Search Results - (( simulation optimization model algorithm ) OR ( data equalization based algorithm ))
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1
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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2
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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3
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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Thesis -
4
Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure
Published 2016“…In the real data simulation, both methods obtained the same model structure whereas in simulated data modelling, only DMA was able to select the correct model structure. …”
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5
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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Enhancing quality of service in Multi-Radio Multi-Channel Wireless Mesh Networks
Published 2023“…The COngestion Reduction Routing Algorithm (CORRA) tackles this challenge by evaluating link quality and interference to find optimal data paths. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Final Year Project / Dissertation / Thesis -
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Optimum calculation of tilt angles and components of standalone photovoltaic system to harvest solar energy
Published 2018“…Optimization and configuration algorithm of sizing SAPV system is implemented using MATLAB and hourly meteorological data and load demand. …”
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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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12
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 -
15
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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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
Published 2023“…Balancing; Forecasting; Stream flow; Support vector machines; Exploitation and explorations; Machine learning models; Optimisations; Optimization algorithms; Prediction modelling; Simulated annealing integrated with mayfly optimization; Streamflow prediction; Support vector regression models; Support vector regressions; Support vectors machine; Simulated annealing; algorithm; mayfly; optimization; prediction; streamflow; support vector machine; Jhelum River…”
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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