Search Results - (( processes optimisation based algorithm ) OR ( based classification using algorithm ))
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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Thesis -
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For horizontal localisation, different algorithm based on multi-class k-nearest neighbour classifiers with optimisation parameter is presented. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…Overall, the MCML classification algorithm is proven to be used as a benchmark for early detection of text-based mental health disorders.…”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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An Automated System For Classifying Conference Papers
Published 2021“…This project is aimed to develop an automated web-based conference paper system for the manual process of assigning papers to reviewers by using classification models. …”
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Final Year Project / Dissertation / Thesis -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Conventional material selections are mostly based on the experience of product design engineers and the materials in common use. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…The performance of each neural network was analysed in terms of the classification accuracy, average score, total training time required during the training process and the test time of the optimised networks. …”
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Research Reports -
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Processing and classification of landsat and sentinel images for oil palm plantation detection
Published 2022“…In distinguishing oil palm trees, optimisation of the pre-processing of the images enables the extraction of useful information based on its spectral signature, before they are utilised as an input for the soft computing method. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…Based on these results, this paper aims to provide insights into the strengths and limitations of each optimizer, highlighting the importance of considering task-specific requirements when selecting an optimization algorithm for deep learning models.…”
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Proceeding Paper -
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Feature clustering for pso-based feature construction on high-dimensional data
Published 2019“…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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Designing a new model to detect Trojan Horse based on knowledge discovery and data mining
Published 2024thesis::master thesis -
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Automated classification radiograph of Periodontal bone loss using deep learning
Published 2025“…Several combinations of epochs, learning rates, and optimisation algorithms were tested to enhance performance. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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Book Section -
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Published 2020“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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