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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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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Furthermore, the EDLB algorithm enhances load balancing by 46.46%. These results highlight the effectiveness of the EDLB algorithm in addressing critical load balancing issues and surpassing existing methods. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Optimum Power Production of Small Hydropower Plant (SHP) Using Firefly Algorithm (FA) in Himreen Lake Dam (HLD), Eastern Iraq
Published 2017“…The results obtained from these two methods, namely Firefly Algorithm (FA) and Particle Swarm Optimization, (PSO) are compared. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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The optimization of resources allocation to minimize energy consumption within data center in cloud
Published 2019“…So in this research, our proposed algorithm is going to optimize the total running machine by switching off the hosts with below 30% of CPU power consumption and migrate all the VMs run under it to other hosts.But, for over-utilized hosts with more than 90% of computing resources consumption, the migration of some VMs run under it will be carried out. …”
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Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator
Published 2011“…The comparison between actual data from a different day and the prediction by the proposed method showed a match that is close enough to be considered as reliable. …”
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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.]
Published 2017“…Afterwards, data mining algorithms were applied in order to forecast electric load. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Web based applications for energy management system incorporated network reconfiguration using genetic algorithm / Wan Adnan Wan
Published 2006“…The Genetic Algorithm Based Network Reconfiguration Technique for loss minimization in the UiTM Distribution System is also proposed based on general combinatorial optimization algorithm. …”
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Feature selection and parameter optimization with GA-LSSVM in electricity price forecasting
Published 2014“…A comparative study of proposed approach with other techniques and previous research was conducted in term of forecast accuracy, where the results indicate that (1) the LSSVM with GA outperforms other methods of LSSVM and Neural Network (NN), (2) the optimization algorithm of GA gives better accuracy than Particle Swarm Optimization (PSO) and cross validation. …”
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Feature selection and parameter optimization with GA-LSSVM in electricity price forecasting
Published 2023“…A comparative study of proposed approach with other techniques and previous research was conducted in term of forecast accuracy, where the results indicate that (1) the LSSVM with GA outperforms other methods of LSSVM and Neural Network (NN), (2) the optimization algorithm of GA gives better accuracy than Particle Swarm Optimization (PSO) and cross validation. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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Energy-efficient routing using novel optimization with Tabu techniques for Wireless Sensor Network
Published 2022“…Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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