Search Results - (( based optimization based algorithm ) OR ( normal distribution function algorithm ))
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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Profit-based optimal generation scheduling of a microgrid
Published 2023“…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”
Conference paper -
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For this purpose, the normal distributions are applied to each class. The parameters of this distribution are optimized by applying the proposed MOHA. …”
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4
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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5
Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
Published 2023“…The combination of the high-Tc SQUID magnetometer and the PSO-based reconstruction technique offers a powerful approach for characterizing the MNP core size distribution, and further improvements can be expected from the recent state-of-the-art optimization algorithm to optimize further the computation time and the best objective function value.…”
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Performance Improvement of Multiobjective Optimal Power Flow-Based Renewable Energy Sources Using Intelligent Algorithm
Published 2022“…Weibull and lognormal probability distribution functions (PDFs) are respectively adopted to describe uncertainties in wind speed and solar irradiance. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The NPO was tested and evaluated based on sixty unconstrained benchmark test functions. …”
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8
Tasks Distribution In Driver Scheduling Using Dynamic Set Of Bandwidth In Harmony Search Algorithm With 2-Opt
Published 2021“…The existing techniques (HS and its variants) have issues in terms of searching strategy (exploration and exploitation), slow convergence rate and high computation time for solving the scheduling problems maximally or near to optimal one. Therefore, a tasks distribution in driver scheduling using dynamic set of bandwidth in harmony search algorithm with 2-opt (SBHS2-opt) was proposed in this research. …”
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9
Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…One of the models considers a Normal distribution function for demand, and another one, a Uniform distribution function. …”
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Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The optimal sizing and allocation of distributed generation problem is based on active power loss reduction and voltage profiles improvement. …”
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12
Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer
Published 2024“…The proposed strategy reduced the system’s total net present cost, power loss, and emissions by (1.06), (8.69), and (17.19), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Book Section -
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Acltshe-Amts: A New Adaptive Brain Tumour Enhancement And Segmentation Approaches
Published 2024“…In the second stage, a new approach called Adaptive Multilevel Thresholding Segmentation (AMTS) is proposed for unsupervised brain tumor xxi subregion segmentation from normal brain tissue. The AMTS approach segments and extracts the whole tumor, core tumor, and enhanced tumor regions from the brain MR images, integrating the Multi-Objective Grasshopper Optimization algorithm, Kapur Entropy, Cross-Entropy, and Localized active contour.…”
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15
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The model was trained based on the Leven-berg Marquardt algorithm with sigmoid activation functions. …”
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16
Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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Conference or Workshop Item -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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