Titlebook: Recent Innovations in Mechanical Engineering; Select Proceedings o Meghanshu Vashista,Gaurav Manik,Bhuvnesh Bhardwaj Conference proceedings

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Chandramani Goswami,Ratnesh Sharma,Shiv Ranjan Kumar,Ajay Singh,Anand Prakash optimization and paradigm of artificial evolution.Useful fo.This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing. This methodology achieves excellent results f

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Farheen Bano,Zulquernain Mallick,Abid Ali Khan,Nabila Elnahasng the techniques of evolutionary computing. This methodology achieves excellent results for defining fitness functions and representations for problems by merging evolutionary computation with mathematical optimization to produce automatic creation of emerging visual behaviors..In the first part of

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Paramjit Thakur,D. N. Raut,Fauzia Siddiqui optimization and paradigm of artificial evolution.Useful fo.This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing. This methodology achieves excellent results f

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Jitendra Gupta,Bhuvnesh Bhardwaj,Varun Sharmaation is time consuming. The run time is therefore a major consideration when designing a GA for optimisation, thus a look-up table for fitness evaluation is desirable. As a consequence, it is appropriate to limit the number of different chromosome fitness evaluations that any particular run of the

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source MDR software package. In this wrapper we also introduce a scaling method based on an exponential distribution function with a single user-adjustable parameter. Here we obtain expert knowledge from Tuned ReliefF (TuRF), a method capable of detecting attribute interactions in the absence of mai