Titlebook: Cognitive Computing and Information Processing; Third International T.N. Nagabhushan,V. N. Manjunath Aradhya,Chayadevi Conference proceedi

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Chiral anomalies and differential geometry,path set by applying dominance principle. Literature reveals that solving such problems within polynomial time is difficult even for smaller instances using traditional algorithms. This study investigates the convergence of swarm intelligent algorithms and compares them with performance metrics such

Lasting

https://doi.org/10.1007/3-540-16064-7 that maintenance of diversity in the swarm is very important for preventing the swarm from converging prematurely for multimodal function problems. In this paper, an improved version of the Directionally Driven Self-Regulating Particle Swarm Optimization (DD-SRPSO) algorithm is proposed with a mech

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Chiral anomalies and differential geometry,nt of learning (JOL). The input is divided into subsets. Each subset is learnt by the learning algorithm, which in turn is regulated by the metacognitive layer. Each model begins with zero rules. The underlying learning algorithm then employs prediction error and novelty of sample to add rules to th

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/c/image/229006.jpg

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Conference proceedings 2018ld in Bengaluru, India, in December 2017.. The 43 revised full papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on cognitive computing in medical information processing; cognitive computing and its applications; cognitive computing in video analytics..

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