Search Results - (( based optimization method algorithm ) OR ( variable selection based algorithm ))*
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
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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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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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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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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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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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Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm
Published 2015“…The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. …”
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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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10
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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OPTIMIZATION OF A CRUDE DISTILLATION UNIT USING PARAMETRIC DESIGN OF TAGUCHI AND RESPONSE SURFACE METHODS
Published 2014“…A sequential quadratic programming (SQP) algorithm is then employed to optimize a profit function based onthereduced number of decision variables.…”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…An important contribution of the proposed method is modeling of interaction in addition to relevancy and redundancy based on information-theoretic criteria for the feature selection. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The results show that hybrid forecast model provide better performance when it is trained and tested with optimally selected input variable vector (IV), containing historical load and meteorological variables. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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15
Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…It shows that optimization based on GA is capable of reducing production time in the machining process.…”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…One of these MOO algorithms Multi-Objective Particle Swarm Optimization (MOPSO) extends it to handle problems with multiple objectives simultaneously, but like many swarm-based algorithms, MOPSO can suffer from premature convergence or local optima solutions. …”
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A review of crossover methods and problem representation of genetic algorithm in recent engineering applications
Published 2020“…Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Charles Darwin's proposed principles of natural genetics and natural selection theories. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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Thesis -
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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Systematic design of chemical reactors with multiple stages via multi-objective optimization approach
Published 2015“…By using reference-point based multi-objective evolutionary algorithm (R-NSGA-II), Pareto-optimal solutions are successfully generated within the region of user-specified reference points, thus facilitating in the selection of final optimal designs. …”
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