By Sundarapandian Vaidyanathan (auth.), Natarajan Meghanathan, Dhinaharan Nagamalai, Nabendu Chaki (eds.)
The foreign convention on Advances in Computing and data expertise (ACITY 2012) presents an outstanding foreign discussion board for either lecturers and execs for sharing wisdom and ends up in conception, technique and purposes of machine technology and knowledge expertise. the second one foreign convention on Advances in Computing and knowledge know-how (ACITY 2012), held in Chennai, India, in the course of July 13-15, 2012, lined a few subject matters in all significant fields of desktop technology and data expertise together with: networking and communications, community safeguard and functions, net and web computing, ubiquitous computing, algorithms, bioinformatics, electronic photograph processing and trend popularity, synthetic intelligence, smooth computing and functions. Upon a energy assessment technique, a couple of top of the range, proposing not just leading edge rules but in addition a based evaluate and a powerful argumentation of an analogous, have been chosen and picked up within the current complaints, that's composed of 3 various volumes.
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Extra info for Advances in Computing and Information Technology: Proceedings of the Second International Conference on Advances in Computing and Information Technology (ACITY) July 13-15, 2012, Chennai, India - Volume 2
Applied Mathematics and Computation 188(2), 1567–1579 (2007) 10. : Wairs improving classification accuracy by weighting attributes in the airs classifier. In: IEEE Congress on Evolutionary Computation, CEC 2007, pp. 3759– 3765 (2007) 11. : Medical data mining using BGA and RGA for weighting of features in fuzzy k-NN classification. In: International Conference on Machine Learning and Cybernetics, vol. 5, pp. 3070–3075 (2009) 12. : Feature-weighted knearest neighbor classifier. In: FOCI 2007, pp.
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Likewise, in HS algorithm, the value of a decision variable is selected according to one of the following rules: 1) selecting a value from Harmony Memory (HM); 2) selecting a value near to values of HM; and 3) selecting a random value in the possible range of values. HS includes some parameters which are described as follow: HM (Harmony Memory) encloses all the generated Harmony vectors. Equation (4) shows the memory. HMS (HM Size) determines the number of Harmony vectors in HM. Each vector is a solution for optimization problem.