Search Results - (( learning application optimisation algorithm ) OR ( based optimization based algorithm ))
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.]
Published 2022“…Hence, this study conducted numerical analysis, specifically backpropagation gradients and gradient-based optimization for snatch-theft detection. Here, snatch theft images and augmented images were used to perform the experimental study to determine the optimum hyperparameter values. …”
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EEG-based emotion recognition using machine learning algorithms
Published 2024“…Human emotions are very complex and hard to identify based on their facial expressions and appearance. …”
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Final Year Project / Dissertation / Thesis -
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…With various optimization algorithms available, choosing the one that best suits the deep learning model and dataset can make a substantial difference in achieving optimal results. …”
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Proceeding Paper -
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance
Published 2024“…To address these challenges, this research aims to optimise the application of deep learning models for NER and achieve enhanced results. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…The study suggests that the application of rule-based optimisation to predict stock market turning points generate more accurate and time saving decision.…”
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Book Section -
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Final Year Project / Dissertation / Thesis -
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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“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Thesis -
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). The analysis was performed based on inter- and intra-model mobile device identification among 120 mobile devices in 12 models for speech and non-speech segments under different environmental influences, communication networks, and stationaries. …”
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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“…In this project, the networks were trained using certain types training algorithm depending on the types of networks; Levenberg Marquardt (LM) for the MLP, competitive network for the LVQ and hybrid learning for ANFIS. …”
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Research Reports -
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…The GD method not performed well in large scale applications and when higher learning performances are required. …”
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Thesis -
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency
Published 2024“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…This study extends our knowledge of machine learning model optimisation, which has the potential to enhance the effectiveness of these models across a range of applications.…”
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Conference or Workshop Item -
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To show the methods applicability, this paper uses the proposed algorithm in three sustainable and resilient case studies. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
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Final Year Project / Dissertation / Thesis -
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Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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Thesis
