Search Results - (( java segmentation using algorithm ) OR ( programming adaptive evolutionary algorithm ))
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Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polyn...
Published 2016“…Hence, in this paper, an adaptive mutation operator based multi-objective evolutionary programming is presented. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The adaptive repository mechanism is a general scheme and can be embedded with high flexibility into any population-based evolutionary algorithm. …”
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Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system
Published 2013“…The purpose of this thesis is to presents a new technique namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
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Optimized processing of satellite signal via evolutionary search algorithm
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Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Conference Approval System (e-CoAS) / Nor Hidayah Rahim
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Pharmacy Management System (PhaMSys)/ Norfatin Liyana Yussof
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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