support vector machines, fuzzy reasoning, and Bayesian methods to snap-drift and spiking neurons. This year EANN accepted approximately 40% of submitted papers for fu- length presentation at the conference. All members of the Program Committee were asked to participate in the reviewing process.
出版日期Conference proceedings 2009
關(guān)鍵詞Fuzzy; Software; artificial intelligence; cluster analysis; data mining; data reconstruction; development;
版次1
doihttps://doi.org/10.1007/978-3-642-03969-0
isbn_softcover978-3-642-03968-3
isbn_ebook978-3-642-03969-0Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer-Verlag Berlin Heidelberg 2009
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Can Virtual Humans Teach Empathy?a back-propagation (BP) algorithm, trained on the peaks of Polonium, extracted from many spectra of real samples analyzed in the laboratory. With this method, we have achieved a fitting procedure that does not introduce any error greater than the error of measurement, evaluated to be 10%.
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Teaching English as a Foreign Languagegularization by early stopping provides networks with lower complexity and more accurate predicted hydrographs than regularization by weight decay. Satisfactory results can thus be obtained up to a forecasting horizon of three hours, thereby allowing an early warning of the populations.
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