Search Results - (( variable activation function algorithm ) OR ( simulation optimization system algorithm ))
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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2
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system
Published 2023“…Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. …”
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Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system
Published 2024“…To build and improve the Fuzzy PID controller for the semi-active suspension system used in quarter cars, using a novel meta-heuristic technique known as Grey Wolf Optimizer (GWO). …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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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“…The computational burden of C-MPC is expensive due to utilize all available voltage vectors of a power inverter to predict the future behavior of the system. This dissertation has focused on Lyapunov model predictive control (L-MPC) methods, in which Lyapunov control law is employed in the cost function to minimize the error between the desired control variables and the actual control variables of a three-phase four-leg inverter to optimize closed-loop system performance. …”
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8
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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9
Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (AN...
Published 2021“…For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. …”
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Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. …”
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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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12
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy
Published 2019“…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024“…Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. …”
Conference Paper -
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Teletraffic performance of mobile cellular channel assignment using genetic algorithm
Published 2023Subjects:Conference paper -
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Optimization of handover algorithms in 3GPP long term evolution system
Published 2011“…Simulation results show that this optimization outperforms non-optimized algorithms by minimizing the average number of handovers per UE per second while maximizing average system throughput.…”
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A multiobjective simulated Kalman filter optimization algorithm
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DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING
Published 2007“…This paper presents the application of Genetic Algorithm (GA) and Simulated Annealing (SA) techniques for optimal design and analysis of a Brushless DC Motor (BLDC) widely used in many industrial motion control apparatus and systems. …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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