Search Results - (( software identification method algorithm ) OR ( simulation optimization method algorithm ))*
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1
Three phase fault algorithm in distribution system by using database approach and impedance based method
Published 2012“…A three phase fault location algorithm using database and impedance based method is utilized in distribution system to locate fault which may occur in any possible fault sections and to optimize the switching operations to reduce the outage time affected by fault. …”
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2
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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3
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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4
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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5
Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…Thus, an integrated simulation module consisting of an inverse optimization method and a finite element method was developed for modeling the powder compaction process as a whole. …”
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Article -
6
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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7
Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data
Published 2009“…Consequently, improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural network associated with three different training algorithms. …”
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8
Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model
Published 2018“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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9
Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
10
Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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11
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE is also used to develop a new dynamic parameter identification framework to estimate the barycentric parameters of the CRS A456 robot manipulator. The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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12
Simulation and characterization of indium gallium arsenide thermophotovoltaic cell for harvesting waste heat with different spectral irradiances
Published 2023“…TCAD Silvaco software was used to simulate the output performance of the TPV cell. …”
text::Thesis -
13
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
14
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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15
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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16
Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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17
Improved particle swarm optimization by fast annealing algorithm
Published 2019“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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Proceeding Paper -
18
Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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19
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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20
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
