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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Thesis -
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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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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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus
Published 2009“…Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
Published 2021“…Among the hybrid models, in terms of accuracy, the best optimisation algorithm at station 1K06 was the AMFO while the best optimisation algorithm at station 1K07 was the HPSOGA. …”
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Final Year Project / Dissertation / Thesis -
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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…The Wisconsin dataset is used to evaluate the performance of these classifiers, and the hyperparameters are optimised using the JA-ABC5 algorithm. …”
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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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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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A modified weight optimisation for higher-order neural network in time series prediction
Published 2020“…The performance of MCS-MCMC learning algorithm was validated with several test functions and compared with those of MCS learning algorithm. …”
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Modelling Of Biogas Production From Banana Stem Waste With Neural Networks Learning Strategies To Optimse The Production
Published 2017“…In recent years, intelligence computation is applied to design a better process model and optimised biogas yield. This paper presents a comparative study of several neural networks learning (back-propagation, resilient propagation, Lavenberg-Marquardt and particle swarm optimisation) algorithms for process modelling and optimisation and its relation with the optimisation result. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…The interactive metamodel is extracted using Q-Learning (QL) via online observing and learning of the outflow-inflow traffic characteristics. …”
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14
Optimisation and control of fed-batch yeast production using q-learning
Published 2013“…To cater for the process disturbance, Q-learning with exploration (QLE) has been included in this work for online optimisation. …”
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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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Thesis -
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
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Student Project -
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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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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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Metaheuristic algorithms applied in ANN salinity modelling
Published 2024“…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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