Search Results - (( processes simulation based algorithm ) OR ( parameter optimization _ algorithm ))
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1
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
2
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 -
3
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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Thesis -
4
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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Final Year Project -
5
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Article -
6
Parameter-Less Simulated Kalman Filter
Published 2017“…Simulated Kalman Filter (SKF) algorithm is a new population-based metaheuristic optimization algorithm. …”
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7
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Article -
8
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Thesis -
9
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Thesis -
10
Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System
Published 2014“…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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Article -
11
Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System
Published 2014“…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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12
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…These findings indicate that the PSO algorithm excels in delivering superior results while showcasing rapid convergence, robustness, and consistent repeatability in optimizing laser beam machining parameters.…”
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13
An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach
Published 2017“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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14
Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Agents interact among them to modify and enhance the solution throughout the search process. Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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15
Warpage analysis on thick shell part using response surface methodology (RSM) and bat algorithm (BA) to optimize parameter setting in injection molding process
Published 2018“…RSM is use to optimize process parameters setting and reduce warpage problem during IMP by Design of Experiment (DOE) based on the recommended parameter setting in AMI. …”
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Conference or Workshop Item -
16
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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Article -
17
Automatic control of flotation process using computer vision
Published 2015“…The performance of improved marker based watershed algorithm was validated by using several industrial and laboratory froth images. …”
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Thesis -
18
Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq
Published 2016“…The first algorithm was based on the traditional simulation of reservoir operation, whilst the second algorithm (Salg) enhanced the GAOM by changing the population values of GA through a new simulation process of reservoir operation. …”
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19
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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Monograph -
20
Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling
Published 2011“…This model minimizes the makespan of all the loading and unloading tasks for a set of cranes in a scheduling problem. Based on the simulated annealing (SA) algorithm, a scheduling method is proposed to solve the problem in a relatively short period of time. …”
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