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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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Development of New Genetic Algorithm Software for Blow Mould Process
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Development of optimization Alghorithm for uncertain non-linear dynamical system
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A New Optimization Algorithm based on Copulation Behavior of Simine Jackals
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Thus, a new algorithm known as infection evolution (IE) was developed in this study. …”
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms
Published 2017“…One of BIAs, artificial bee colony (ABC) optimization algorithm, has shown excellent performance in many applications compared to other optimization algorithms. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…Thirdly, this study uses SHAP framework to improve the interpretability of the new algorithm (EBGWO-CatBoost), and solves the problem of the weak interpretability of the new algorithm. …”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks
Published 2011“…TCP researchers evaluated the performance and fairness of different TCP protocols on the basis of new algorithms. The new High-Speed Transport Control Protocols (HS-TCP) were developed but there are still many problems regarding to bandwidth utilization, throughput and packet loss rate. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
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Hybrid particle swarm optimization algorithm with fine tuning operators
Published 2009“…This paper introduces a new approach called hybrid particle swarm optimization like algorithm (hybrid PSO) with fine tuning operators to solve optimisation problems. …”
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