Search Results - (( deep learning optimisation algorithm ) OR ( java implementation mining algorithm ))
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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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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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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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A review of hybrid deep learning applications for streamflow forecasting
Published 2024Subjects:Review -
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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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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Conference or Workshop Item -
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Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Conference or Workshop Item -
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…Choosing a suitable optimization algorithm in deep learning is essential for effective model development as it significantly influences convergence speed, model performance, and the success of the train- ing process. …”
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Proceeding Paper -
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024Subjects:Article -
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network
Published 2022“…The Long Short-Term Memory (LSTM) algorithm optimised using Particle Swarm Optimization (PSO) was selected as the model structure due to the system's high degree of nonlinearity. …”
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Proceeding -
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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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Article -
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Financial trading using learning-based approach
Published 2022“…In this work, deep reinforcement learning algorithms were applied to automate the trading process. …”
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Final Year Project / Dissertation / Thesis -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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Book Section -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Forecasting of fine particulate matter based on LSTM and optimization algorithm
Published 2024Subjects:Article -
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Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing
Published 2022“…In recent years, the advancement of deep learning algorithms and hardware enabled the use of artificial intelligence technology to automatically capture self-stimulatory behaviours. …”
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