Search Results - (( parameter optimization method algorithm ) OR ( parameter solution learning algorithm ))
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1
Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…ANFIS accuracy depends on the parameters it is trained with. Keeping in view the drawbacks of gradients based learning of ANFIS using gradient descent and least square methods in two-pass learning algorithm, many have trained ANFIS using metaheuristic algorithms. …”
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2
Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023Article -
3
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Conference or Workshop Item -
4
Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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Thesis -
5
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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7
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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8
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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9
Differential evolution for neural networks learning enhancement
Published 2008“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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10
Optimal power flow using a hybridization algorithm of arithmetic optimization and aquila optimizer
Published 2024“…The proposed AO-AOA algorithm follows two strategies to find a better optimal solution. …”
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11
Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm
Published 2025“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Thesis -
13
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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14
An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system
Published 2023“…Damping; Eigenvalues and eigenfunctions; Electric power systems; Learning algorithms; Optimization; Particle swarm optimization (PSO); Problem solving; State space methods; Test facilities; Backtracking search algorithms; Multi machine power system; Power system damping; Power system oscillations; Power system stability; Power System Stabilizer; System stability; algorithm; Article; backtracking search algorithm; bacterial foraging optimization algorithm; machine; mathematical analysis; mathematical computing; mathematical parameters; particle swarm optimization; power supply; power system stabilizer; process optimization; statistical model…”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Final Year Project / Dissertation / Thesis -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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17
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…A modified global search method with fewer parameters is devised to rapidly identify approximated location of GMPP. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Student Project -
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Thesis -
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