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1
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Article -
2
On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
Published 2015“…Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Conference or Workshop Item -
3
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…However, the internal power parameters (weight and basis) of ELM are initialized at random, causing the algorithm to be unstable. The Particle swarm optimization (PSO) is a well-known meta-heuristic which is used in this research to optimize the ELM. …”
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Conference or Workshop Item -
4
Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Thesis -
5
Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…In this paper, a sound approach for a Twin Rotor Multi-input Multi-Output System (TRMS) parametric modeling is proposed based on dynamic spread factor particle swarm optimization. …”
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Proceeding Paper -
6
A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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7
A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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8
Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration
Published 2025“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”
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9
Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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10
Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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11
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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12
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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13
Neural Network – A Black Box Model
Published 2024“…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
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Book Chapter -
14
Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Thesis -
15
Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty
Published 2011“…The PSO algorithm is used to minimize the infinity norm of the transfer functions matrix of the nominal closed loop system to obtain the optimal parameters of the weighting function. …”
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Thesis -
17
Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Article -
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Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers
