Titlebook: Neural Information Processing; 19th International C Tingwen Huang,Zhigang Zeng,Chi Sing Leung Conference proceedings 2012 Springer-Verlag B

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书目名称Neural Information Processing影响因子(影响力)




书目名称Neural Information Processing影响因子(影响力)学科排名




书目名称Neural Information Processing网络公开度




书目名称Neural Information Processing网络公开度学科排名




书目名称Neural Information Processing被引频次




书目名称Neural Information Processing被引频次学科排名




书目名称Neural Information Processing年度引用




书目名称Neural Information Processing年度引用学科排名




书目名称Neural Information Processing读者反馈




书目名称Neural Information Processing读者反馈学科排名

放大

Modelling Energy Use and Fuel Consumption in Wheat Production Using Indirect Factors and Artificial n based on farm conditions, farmers’ social considerations, farm operation, machinery condition and farm inputs, arable farms in Canterbury with an error margin of ±12% (± 2900 MJ/ha) and ±8% (± 5.6 l/ha), respectively.

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Alpha-Cells

Conference proceedings 2012lected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The 5 volumes represent 5 topical sections containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.

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0302-9743 and LNCS 7667 constitutes the proceedings of the 19th International Conference on Neural Information Processing, ICONIP 2012, held in Doha, Qatar, in November 2012. .The 423 regular session papers presented were carefully reviewed and selected from numerous submissions. These papers cover all major

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招致

A Gaussian Mixture Model Based System for Detection of Macula in Fundus Images detection of macular region. We evaluate the proposed technique using publicly available fundus image database MESSIDOR. The results show the validity of proposed system and are found to be competitive with previous results in the literature.

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indices

Assessment of Financial Risk Prediction Models with Multi-criteria Decision Making Methodsudy is carried out to evaluate the performance of ten algorithms over six real-life credit risk data sets. The results reveal that the use of a unique performance measure may lead to unreliable conclusions, whereas this situation can be overcome by the application of multi-criteria decision making techniques.

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