Search Results - (( re evaluation study algorithm ) OR ( based optimization based algorithm ))*
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Performance evaluation metrics for multi-objective evolutionary algorithms in search-based software engineering: systematic literature review
Published 2021“…Many recent studies have shown that various multi-objective evolutionary algorithms have been widely applied in the field of search-based software engineering (SBSE) for optimal solutions. …”
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2
Sustainable renewable energy resources utilization in rural areas
Published 2016“…A region having ten different sub-regions has been considered for the optimization based on transportation algorithm. The partitions are made based on customer segmentation to ensure that various scattered demand for the RE is represented at the best location to enhance energy optimization by minimizing the energy loss during transmission. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…A region having ten different sub-regions has been considered for the optimization based on transportation algorithm. The partitions are made based on customer segmentation to ensure that various scattered demand for the RE is represented at the best location to enhance energy optimization by minimizing the energy loss during transmission. …”
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4
Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…Furthermore, genetic algorithm (GA) has been used to optimize the FLCs performance. …”
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5
Analysing ratio-based controllers against motivational game theory in peer-to-peer renewable energy trading
Published 2024“…This inefficiency highlights the need for a sophisticated controller equipped with optimal algorithms. Thus, the aim of this research is to design proper models for peer-to-peer trading algorithms for RE to address these inefficiencies. …”
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Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau
Published 2020“…This study presents an augmented reality (AR) based facility layout planning (FLP) system with an optimization algorithm to assist facility layout designers in decision making. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda
Published 2006“…Disagreement of grade given by two human judges, time consuming and high evaluation cost became a reason of research on Computer-based Assessment System (CbAS) been studied. …”
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10
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The approach is based on optimization of selected test case from test suite T. …”
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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill
Published 2019“…These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model’s accuracy. …”
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Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO)
Published 2024“…The highlight of our algorithm, GiPSO, exhibits improvement in optimizing the source of leakage in high precision Objective Function Value (OFV). …”
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14
Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
Published 2024“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…The main objective of this study is to identify the demand patterns and optimizing the lecturer’s contribution by maintaining a class sizes of maximum number of students in each class is 30 and a teaching load of up to 20 credit hours per lecturer. …”
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The evaluation is carried out based on multiple electric vehicles (EV) drive cycles with different Li-ion cells chemistry at varying ambient temperatures. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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