Search Results - (( java segmentation using algorithm ) OR ( some evolutionary process algorithm ))
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Maintain optimal configurations for large configurable systems using multi-objective optimization
Published 2022“…The different approaches have been presented by Search-based software engineering (SBSE) to resolve the software engineering issues into computational solutions using some metaheuristic approach. Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. …”
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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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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The results show that Volterra model with PSO–KS is preferable for fast identification process, while ABC–KS method is preferable for accurate identification process. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…At the same time implementing elitism feature increases the computational complexity of the algorithm. Furthermore, niching strategies in some algorithms play an important role in delivering a diverse set of solutions. …”
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin
Published 2006“…The methods that wilt be applied are conventional statistical methods Markowitz Optimization as well as evolutionary programming (EP) utilizing genetic algorithms. …”
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch
Published 2016“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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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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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The results show that Volterra model with PSO-KS is preferable for fast identification process, while ABC-KS method is preferable for accurate identification process. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey
Published 2022“…Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Multi-objective optimization of HRES by Evolutionary Algorithm have become attractive in recent years due to the effectiveness of such algorithms for complicated problems. …”
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
Published 2013“…Training an artificial neural network (ANN) is an optimization task since it is desired to find optimal neurons‘ weight of a neural network in an iterative training process. Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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An Evolutionary Stream Clustering Technique for Outlier Detection
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…The proposed technique is named Evolutionary Cost-Cognizant Regression Test Case Prioritization (ECRTP). …”
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