Search Results - (( based application study algorithm ) OR ( parameter optimization based algorithm ))
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
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A Comparison Study Between Two Algorithms Particle Swarm Optimization for Depth Control of Underwater Remotely Operated Vehicle
Published 2013“…This paper investigates two algorithms based on particle swarm optimization (PSO) to obtain optimum parameter. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…However, to fully utilize the algorithm, the parameter of the algorithm need to be set properly. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Optimization of milling parameters using ant colony optimization
Published 2008“…This study is to develop optimization procedures based on the Ant Colony Optimization (ACO). …”
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Undergraduates Project Papers -
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DC MOTOR CONTROL USING GENETIC ALGORITHM BASED PID
Published 2011“…This dissertation presents the research that had been done on the chosen topic, works done and results acquired throughout the Final Year Project for two semesters, about the DC Motor Control using Genetic Algorithm based PID. The objectives of this project are to optimize speed control of the DC motor by using Genetic Algorithm based PID, to improve the performances of the DC motor controller in term of rise time, settling time, maximum overshoot and Integral of Time Absolute Error (ITAE) and to decide the best parameters to be used for Genetic Algorithm that can optimize the performance of a DC Motor ( eg: population size, mutation rate and crossover value). …”
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A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique
Published 2022“…Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D) is one of the algorithms that utilize the concepts of decomposition and neighbourhood to solve multi-objective problems. …”
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
Published 2023“…In the first part, the study assessed, the effectiveness of various metaheuristic algorithms (PSO-IWO-ICA) in tuning the parameters of the ANN prediction structure in order to get the optimal parameter of the ANN. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Besides that, another limitation that exists in previous researches is the absence of parameter optimization for the classifier. Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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