Search Results - (( parameter optimization means algorithm ) OR ( variable selection based algorithm ))

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  1. 1

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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    Article
  2. 2

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
  3. 3

    Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network by Darajeh, Negisa, Masoumi, Hamid Reza Fard, Kalantari, Katayoon, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Khandanlou, Roshanak

    Published 2016
    “…To optimize the network, independent variables including ion concentration, adsorbent dose, and removal time were used as input parameters, while the removal percentage of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite were selected as outputs. …”
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    Article
  4. 4
  5. 5

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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    Thesis
  6. 6

    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

    Published 2018
    “…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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    Book Chapter
  7. 7

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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    Thesis
  8. 8

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…In this paper, a novel parametric algorithm is proposed that is able to handle different planning goals by means of a set of objective-controller parameters. …”
    Article
  9. 9

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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    Thesis
  10. 10
  11. 11

    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

    Published 2011
    “…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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    Thesis
  12. 12

    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…Thus, a safe experimentation dynamics (SED) algorithm is selected to solve this unstable convergence but still not enough to achieve high accuracy because the update designed parameter only depends on the fixed step size gain. …”
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    Thesis
  13. 13

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    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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    Thesis
  14. 14

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. …”
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    Thesis
  15. 15

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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    Thesis
  16. 16

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…Through rank selection technique, the chromosomes are sorted based on the fitness function to learn about the population of current generation. …”
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    Thesis
  17. 17

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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    Article
  18. 18

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
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    Conference or Workshop Item
  19. 19

    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

    Published 2013
    “…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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    Conference or Workshop Item
  20. 20

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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    Article