Search Results - (( model evaluation based algorithm ) OR ( simulation optimization method 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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2
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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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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5
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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6
Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
Published 2016“…This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. …”
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7
The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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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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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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Enhancing NoC-based MPSoC performance: a predictive approach with ANN and guaranteed convergence arithmetic optimization algorithm
Published 2023“…The main idea of the proposed method is to develop a prediction model, speci‚cally an Arti‚cial Neural Network (ANN) optimized using the Guaranteed Convergence Arithmetic Optimization Algorithm (GCAOA-ANN), for predicting the utilized routing algorithm in NoC-based MPSoC platform during the DSE process. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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15
DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…Experimental evaluation confirmed that the proposed grid scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.…”
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16
Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm
Published 2023“…The solar sites will be evaluated based on their annual average solar irradiation and the optimal tilt angle and orientation angle for solar panel at the solar sites can be estimated using the computational model. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…Furthermore, Optimized Parametric Topology Control Routing algorithm performs significantly better than Triangular Routing Method and Change Foreign Agent Algorithm. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…This can overcome the existing memory-based algorithms such as random search (RS) and simulated annealing (SA) which currently produce less control accuracy due to the local minimum problem. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…This can overcome the existing memory-based algorithms such as random search (RS) and simulated annealing (SA) which currently produce less control accuracy due to the local minimum problem. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. …”
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