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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Final Year Project / Dissertation / Thesis -
3
Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar
Published 2012“…The learning process creates knowledge that guides a person to make the decisions. …”
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Research Reports -
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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6
Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Final Year Project / Dissertation / Thesis -
7
Deploying blockchains to simplify AI algorithm auditing
Published 2023“…A huge number of business companies have incorporated several machine learning algorithms for day-to-day decision making. …”
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Proceeding Paper -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. This study can be helpful in analysing the capabilities of machine learning methodologies for time-series data-sets as well as helping governments in the decision making process for mitigation of the pandemic. …”
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10
Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. This study can be helpful in analysing the capabilities of machine learning methodologies for time-series data-sets as well as helping governments in the decision making process for mitigation of the pandemic. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
text::Thesis -
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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Thesis -
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A New Probabilistic Output Constrained Optimization Extreme Learning Machine
Published 2023“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Thesis -
15
Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…Therefore, the automation of this process is required to recognize tumors. Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. Therefore, the proposed fuzzy model is a useful aid in the decision-making process, specifically in the healthcare sector.…”
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Machine learning for data classification in construction project planning
Published 2023“…The concept of the Machine Learning is the ability of the machine able to learn the situation with algorithms rules and make a predictions or decision. …”
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Final Year Project / Dissertation / Thesis -
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Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment
Published 2012“…Sync agent which is Multi-agent system is a promising technique which, we believe that, this approach has a potential of increasing the performance of the network and easy learning process by speed up the update process of the mobile learning contents.…”
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Conference or Workshop Item -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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