Search Results - probable distribution ((centre algorithm) OR (genetic algorithm))
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The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile
Published 2014“…This paper proposes heuristic Genetic Algorithm known as SIGA (Selection Improvement in Genetic Algorithm) in consideration of genetic operator probabilities likewise the progression of switch adjustment in Distribution Network Reconfiguration (DNR) while satisfying the parameters constraints. …”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…The activation function in this neural network model then estimated using genetic algorithms. Determination of the best factor is carried out in a genetic algorithm by combining several parameters of the crossover probability (Pc) and mutation probability (Pm). …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…This research proposes the enhanced metaheuristic algorithms that exploit the power of Tabu Search, Genetic Algorithm, and Simulated Annealing for solving VRPSD. …”
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A breeder genetic algorithm for vehicle routing problem with stochastic demands
Published 2009“…The BGA was compared to the standard Genetic Algorithm on a set of randomly generated problems following some discrete probability distributions. …”
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Population genetic structure of Malayan Tapir (Tapirus indicus Desmarest) in Peninsular Malaysia
Published 2019“…Eight polymorphic markers were successfully developed and used in the population genetic structure analysis. Using K-means clustering algorithm, five clusters were inferred among the wild samples (N = 57), which showed a complex population structure probably comprising multiple continuous populations that also experiencing considerably restricted gene flow due to isolation by geographical barriers especially mountain ranges. …”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…A genetic algorithm based on speed invariant and the elite algorithm is proposed to solve the multi-TSP assignment problem. …”
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Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks
Published 2021“…This chapter proposes a mixed-integer optimization using genetic algorithm (MIOGA) for determining the optimum sizes and placements of battery-sourced solar photovoltaic (B-SSPV) plants to reduce the total energy losses in distribution networks. …”
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Probabilistic load flow�based optimal placement and sizing of distributed generators
Published 2023“…Electric load flow; Environmental impact; Genetic algorithms; Investments; Location; Operating costs; Probability distributions; Distributed generation; Distributed generation resources; Distributed generators; Distribution network; Electrical energy demand; Flow based; Location optimization; Optimal placement and sizings; Probabilistic load flow; Distributed power generation…”
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Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes
Published 2025“…The research leverages Artificial Intelligence (AI)-based Genetic Algorithms (GA) and game theory to address critical challenges in resource allocation. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…One of the main problems of this method is premature convergence and to improve this problem, the compound of the particle swarm algorithm and genetic algorithm were evaluated. The basis of this compound is in such a way that the advantages of the Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) have been applied simultaneously. …”
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Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient
Published 2023“…Bioinformatics; Correlation methods; Gaussian distribution; Gaussian noise (electronic); Genes; DREAM; Gaussian model; Gene regulatory networks; Pearson correlation coefficients; Probability and statistics; Complex networks; algorithm; biological model; biology; gene inactivation; gene regulatory network; genetics; human; Algorithms; Computational Biology; Gene Knockout Techniques; Gene Regulatory Networks; Humans; Models, Genetic…”
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A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems
Published 2019“…The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. …”
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Sizing and placement of battery-coupled distributed photovoltaic generations
Published 2017“…To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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Enhanced ABD-LSSVM for energy fuel price prediction
Published 2013“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong
Published 2014“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. The non-dominated sorting genetic algorithm II (NSGA-II), the improved strength Pareto evolutionary algorithm II (SPEA-II), and the compressed objective genetic algorithm II (COGA-II) were applied. …”
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