Search Results - ((regression algorithm) OR (((regression algorithms) OR (control algorithm))))

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  1. 1

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

    Published 2023
    “…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”
    Article
  2. 2

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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    Thesis
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    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm.…”
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    Book Section
  6. 6

    Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression by Wong S.Y., Siah Yap K., Tan C.H.

    Published 2023
    “…Fuzzy rules; Fuzzy systems; Genetic algorithms; Inference engines; Membership functions; Process control; Regression analysis; Functional relationship; Fuzzy inference systems; Human understanding; Hybrid genetic algorithms; Interpretability; Logical interpretation; Optimization tools; Regression; Fuzzy inference…”
    Conference Paper
  7. 7

    Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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    Article
  8. 8

    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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    Article
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    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

    Published 2024
    “…However, compared with the traditional risk control algorithm (logistic regression algorithm), CatBoost algorithm also needs to have the advantages of high efficiency, low algorithm complexity and strong interpretable ability. …”
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    Thesis
  11. 11

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar, A., Kanthasamy, R., Sait, H.H., Zwawi, M., Algarni, M., Ayodele, B.V., Cheng, C.K., Wei, L.J.

    Published 2022
    “…A total of 12 machine learning algorithms which comprises the regression models, SVM, GPR, and ANN were configured, trained using 124 datasets. …”
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    Article
  12. 12

    A Random Forest Regression Based Space Vector PWM Inverter Controller for the Induction Motor Drive by Hannan M.A., Ali J.A., Mohamed A., Uddin M.N.

    Published 2023
    “…Adaptive control systems; Controllers; Decision trees; Deep neural networks; Electric drives; Electric inverters; Electric motors; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Induction motors; Inference engines; Learning algorithms; Modulation; Neural networks; Regression analysis; Tracking (position); Two term control systems; Vector spaces; Vectors; Voltage control; Adaptive neuro-fuzzy inference system; Backtracking search algorithms; Different operating conditions; Proportional integral controllers; Random forests; Space Vector Modulation; Space vector pulse width modulation; Three phase induction motor; Pulse width modulation…”
    Article
  13. 13

    Diagnosis of Poor Control Loop Performance: Investigate Support Vector Regression Method on Stiction Quantification for Control Valve Nonlinearity by A/L Karuppiah, Yuveneshraj

    Published 2016
    “…The control valve in process control undergoes wear and aging which causes valve stiction. …”
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    Final Year Project
  14. 14

    Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm by aiman Azrael, Shaiful Nahar Sukri, Siti Sarah Zahidah, Nazri, Muhamad Sukri, Hadi, Annisa, Jamali, Hanim, Mohd Yatim, Intan Zaurah, Mat Darus

    Published 2021
    “…System identification was implemented via swarm intelligence algorithm known as cuckoo search algorithms based on auto regressive with exogenous model structure. …”
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    Proceeding
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    Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system by Nouri, Hossein, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Samin, Razali

    Published 2013
    “…Passino invented the bacteria foraging optimization algorithm, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. …”
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    Article
  16. 16

    Active vibration control of a flexible beam structure using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan

    Published 2017
    “…The objective of this work was to evaluate the performance of chaos-enhanced Stochastic Fractal Search (CFS) optimization algorithm in modeling and vibration control of flexible beam system. …”
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    Article
  17. 17

    Modelling of Flexible Manipulator System Using Flower Pollination Algorithm by Fadhli Muiz, Talib, Muhamad Sukri, Hadi, Hanim, Mohd Yatim, Annisa, Jamali, Mat Hussin, Ab Talib, Intan Zaurah, Mat Darus

    Published 2020
    “…If the advantages of FMS are not to be sacrificed, an accurate model and efficient control system must be developed. Thus, this study presents an approach of evolutionary swarm algorithm via flower pollination algorithm (FPA) to model the dynamic system of flexible manipulator structure. …”
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    Proceeding
  18. 18

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    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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    Article
  19. 19

    Machine learning algorithms for early predicting dropout student online learning by Dewi, Meta Amalya, Kurniadi, Felix Indra, Murad, Dina Fitria, Rabiha, Sucianna Ghadati, Awanis, Romli

    Published 2023
    “…Of the 4 algorithms used, the highest recall value is in Naive Bayes (1), the highest precision is in Logistic Regression with Lasso (1), while the highest accuracy value (0.99) and F1score (0.97) are obtained from the Support Vector Machine which has value equal to Logistic Regression with Lasso. …”
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    Conference or Workshop Item
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    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

    Published 2023
    “…The algorithms are Decision Tree (c4.5), Linear Regression (LR), and Decision Forest (DF) with a 10-fold cross-validation method for training and testing. …”
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    Article