Search Results - (( using function method 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“…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
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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3
Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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4
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The third set affirmed that the enhancement on the proposed algorithm, which made use of indexing method that suits the medoids, could boost the performance to about 9 to 27 times in terms of execution time depending on the complexity of the dataset. …”
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5
Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…To verify the prediction performance of the proposed methods, the proposed methods are compared with three existing regression methods used in previous studies. …”
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6
Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…A new scaled modified BFGS (smBFGS) is compared with the mBFGS in terms of iteration numbers and CPU time. These methods were tested with several selected functions by using code Maple 18 software. …”
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7
Application of correlation as a measure of performance
Published 2011“…In this study the correlation measure Rp 2 derived from the Un replicated Linear Functional relationship (ULFR) model will be shown to be a useful measure of performance in selected procedure or algorithm for a particular image registration method, a medical treatment, a character recognition method, and a compression method. …”
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8
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…The results show that the ASED- and SED-based methods produced stable convergence. The ASED-based method provided better tracking performance than the SED method by obtaining the objective function’s lower values. …”
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9
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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10
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Modeling of hydrological process has been increasingly complicated since we need to take into consideration an increasing number of descriptive variables. In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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11
OPTIMIZATION OF A CRUDE DISTILLATION UNIT USING PARAMETRIC DESIGN OF TAGUCHI AND RESPONSE SURFACE METHODS
Published 2014“…Variables with more than 90% contribution factors are selected and validated with the response surface method. …”
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12
Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure
Published 2016“…A parsimonious model structure is desirable in enabling easy control design. Two methods of model structure selection are closely looked into and these are deterministic mutation algorithm (DMA) and forward selection procedure (FSP). …”
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13
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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14
Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…This technique is selected for the treatment such a non-linear function relationship among the variables. …”
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15
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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16
Evaluation of lightning return stroke current using measured electromagnetic fields
Published 2012“…However, the improvement of Deindorfer and Uman on the Heidler function with an unknown variable is selected as the general channel base current function. …”
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17
Optimal power flow solutions for power system operations using moth-flame optimization algorithm
Published 2021“…The comparison proves that MFO offers a better result compared to the other selected methods. In IEEE 30-bus test system, MFO outperform the other optimization methods with 967.589961$/h compared to 971.411400 $/h, 983.738069$/h, 975.346233$/h, 985.198050$/h, 1035.537820$/h for Improved Grey Wolf Optimizer (IGWO), Grey Wolf Optimizer (GWO), Ant Loin Optimizer (ALO), Whale Optimization Algorithm (WOA), and Sine Cosine Algorithm (SCA) respectively. …”
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18
An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration
Published 2018“…This paper discusses bit selection by employing a method of combining Artificial Neural Network (ANN) and the computation of Genetic Algorithm (GA). …”
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19
Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
Published 2021“…To overcome these problems, the LAD-SCAD based on sure independence screening (SIS) technique is put forward. The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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20
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Artificial intelligence (AI) methods are normally selected to deal with this problem. …”
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