Search Results - (( (variable OR variables) prediction using algorithm ) OR ( java application based algorithm ))
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1
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 -
2
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 -
3
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. …”
Article -
4
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 -
5
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 -
6
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 -
7
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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Article -
8
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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9
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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10
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 -
11
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…GA and correlation analysis are used for the selection of the most influential input variables for the training and testing of the hybrid model. …”
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12
Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…First, the flower pollination algorithm is applied to search for informative spectral variables, followed by variable elimination. …”
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13
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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14
Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…These components have been used in several studies as new predictor variables to predict the behaviour of the response variable. …”
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Thesis -
15
Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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16
Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models
Published 2019“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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Thesis -
17
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. …”
Article -
18
Automatic control of flotation process using computer vision
Published 2015“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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Thesis -
19
Soil Pore Water Pressure and River Suspended Sediment Modelling using Artificial Neural Networks
Published 2012“…This study reports the attempts and associated findings in predicting some hydrologic variables using the A1--.'…”
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20
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
