Titlebook: Recent Developments in Intelligent Systems and Interactive Applications; Proceedings of the I Fatos Xhafa,Srikanta Patnaik,Zhengtao Yu Conf

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Adaptive Stochastic Ranking Schemes for Constrained Evolutionary Optimizationclassic SR is applied to choose one of constraint violation and fitness as the basis for comparison of a pair of individuals. This paper presents two adaptive SR schemes, referred to as a linear decline SR and a reciprocal decline SR respectively, which are inspired by cooling schedules for simulate

construct

A Case-Based Reasoning Method with Relative Entropy and TOPSIS Integrationision-makers. At first we design the similarity calculation methods according to the different case feature such as crisp number, interval number, crisp symbols and fuzzy linguistic variables. The similarity of each feature is calculated between target case and each historical case which step gets a

Esophagus

An Algorithm Design for Electrical Impedance Tomography Based on Levenberg Methodithm principle for nonlinear approximation is introduced and then the ideas to apply the Levenberg algorithm into our electrical impedance tomography outlined, and finally a detailed algorithm for electrical impedance tomography experiments is described. Initial simulations for the proposed algorith

CANON

无聊的人

GA Based Optimization of Sign Regressor FLANN Model for Channel Equalization accordingly. The ISI component at the output of equalizer is forced to zero on use of LTI system having appropriate transfer function. The deteriorating effect of inter symbol interference ia adequately compensated by the method of adaptive equalization. In this paper, the channel has been equalize

Consequence

Dictation

Parallelization of the Conical Area Evolutionary Algorithm on Message-Passing Clusterssented here to obtain a satisfactory balance between convergence speed and communication costs. Experimental results on ZDT test problems indicate that the peCAEA obtains satisfactory solution quality with good speedup on clusters.

Blatant

infringe

A Case-Based Reasoning Method with Relative Entropy and TOPSIS Integration time, RTCBR is tested on UCI data sets and compared with other two well-known CBR algorithms such as Euclidean distance CBR (ECBR) and Manhuttan distance CBR (MCBR). Empirical results indicate that RTCBR outperforms ECBR, MCBR, which can effectively improve the accuracy of CBR system.

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