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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”
Conference paper -
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The combined influence of the genetic algorithm and correlation analysis are used in this technique. …”
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Article -
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…However, the difficulty of correctly forecasting or predicting the weather continues to exist. Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. …”
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Proceedings -
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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“…In enhancing prediction accuracy, the T-method employed Taguchi�s orthogonal array as a variable selection approach to determine a subset of independent variables that are significant toward the dependent variable or output. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Final Year Project -
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Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Published 2025“…Therefore, it is recommended to utilize the prediction algorithms within the range of input variables employed in this investigation for optimal results. ? …”
Article -
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Prediction of monthly rainfall at Senai, Johor using artificial immune system and deep learning neural network
Published 2020“…MLP is a deep learning algorithm used in the Artificial Neural Network (ANN). …”
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Neural network based model predictive control for a steel pickling process
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. …”
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…It is concluded that these algorithms are suitable for predicting sensitive output energy data of a CCPP depending on thermal input variables.…”
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Depression prediction using machine learning: a review
Published 2022“…The aim of this study is to identify important variables used in depression prediction, recent depression screening tools adopted, and the latest machine learning algorithms used. …”
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An Educational Tool Aimed at Learning Metaheuristics
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. …”
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Conference or Workshop Item -
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
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. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
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. …”
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Thesis -
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Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour
Published 2014“…Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. …”
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Article -
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
Conference paper -
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Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz
Published 2022“…ML algorithms were used to examine significant variables utilising feature selection methods. …”
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Thesis -
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…The model had an impressive performance during the training phase, with a R2 of 0.98, RMSE of 2.412 MPa, and MAE of 1.6249 MPa when using 8 input variables to predict the compressive strength of concrete. …”
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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis
Published 2017“…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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