Search Results - (( using optimization using algorithm ) OR ( variables selection method algorithm ))
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1
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025Subjects:Conference paper -
2
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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3
Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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4
Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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5
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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6
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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7
Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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8
Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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9
The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…In enhancing prediction accuracy, the T-method employed Taguchi�s orthogonal array as a variable selection approach to determine a subset of independent variables that are significant toward the dependent variable or output. …”
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10
Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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11
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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12
Development of committee machine models for multiple response optimization problems
Published 2014“…Responses of Taguchi are restricted to be selected from defined levels of input variables and newer hybrid methods use only one ANN in modeling. …”
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13
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. …”
Conference paper -
14
Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…Broyden-Fletcher-Goldfarb-Shanno (BFGS) is one of a well-known Quasi-Newton update formula. This method is generally considered as the most efficient method among other variable metric methods for solving unconstrained optimization problems. …”
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15
Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan
Published 2024“…These methods are tested using 20 test functions with different variables also with four initial points have been for each variable. …”
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16
Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…We refer to the new DE algorithm as random variable length crossover DE (rvlx- DE) algorithm. …”
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17
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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18
An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator
Published 2019“…A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. …”
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19
Systematic design of chemical reactors with multiple stages via multi-objective optimization approach
Published 2015“…Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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20
Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Additionally, our method employs an improved initialization phase using equal sampling for each decision variable to ensure a comprehensive exploration of the entire solution space. …”
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