Search Results - (( simulation optimization using algorithm ) OR ( variables selection method algorithm ))
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1
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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2
Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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3
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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4
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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5
Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure
Published 2016“…In the real data simulation, both methods obtained the same model structure whereas in simulated data modelling, only DMA was able to select the correct model structure. …”
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6
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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8
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”
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9
Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…Meanwhile, based on the fuzzy simulation technique, the model adapted to a series of different distributed fuzzy variable, an improved particle swarm optimization algorithm (IPSO) is used for numerical simulations. …”
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10
Workload utilization dissemination on grid resources for simulation environment
Published 2013“…Among these factors are the manipulation of computer RI's, type of workload information with method of use, the workload dissemination direction along with implementation method and using certain algorithm to come out with new integrated scheduling with load balancing capability. …”
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11
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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12
Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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13
Rainfall prediction using multiple inclusive models and large climate indices
Published 2023Article -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Also, additional experiments to compare the relative performance of the IFS with five related feature selection algorithms were carried out using natural domain datasets. …”
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15
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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16
Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
17
Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
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18
A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Based on the two ratios, a multi-objective model is built to evaluate their joint impact on portfolio selection. Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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19
A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Based on the two ratios, a multi-objective model is built to evaluate their joint impact on portfolio selection. Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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20
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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