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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…The propsed algorithm could be valuable aid for analyzing the fluid flow and reservoir simulation in an effective manner. …”
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Conference or Workshop Item -
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Car dealership web application
Published 2022“…Hence, two transfer learning algorithms were proposed and implemented to provide initial performance boost to the River adaptive random forest regressor and classifier, respectively. …”
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Final Year Project / Dissertation / Thesis -
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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Identifying and predicting Muslim’s community funeral funding protocols
Published 2024“…However, they are not conclusive enough as they lack predicting capability that Machine Learning can offer. Selected Machine Learning algorithms such as Decision Tree, Random Forest, and Naïve Bayes were used to classify the people that will go through funeral poverty based on a selected dataset and a survey conducted. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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A review on the treatments for monocular visual impairment for the development of a visual aid
Published 2023“…This paper presents an initial investigation into developing a visual aid for monocular visual impaired patients. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023“…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”
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Pruned committee neural network based on accuracy and diversity trade-off for permeability prediction
Published 2014“…In this paper, first we constructed a committee neural network with different learning algorithms and then proposed an expert pruning method based on diversity and accuracy tradeoff to improve the committee machine framework. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science
Published 2021“…The detailed review of literature undertaken in this study provides a strong basis for the conclusion that the integration of spatial techniques and machine learning has the potential to improve air pollution prediction outcome and aid appropriate intervention initiatives by the stakeholders. …”
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Deep learning framework for hierarchical-based object identification and description
Published 2024“…The HIDF aims to overcome global generalization, hierarchical and correlation learning limitations by describing an object when it cannot be initially identified. …”
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Thesis -
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…Herschel-Bulkley model is used to approximate the complex rheological behavior of a non-Newtonian fluid. The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features
Published 2018“…However, this technique has limited performance in determining the nature of the lesions. This study initiates a computer-aided diagnosis (CAD) system to aid radiologists in an objective and more reliable interpretation of ultrasound images of liver lesions. …”
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LSTM-based electroencephalogram classification on autism spectrum disorder
Published 2021“…A novel autism diagnosis method based on a bidirectional long-short-term-memory (LSTM) network's deep learning algorithm is proposed. This multi-layered architecture merges two LSTM blocks with the other direction of propagation to classify the output state on the brain signal data from an electroencephalogram (EEG) on individuals; normal and autism obtained from the Simon Foundation Autism Research Initiative (SFARI) database. …”
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White blood cell recognition for biomarker model using improved convolutional neural network (CNN)
Published 2022“…Manual WBC analysis is less efficient, therefore a Computer Aided Diagnosis (CAD) based on Deep Learning (DL) model become subject of interest nowadays. …”
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Thesis -
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao
Published 2024“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. Among these, the Gaussian-kernel Support Vector Machine stood out, achieving remarkable performance with 88.18% validation and 93.37% test accuracies. …”
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Thesis -
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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. Ensemble is a learning algorithm that combines some experts instead of considering a single best expert for the predictions.The thesis proposed anoptimizing method leading to small structure of assemble GA. …”
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Thesis -
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The methods have been evaluated for their performance on MDL’s MDDR, NCI’s AIDS and IDDB drug databases containing various biologically active classes of molecular structures. …”
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Monograph
