Search Results - (( time optimization based algorithm ) OR ( parameter adaptation method algorithm ))
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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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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…In the sizing of the SAPV system, the mutation adaptive DE (MADE) algorithm based multi-objective functions minimizes three constraint objective functions. …”
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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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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. …”
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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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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Published 2023“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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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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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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Particle swarm optimization-based model-free adaptive control for time-varying batch processes
Published 2024“…Concerning the mentioned problems, this study proposes to investigate the application of the particle swarm optimization-based model-free adaptive control (PSO-MFAC) method for time-varying batch processes. …”
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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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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
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Artificial intelligence technique in solving nano-process parameter optimization problem / Norlina Mohd Sabri...[et al.]
Published 2017“…Three artificial intelligence techniques have been selected to solve this parameter optimization problem. The techniques are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The performances obtained show that the optimized APFLC is better than the non-optimize APFLC in terms of RMSE and the settling time.…”
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