Search Results - (( model evaluation case algorithm ) OR ( global optimization based algorithm ))*
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Development of committee machine models for multiple response optimization problems
Published 2014“…The results represent Global Desirability of proposed algorithm is equal or higher than GD of case studies. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. …”
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization
Published 2021“…The findings revealed that SC-FDO achieved better performances in most cases than the original FDO and well-known optimization algorithms. …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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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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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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A study on model-free approach for liquid slosh suppression based on stochastic approximation
“…In addition, the performance of the SPSA based methods is compared to the other stochastic optimization based approaches, which also includes the variants of SPSA based method, such as Global SPSA. …”
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Research Report -
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
Published 2025text::Thesis -
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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Exponentially adaptive sine-cosine algorithm for global optimization
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Conference or Workshop Item -
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Artificial immune system based on hybrid and external memory for mathematical function optimization
Published 2023“…Artificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…To overcome this problem, an efficient Global Particle Swarm Optimization (GPSO) algorithm is proposed in this paper, based on a new updated strategy of the particle position. …”
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