Search Results - (( developing function learning algorithm ) OR ( learning application optimisation algorithm ))
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Particle Swarm Optimisation with Improved Learning Strategy
Published 2015“…Comparison is made on the PSO-ILS with 6 well-established PSO variants on 10 benchmark functions to investigate the optimisation capability of the proposed algorithm. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
Published 2021“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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Final Year Project / Dissertation / Thesis -
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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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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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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…For this intelligent TMM, a variant of Frequency Pattern Growth (FP-Growth), called enhanced FP-Growth (EFP-Growth) algorithm is developed by altering the internal data structures for faster execution and by developing a modified exponential decay function (MEDF) to automatically calculate minimum supports for adapting trust evolution characteristics. …”
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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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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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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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Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
Published 2017“…The model output optimisation by genetic algorithm (GA) produces higher biogas production compared to the optimisation using statistical methods. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey
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