Search Results - (( evolution optimization techniques ) OR ( simulation optimization techniques ))
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1
Comparative Study of Economic Dispatch by Using Various Optimization Techniques
Published 2014“…The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA). …”
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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy
Published 2019“…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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Computational intelligence based approach for enhanced distance relay design
Published 2024text::Final Year Project -
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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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5
Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. …”
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Proceeding Paper -
6
Performance study of fractional frequency reuse in ofdma network / Mohamad Hussain F Snosi
Published 2017“…With the use of MATLAB simulation, which is highly configurable, this project will study a performance of frequency reuse technique in OFDMA. …”
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica...
Published 2021“…Originality/value: Attempted to develop a system with different optimization techniques. © 2020, Emerald Publishing Limited.…”
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Evolving controllers for simulated car racing using differential evolution
Published 2013“…This paper presents an initial approach for creating autonomous controllers for the car racing game using a hybrid technique. The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known car racing game, namely The Open Racing Car Simulator (TORCS). …”
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DE-based robust controller design for helicopter cruise control
Published 2014“…The proposed controller design attempts to simplify this complicated task where the automated design is employed via DE-based modern optimization. The effectiveness of the proposed controller design technique is presented by comparing its performance with that of conventional LQR-based controllers in computer simulation.…”
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DE-based Robust Feedback Controller for Longitudinal Cruise Control of Helicopter
Published 2011“…This paper presents a robust state feedback controller tuning via constrained optimization using DE (differential evolution). The controller gain is optimized based on linear state-space model of the plant such that the closed-loop system achieves maximum stability radius. …”
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11
A novel cell-selection optimization handover for long-term evolution (LTE) macrocellusing fuzzy TOPSIS
Published 2016“…This improvement stems from the highly reliable cell-selection technique that leads to increased throughput of the cell with a successful handover. …”
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Metaheuristic techniques in enhancing the efficiency and performance of thermo-electric cooling devices
Published 2017“…The objective of this paper is to focus on the technical issues of single-stage thermo-electric coolers (TECs) and two-stage TECs and then apply new methods in optimizing the dimensions of TECs. In detail, some metaheuristics-simulated annealing (SA) and differential evolution (DE)-are applied to search the optimal design parameters of both types of TEC, which yielded cooling rates and coefficients of performance (COPs) individually and simultaneously. …”
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Optimal HE-PWM inverter switching patterns using differential evolution algorithm
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Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…Simulation results highlight the superiority of the proposed system in terms of accuracy and convergence as compared with other evolution algorithms (genetic optimization, particle swarm optimization, and ant colony optimization) for different communication modes (power saving mode, high throughput mode, emergency communication mode, and balanced mode). � Czech Technical University in Prague, 2019.…”
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Optimizing railway safety by analyzing human reliability techniques - A review
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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17
Robust H-infinity controller synthesis using multi-objectives differential evolution algorithm (MODE) for two-mass-spring system
Published 2011“…The conflicting nature of these objectives has made such design exercise a tedious endeavor. In this study, the optimal-tuning of the Hinfinity controller parameters using multi-objective differential evolution (MODE) technique is proposed, and apply for control of a two-mass-spring system which represents a typical benchmark robust control problem. …”
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Optimizing of PID controller for flexible link system using a Pareto-based Multi-objective differential (PMODE) evolution
Published 2011“…This can be viewed like many other real-life control problems as a multi-objectives optimization problem in which an optimal compromise between the design objectives is required. …”
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20
PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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