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Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel
Published 2020“…In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. …”
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Article -
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Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel
Published 2019“…In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication
Published 2021“…By using the optimization min-sum belief propagation approach, a low complexity min-sum (MS) based decoding algorithm called Variable Global Optimization Min-Sum (VGOMS) has been developed. …”
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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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Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…The algorithm with the least estimation error is selected for optimization. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Monograph -
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Optimization of super twisting sliding mode control gains using Taguchi method
Published 2018“…Optimized algorithm achieved 9.3% of reduction in root mean square of tracking error and 38.4% of reduction in chattering experimentally.…”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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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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Improved recurrent NARX neural network model for state of charge estimation of lithium-ion battery using pso algorithm
Published 2023Conference Paper -
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PID-Ant Colony Optimization (ACO) control for electric power assist steering system for electric vehicle
Published 2013“…Simulation results shows the performance and effectiveness of using ACO algorithm for PID tuning.…”
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Proceeding Paper -
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Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The evaluation results the proposed KGA model using several time series, namely the sunspot data, the Mackey-Glass time series, and electrical load forecasting using data from several econometric factors, as well as historical electricity demand data, show that the proposed KGA model is eflective in finding the optimal number ofneurons for the hidden layer of a BP network that is used to perform time series prediction.…”
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Thesis -
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
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