Search Results - (( different optimization method algorithm ) OR ( parameter adaptation method algorithm ))
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Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…One method to mitigate this is to introduce adaptivity into the algorithm to discover good parameter settings during the search. …”
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…The hybrid method, IDBA-AFW, aims to enhance the original IDBA by incorporating the Adaptive Floyd-Warshall algorithm for graph transformation and optimization. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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Sensitivity analysis of drill wear and optimization using Adaptive Neuro fuzzy –genetic algorithm technique toward sustainable machining
Published 2018“…Effects of spindle rotational speed, feed rate and diameter of drill on tool wear were determined through Adaptive Neuro Fuzzy Inference System (ANFIS). Next, genetic algorithm (GA) was used to identify the optimal drilling parameter for different diameters of drill. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Therefore, finding the best weights in learning process is an important task for obtaining good performance of ANNs.Previous researchers have proposed some methods to get the best weights such as simple average and majority voting.However, these methods have some limitations in providing the best weights especially in condition diagnosis of bearing systems.In this paper, we propose a hybrid technique of multiple classifier-ANNs (mANNs) and adaptive probabilities in genetic algorithms (APGAs) to obtain the best weights of ANNs in order to increase the classification performance of ANNs in condition diagnosis of bearing systems. …”
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