Search Results - (( using integration based algorithm ) OR ( using optimization based algorithm ))

Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

“…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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Score Fusion Using Hybrid Bacterial Foraging Optimization And Particle Swarm Optimization (Bfo-Pso) For Hand-Based Multimodal Biometrics by Shanmugasundaram, Karthikeyan

“…Therefore, this research is focused on the hand-based multimodal biometric score fusion which incorporates the scores of hand-based multimodalities and the optimal weights using Hybrid Bacterial Foraging - Particle Swarm Optimization (HBF-PSO) algorithm.…”
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Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

“…It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

“…In this paper, an improved butterfly optimization algorithm (IBOA) is proposed and subsequently integrated into the training process of the WNNs. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…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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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

“…The comparison of the result of the developed integrated algorithm using two benchmark FMS scheduling algorithms datasets is conducted. …”
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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

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An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Mohammed, M.A

“…Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. …”
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine by Kasilingam G., Pasupuleti J.

Implementation and analysis of BBO algorithm for better damping of rotor oscillations of a synchronous machine by Kasilingam G., Pasupuleti J., Nithiyananthan K.

Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy by Ehteram M., Banadkooki F.B., Fai C.M., Moslemzadeh M., Sapitang M., Ahmed A.N., Irwan D., El-Shafie A.

A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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DC MOTOR CONTROL USING GENETIC ALGORITHM BASED PID by SHAHRONI, NURUL ASHIKIN

“…This dissertation presents the research that had been done on the chosen topic, works done and results acquired throughout the Final Year Project for two semesters, about the DC Motor Control using Genetic Algorithm based PID. The objectives of this project are to optimize speed control of the DC motor by using Genetic Algorithm based PID, to improve the performances of the DC motor controller in term of rise time, settling time, maximum overshoot and Integral of Time Absolute Error (ITAE) and to decide the best parameters to be used for Genetic Algorithm that can optimize the performance of a DC Motor ( eg: population size, mutation rate and crossover value). …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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