Titlebook: Emerging Intelligent Computing Technology and Applications; 9th International Co De-Shuang Huang,Phalguni Gupta,Michael Gromiha Conference

中間時期

書目名稱Emerging Intelligent Computing Technology and Applications影響因子(影響力)




書目名稱Emerging Intelligent Computing Technology and Applications影響因子(影響力)學科排名




書目名稱Emerging Intelligent Computing Technology and Applications網(wǎng)絡公開度




書目名稱Emerging Intelligent Computing Technology and Applications網(wǎng)絡公開度學科排名




書目名稱Emerging Intelligent Computing Technology and Applications被引頻次




書目名稱Emerging Intelligent Computing Technology and Applications被引頻次學科排名




書目名稱Emerging Intelligent Computing Technology and Applications年度引用




書目名稱Emerging Intelligent Computing Technology and Applications年度引用學科排名




書目名稱Emerging Intelligent Computing Technology and Applications讀者反饋




書目名稱Emerging Intelligent Computing Technology and Applications讀者反饋學科排名

NAG

Arboreal

https://doi.org/10.1007/978-3-322-80407-5nential stability of these networks. The derived result improves and extends some related results in the literature. Finally, an illustrative example is provided to demonstrate the effectiveness of our theoretical results.

epidermis

Karl Steinbuch,Werner Rupprechtclassification error of the model. We show the performance of the multi-objectivization approach on five data sets and compare it to a surrogate based single-objective algorithm for the same problem. Moreover, we compare the multi-objectivization approach to two surrogate based approaches – a single-objective one and a multi-objective one.

易彎曲

Psa617

Psa617

Karl Steinbuch,Werner Rupprechtng and testing of two well known classifiers- Extreme Learning Machine (ELM) and Support Vector Machine (SVM). The performance evaluation of ELM and SVM classifiers shows that the proposed feature selection method works well with these classifiers.

Irremediable

BALE

,Digitale übertragung im Basisband,an three previously published differential coexpression analysis (DCEA) methods. We applied the new approach to a public available type 2 diabetes (T2D) expression dataset, and many additional discoveries can be found through our method.

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