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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Thesis -
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Conference or Workshop Item -
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…Creating a PSO algorithm-based infrastructure integrating with the recommendation system will further enhance solution to the design problem. …”
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Final Year Project -
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Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
Published 2017“…The proposed control strategy has been compared with the conventional proportional-integral-derivative (PID) controller concerning its robustness characteristic with the variation in the system supply pressure in which the controller variables are obtained through particle swarm optimization (PSO) algorithm. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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A variable-capacity-based fuzzy random facility location problem with VaR objective
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Book chapter -
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Bees algorithm for Forest transportation planning optimization in Malaysia
Published 2021“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…The dataset employed for this investigation comprises eight input parameters and one output variable, representing the battery RUL. In conducting an analysis, the performance of the PSO NN model is compared with hybrid NN with Cultural Algorithm (CA-NN) and Harmony Search Algorithm (HSA-NN), as well as the standalone Autoregressive Integrated Moving Average (ARIMA). …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Optimizing Renewable Energy Integration in Weak Grids withUPQC Controller
Published 2024“…Integrating renewable energy into weak grids poses significant challenges, including voltage instability, power quality deterioration, and limited capacity to handle variable generation. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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