Search Results - (( learning application optimisation algorithm ) OR ( java implementation modified algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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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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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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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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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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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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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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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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Particle Swarm Optimisation with Improved Learning Strategy
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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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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey
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EEG-based emotion recognition using machine learning algorithms
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Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.]
Published 2022“…This paper presents the machine learning algorithm applications on the prediction of property prices and rents in real estate. …”
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