Search Results - (( probable optimization approach algorithm ) OR ( parameter optimization method algorithm ))
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1
A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…A novel meta-heuristic optimization approach termed the Memory-Guided Jaya algorithm (MG-Jaya), is specifically tailored to address diverse challenges in multi-objective optimal power flow (MOOPF) incorporating RES. …”
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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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4
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
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Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah
Published 2010“…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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7
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model
Published 2024“…The experiments in this study compare the SWMTop-kDelta algorithm with two previous researchers and two baseline approach algorithms to evaluate their effectiveness. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…Besides, a Bayesian uncertainty analysis was carried out to quantify the model output behaviors due to derivation from the uncertainty in the input parameters. A Bayesian method for CNN using TensorFlow Probability was used in this study. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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GENETIC FUZZY FILTER BASED ON MAD AND ROAD TO REMOVE MIXED IMPULSE NOISE
Published 2010“…In this thesis, a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD) is proposed. The proposed method consists of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization using genetic algorithms (GA) to perform efficient and effective noise removal. …”
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16
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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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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Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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20
Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…This type of outcome is valuable to the decision-maker to implement a more optimal strategy for reducing the probability of landslides and its associated damages. ? …”
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