Search Results - (( using factor error algorithm ) OR ( simulation optimization based algorithm ))
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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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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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Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin
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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4
Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The modal frequencies of the tower are evaluated under various conditions of damage in concrete and connection in different parts of the tower by using finite element simulation. The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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An adaptive localization system using particle swarm optimization in a circular distribution form
Published 2016“…The simulation results show the proposed method using HPSO-TVAC variant achieves very low distance error of 0.19 meter.…”
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Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines
Published 2025“…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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Tuning of PID controller for a synchronous machine connected to a non-linear load
Published 2023“…The simulations show that the proposed method damps optimally and suppresses errors to a minimum. © 2006-2014 Asian Research Publishing Network (ARPN).…”
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System
Published 2020“…An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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Path Planning Optimization For Solar-Powered Perpetual Flight Across The World
Published 2018“…A validated algorithm with overall error percentage less than 10 % is developed to simulate the solar-powered flight.Next, the detailed path planning is planned which allow an UAV to perform mapping mission at constant altitude, 600 m above the Earth’s surface with minimized geometric error without fail. …”
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Monograph -
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Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network
Published 2010“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. …”
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Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system
Published 2024“…Ensuring stable and responsive control, design of optimized PD-type and PID-type fuzzy logic controllers using Particle Swarm Optimization (PSO) were established and were tested under a simulation environment. …”
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Computational modeling of running biomechanics in amateur runners
Published 2024“…Experimental data were collected from ten amateur runners, and muscle-driven simulations were performed using techniques like Computed Muscle Control (CMC) and Static Optimization (SO). …”
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Final Year Project / Dissertation / Thesis -
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Conference or Workshop Item -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…At last, the influencing factor of CMV is revealed based on switching state combination and then the CMV weighting factor is introduced in the cost function to make balance in the ripple content of load currents and the mitigation of CMV. …”
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