Search Results - (( simulation optimization model algorithm ) OR ( using vectorization _ algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
Published 2023“…Balancing; Forecasting; Stream flow; Support vector machines; Exploitation and explorations; Machine learning models; Optimisations; Optimization algorithms; Prediction modelling; Simulated annealing integrated with mayfly optimization; Streamflow prediction; Support vector regression models; Support vector regressions; Support vectors machine; Simulated annealing; algorithm; mayfly; optimization; prediction; streamflow; support vector machine; Jhelum River…”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
Published 2012“…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
Published 2016“…The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi
Published 2013“…Simulation is done by using the observer which uses optimal feedback gain as an example of process from algorithm design to verification of logic. …”
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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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Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…The third step employs the support vector machine algorithm to calculate prediction values. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand
Published 2019“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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A new particle swarm optimization for wireless mesh routing protocol
Published 2008“…We test the propose algorithm in network simulator 2 (ns2). Based on the results, we proven that PSO-SIIW algorithm can be applied to MPR calculation in OLSR.…”
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Monograph -
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Cauchy density-based algorithm for VANETs clustering in 3D road environments
Published 2022“…The model has been simulated by considering several simulation parameters including traffic, mobility, driving behavior, and road curvature. …”
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A STUDY OF TORQUE VECTORING AND TRACTION CONTROL FOR AN ALL-WHEEL DRIVE ELECTRIC VEHICLE
Published 2013“…In addition, an optimal control algorithm will be developed for best performance to minimize energy losses using MATLAB/Simulink software. …”
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A New Optimization Technique Of Support Vector Machine For Electricity Market Price Forecasting
Published 2019“…Therefore, a hybrid of Least Square Support Vector Machine (LSSVM) and Bacterial Foraging Optimization Algorithms (BFOA) is proposed in this research to provide an accurate price forecast with optimized LSSVM parameters (gamma and sigma) and features. …”
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Technical Report -
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A novel multi-state particle swarm optimization for discrete combinatorial optimization problems
Published 2012“…Particle swarm optimization (PSO) has been widely used to solve real-valued optimization problems. …”
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A study of torque vectoring and traction control for an all-wheel drive electric vehicle
Published 2014“…In addition, an optimal control algorithm will be developed for best performance to minimize energy losses using MATLAB/Simulink software. …”
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Minimization of torque ripple and flux droop using optimal DTC switching and sector rotation strategy
Published 2022“…A five-level cascaded H-bridge (CHB) inverter was used in the optimal DTC switching strategy because it had many voltage vectors and could be used for a variety of speed operations. …”
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