Search Results - (( loading optimization based algorithm ) OR ( using evolution research algorithm ))
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter
Published 2018“…Differential Evolution (DE) has been gaining popularity among researchers as an effective yet simple evolutionary algorithm to solve the optimization problems. …”
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Thesis -
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Differential evolution based special protection and control scheme for contingency monitoring of transmission line overloading
Published 2017“…In this paper, a Special Protection and Control Scheme (SPCS) based on Differential Evolution (DE) algorithm for optimal generation rescheduling to mitigate line overloads in contingency conditions has been presented. …”
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Conference or Workshop Item -
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Differential Evolution Based Special Protection and Control Scheme for Contingency Monitoring of Transmission Line Overloading
Published 2017“…In this paper, a Special Protection and Control Scheme (SPCS) based on Differential Evolution (DE) algorithm for optimal generation rescheduling to mitigate line overloads in contingency conditions has been presented. …”
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Book Section -
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A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed
Published 2019“…This study presents two efficient hybrid SHEPWM algorithms, one for low and second for high-level inverters to calculate the optimized firing angles. …”
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Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced
Published 2018“…Secondly, a Hybrid Handover Parameters Optimization algorithm based on Enhanced Weight Performance (HHPO) is introduced to optimize, select suitable Handover Control Parameters (HCP) and to manage the conflict that may occur among self-optimization functions. …”
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An improved hybrid method combined with a cloud-based supervisory control to facilitate smooth coordination under low-inertia grids
Published 2025“…The presented approach synthesizes the traditional droop control and the generalized cloud-based algorithm to address challenges related to dynamic load variations and intermittent renewable energy sources. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan
Published 2020“…This project works on developing an efficient network load balancing mechanism based on the Ant Colony Optimization (ACO) algorithm. …”
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Student Project -
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In this paper, task scheduling strategy based on load balancing Quantum Particles Swarm algorithm (BLQPSO) was proposed. …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
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Evolutionary Programming (EP) based technique for secure point identification with load shedding technique in power transmission / Abdul Rahman Minhat
Published 2008“…The ability of EP to search for the optimal values of multi-load increase as compared to AVSA which is only able to conduct uniform load increase at several load buses has been identified as the strength of EP over AVSA.…”
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Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan
Published 2018“…The change in the system is signified by the change in the system frequency and tie-line (T-L) load. The performance of LFC has to be tuned properly so that the response can be optimized with a selected controller and algorithm for optimization. …”
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