Search Results - (( data simulation model algorithm ) OR ( using optimization method algorithm ))
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A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system
Published 2021“…The simulation results demonstrate that the algorithm can minimize the limitations of the existing methods and it can use the PV generation system effectively. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Teletraffic performance of mobile cellular channel assignment using genetic algorithm
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm
Published 2018“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. …”
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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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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Resource scheduling algorithm with load balancing for cloud service provisioning
Published 2019“…Simulations were conducted to evaluate the effectiveness using Cloudsim simulator in cloud data centers and results shows that the proposed method achieves better performance in terms of average success rate, resource scheduling efficiency and response time. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The proposed method uses a rank accuracy estimation model to decide the rank-1 value to be applied for the decomposition. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…The Travelling Salesman Problem (TSP) is a well-known algorithmic problem its main objective is optimization. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The proposed algorithm is then used to model tyrosine production in Musmusculus (mouse) by using a dataset, the JAK/STAT(Janus Kinase Signal Transducer and Activator of Transcription) signal transduction pathway. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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