Search Results - (( based optimization method algorithm ) OR ( changes optimization strategy algorithm ))
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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2
Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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3
Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…The second experiment result shows both GA and DE algorithms can generate optimal solutions with very high fitness scores but the cost of spawning was extremely high. …”
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4
A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The standard DE algorithm is known as a fixed length optimizer, while our problem demands the need for methods that aren’t tolerated to a fixed individual size, and that was made by altering the mutation and crossover strategies as well as the selection operation. …”
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6
The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Particle Swarm Optimization Of Direct Yaw Control Using Linear Quadratic Integral For Vehicle Stability
Published 2020“…Therefore, in order to achieve an optimum performance of the DYC, the LQI controller gains have been properly selected by using the Particle Swarm Optimization (PSO) algorithm. Apart from optimizing the controller parameters, the LQI with optimization using PSO algorithm capable to maintain the stability of the vehicle in several manoeuvre circumstances. …”
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Genetic algorithm tuning based PID Controller for liquid-level tank system
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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A family of least change diagonally quasi-Newton methods for nonlinear equations
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Garra Rufa‐inspired optimization technique
Published 2020“…In welldeveloped optimization techniques, such as swarm optimization (PSO) and the firefly algorithm (FA), getting around the initial optimal value of the group and randomly checking the effect of the surrounding points may lead to a better solution than the initial optimal value. …”
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14
An improved hybrid method combined with a cloud-based supervisory control to facilitate smooth coordination under low-inertia grids
Published 2025“…Furthermore, integrated with IoT-based control, the optimized hybrid generalized droop method mitigates transient instabilities, as evidenced by a 29 % reduction in voltage overshoot during fault clearance. …”
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15
HDRA: A Haybird Data Reduction and Routing Algorithm
Published 2024“…Recent studies on data reduction methods have shown that sensor nodes often transmit data directly (single hop) to the base station (BS). …”
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HDRA: A Haybird Data Reduction and Routing Algorithm
Published 2024“…Recent studies on data reduction methods have shown that sensor nodes often transmit data directly (single hop) to the base station (BS). …”
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Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN.
Published 2024“…It can be utilized with multiple convolutional and hidden layers, trained using specific algorithms to solve power allocation problems. Simulation results demonstrate that the proposed framework improves power allocation, overall data rates, and Energy efficiency by around 15% compared to traditional deep neural network (DNN) algorithms, methods and strategies.…”
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A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
Published 1999“…Two modified methods for unconstrained optimization are presented. …”
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Fault-tolerant power extraction strategy for photovoltaic energy systems
Published 2018“…The FDI method is based on monitoring the PV panel generated power for the presence of abrupt changes; the MPPT reconfiguration is based on a combination between Incremental Conductance (IncCond) Algorithm and an Improved Current-based Particle Swarm Optimization (ICPSO) tracking technique. …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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