Search Results - (( using factorization learning algorithm ) OR ( based constructive based algorithm ))
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1
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…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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An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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Research Report -
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PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
Published 2023“…Gated Recurrent Unit (GRU) algorithm is used to cater the predicting action of equipment state based on data from an oil and gas industry.…”
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4
Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…The result shows that the detection of malware within application category achieves higher accuracy compared to application with non-category based. In increasing the reliability, the results obtained are then validated by using statistical analysis procedure which each machine learning classification algorithm are iterate 50 times. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…The 3D numerical analysis factors in construction stages, tunnel geometry, and operational parameters while incorporating in-situ and lab test results to establish engineering soil parameters. …”
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Prediction of river water quality based on Artificial Neural Network / Danial Mustaqim Azmi ... [et al.]
Published 2024“…The performance metric used in the study is the calculation of the accuracy for factors such as the number of neurons in the hidden layer, the epoch number, the split data ratio and the learning rate. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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9
Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…Finally, the concept of model compression is integrated, utilizing scaling factors in the batch normalization (BN) layer, and introducing sparse factors to perform sparse training on the network. …”
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Correlation model in the adoption of E-payment services: A machine learning approach
Published 2022“…Then, by using Correlation Based Feature selection algorithm, we select the best subset of features out of the highly correlated features to do predictive modelling. …”
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Final Year Project / Dissertation / Thesis -
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Extrapolation detection and novelty-based node insertion for sequential growing multi-experts network
Published 2003“…Artificial neural networks (ANNs) have been used to construct empirical nonlinear models of process data. …”
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User interface and interactivity design guidelines of algorithm visualization on mobile platform
Published 2019“…Moreover, the evaluation of the effectiveness of the AVOMP prototype from 35 participants through laboratory experiments based on the bloom taxonomy test shows that there is a significant difference between students learning sorting algorithms using the manual approach (Pre-Test) and the AVOMP app (Post-Test). …”
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An artificial neural network approach in service life prediction of building components in Malaysia based on local environment and building service load
Published 2007“…The back-propagation learning algorithm is used as learning model. The environment load factors, workmanship, design, usage and level of maintenance are used as input variables in training process of the neural network model. …”
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Conference or Workshop Item -
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Predicting Diseases Using Multi-BackPropagation
Published 2002“…Multi-network approach does not require any changes in neural network learning algorithm. Instead, the large data is divided into several smaller categories or network. …”
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15
Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…ML models were constructed using 302 patients and 54 input variables from the Malaysian National Cardiovascular Disease Database. …”
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16
A Stepper Motor Design Optimization Using
Published 2005“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Monograph -
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The effect of organisational internal factors and technology orientation on environmental sustainability performance of Malaysian construction firms
Published 2021“…This study seeks to fill this gap by applying the contingency resource-based view, institutional, and learning theories to investigate the effects of organisational internal factors and technology orientation on construction firms’ environmental sustainability performance. …”
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A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow
Published 2025“…This paper introduces a proof-of-concept vision-based deep learning approach for vibration measurement, proposing a factorized (2+1)D Convolutional Neural Network (CNN) model to predict four vibration metrics: acceleration, velocity, displacement, and frequency, with a focus on rigid body motion. …”
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