Search Results - (( java application learning algorithm ) OR ( variable training model algorithm ))

Refine Results
  1. 1
  2. 2

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

    Published 2017
    “…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
    Get full text
    Get full text
    Article
  3. 3

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
    Get full text
    Get full text
    Article
  4. 4

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…In preprocessing of optimization, modeFrontier Response Surface Method (RSM) is able to model the behavior of engine performances corresponding to the change of design variables.…”
    Get full text
    Get full text
    Proceeding Paper
  5. 5
  6. 6

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
    Get full text
    Get full text
    Monograph
  7. 7

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
    Get full text
    Get full text
    Article
  8. 8

    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

    Published 2023
    “…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  9. 9
  10. 10

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
    Get full text
    Get full text
    Thesis
  12. 12

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13

    Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

    Published 2019
    “…Model built resulted in variables importance’s ranking and subsequently, prediction can be made. …”
    Get full text
    Get full text
    Final Year Project
  14. 14

    Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

    Published 2024
    “…Also, the model performance was characterized based on the number of input variables utilized. …”
    Article
  15. 15
  16. 16

    Academic Achievement Prediction Model Using Neural Networks by Normaziah, Abdul Rahman

    Published 2002
    “…This model allows the system administrator to train and normalize data as well as trains. …”
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17
  18. 18

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia by Hayder G., Solihin M.I., Mustafa H.M.

    Published 2023
    “…This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). …”
    Article
  20. 20

    Enhancing the entrepreneurial intention of the retiring military personnel through entrepreneurial training by Yusuf, Lamidi

    Published 2017
    “…Partial Least Squares-Structural Equation Model (PLS-SEM) algorithm and bootstrap techniques were used to test the study hypotheses. …”
    Get full text
    Get full text
    Get full text
    Thesis