Search Results - (( developing function method algorithm ) OR ( _ simulation based algorithm ))
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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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Thesis -
2
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…Subsequently, the THF modelling scheme can be incorporated into an established real time NLFXLMS algorithm termed THF-NLFXLMS algorithm. The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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3
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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4
MOTION PLANNING ALGORITHM FOR VEHICLE PARKING SIMULATION
Published 2008“…This project focuses on creation of the motion planning algorithm of the system and developing a simulation to simulate the vehicle movements. …”
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Final Year Project -
5
Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation
Published 2007“…Several simulations obtain optimum results of implemented algorithm. …”
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6
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…Conventionally, the numerical simulations for such devices are obtained by using the commercial simulation packages based on the Finite Element Methods (FEM). …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…Nonlinear FXLMS (NLFXLMS) control algorithm based on SEF has been previously developed to cancel the noise in environment with external factors that can cause nonlinearity. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. …”
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11
Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Article -
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Thesis -
13
An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition
Published 2011“…The detection algorithm was developed analytically by applying the Signal Detection Theory (SDT) and the Random Matrix Theory (RMT). …”
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Thesis -
14
Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE
Published 2014“…However, when large changes occur in the irradiance, the performance of this algorithm is degraded. To eliminate all of the disadvantages of the classic IC algorithm, we developed a new IC controller based on a fuzzy duty cycle change estimator with direct control. …”
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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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16
A hybrid MEP and AIS Algorithm for energy dispatch in power system
Published 2017“…This necessitates for researches in developing new tools to overcome ED problems. Therefore, this paper introduces the new algorithm as an alternative method to provide the best solution in solving the single objective function of ED problems. …”
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Article -
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Thesis -
18
Simulation-Based Power Estimation for High Throughput SHA-256 Design on Unfolding Transformation
Published 2022“…Several cryptographic SHA-256 hash algorithms have been developed to enhance the performance of data-protection techniques. …”
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Proceeding -
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…Subsequently, it is exploring into the development of random approaches based on MABSA, integrating components into others algorithm whereby Squirrel Search Algorithm (SSA), Cauchy Mutation (CM) approach, and Doppler Effect (DE) phenomenon. …”
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20
Neural network algorithm-based fall detection modelling
Published 2020“…This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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