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1
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. 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 -
2
Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…This thesis presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. …”
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3
An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
Published 2015“…The performance of the proposed system is evaluated using MATLAB simulation and experimentation, in which a digital signal controller is used to implement the proposed algorithm on a real boost converter connected to a PV simulator. …”
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4
Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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5
Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. 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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6
Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel
Published 2020“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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7
Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction
Published 2022“…Particle Swarm Optimization is a meta-heuristics algorithm widely used for optimization problems. …”
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8
Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Both methods have been successfully implemented; however they either are computationally expensive for complex, multi-valued problems, or slow to converge due to rounding of the continuous variable. …”
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Research Reports -
9
A swarm intelligent approach for multi-objective optimization of compact heat exchangers
Published 2023Article -
10
Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
Published 2017“…A nonlinear EHA system model is established and the proposed controller which is sliding mode controller (SMC) is implemented in the simulation studies. 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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11
A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. …”
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12
Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
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13
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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14
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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15
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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16
Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…The aim of this research is to explore a technique that can be implemented to the Variable Speed Micro-hydro Power Generation (VS-MHPG) system to search the optimum operating point for the maximum power extraction. …”
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Proceedings -
17
Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel
Published 2019“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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18
Optimization of biochemical systems production using combination of newton method and particle swarm optimization
Published 2019“…The justification of choosing PSO algorithm is its direct implementation and effectiveness in the optimization process. …”
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19
Dynamic Economic Dispatch For Power System
Published 2016“…This research finds large variable size DED problems can be easily implemented, PSO method is reliable and is suitable for real-time analysis. …”
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Thesis -
20
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…To achieve this goal, the successful implementation of an expeditious and reliable optimization algorithm is crucial. …”
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