Search Results - (( simulation optimization model algorithm ) OR ( basic optimization techniques algorithm ))
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Thesis -
2
Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…The genetic algorithm technique is explained and the real number representation of genetic algorithm is modeled. …”
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3
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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4
Ant colony optimization for solving economic dispatch of power system: article / Muhammad Shukri Che Hashim
Published 2009“…In this study, an optimization technique called Ant Colony Optimization (ACO) had been applied in solving ED problem. …”
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Ant colony optimization for solving economic dispatch of power system / Muhammad Shukri Che Hashim
Published 2009“…In this study, an optimization technique called Ant Colony Optimization (ACO) had been applied in solving ED problem. …”
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6
Simulation Of Token Bucket Algorithm For Network Traffic Performance
Published 2020“…In this research, the optimal size of bucket in Token Bucket Algorithm(TBA)is used as one of the techniques in traffic shaping. …”
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Evaluation method of rationality of urban landscape facility design based on neural network
Published 2025“…Specifically, our work encompasses the following key aspects: 1) Introducing the relevant theoretical knowledge and research progress in urban landscape facility design. 2) Elucidating the basic principles and structures of the backpropagation neural network (BPNN), along with the proposal of an improved genetic algorithm-back propagation neural network (GA-BP) to address the limitations of BPNN. 3) Conducting experiments to determine the optimal parameters for the GA-BP model once training is finished. …”
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An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection
Published 2012“…The three techniques with different planting lining direction lead to different number of trees, therefore the technique promotes the highest number of tree is optimal technique. …”
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Conference or Workshop Item -
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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14
Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers -
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper involves engine modeling in 1D software simulation environment, GT-Power. …”
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Proceeding Paper -
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING
Published 2009“…Converter models for simulation are designed for the forward and backup modes of operation. …”
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Citation Index Journal -
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING
Published 2009“…Converter models for simulation are designed for the forward and backup modes of operation. …”
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Citation Index Journal -
18
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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Final Year Project -
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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq
Published 2016“…The purpose of this study was to formulate and improve an approach of a genetic algorithm optimization model (GAOM) in order to increase the maximization of annual hydropower generation for a single reservoir. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm
Published 2013“…The potential of genetic algorithm in optimization was utilized in the proposed hybrid model to minimize the error prediction for regions of cutting conditions away from the Taguchi based factor level points. …”
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