Search Results - (( parameter optimization method algorithm ) OR ( initial selection method algorithm ))
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…After the optimization of the weights by modified version of the Kohonen Network method these weights will be set as the initial centres of the Gustafson-Kessel (GK) algorithm. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…A modified global search method with fewer parameters is devised to rapidly identify approximated location of GMPP. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…However, a systematic method for optimizing these parameters is still an active research area. …”
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Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm
Published 2023“…Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…In this study, support vector machines (SVM) is employed to recognize the patterns for studied translational initiation sites in alternative weak context. The method has been optimized with the best parameters selected; c = 100, E = 10-6 and ex = 2 for non linear kernel function. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. To achieve optimal RBFN-DDA performance, HS (or GSA) is proposed to optimize the center and the width of each hidden unit in a trained RBFN. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Artificial Neural Networks (ANNs) are one of the most popular methods for classification in condition diagnosis of bearing systems.Regarding to ANNs performance, ANNs parameters have important role especially connectivity weights.In several running of learning processes with the same structure of ANNs, we can obtain different accuracy significantly since initial weights are selected randomly. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Extensive experimentation with genetic algorithm parameters has yielded promising results, notably a parameter set (population size = 12, generation size = 30, mutation rate = 0.2) demonstrating robust performance, achieving optimal timetables with swift convergence and minimal conflicts. …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia
Published 2025“…However, SES is seen to underperform compared to other models due to parameter selection and initial value setting. Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…The first method isbased on fuzzy genetic algorithm to overcome the premature convergence. …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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