Search Results - (( developing function learning algorithm ) OR ( learning operation using algorithm ))
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Reservoir water balance simulation model utilizing machine learning algorithm
Published 2023Article -
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review
Published 2021“…Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
Published 2019“…It will significantly help the oil and gas industry to schedule a replacement or maintenance before the machines end its operation. The project is developed using Deep Learning algorithm which the functionality can be found in KNIME Analytic application. …”
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Final Year Project -
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato...
Published 2025“…This technique uses the Adaptive Moment Estimation Method (Adam) as an optimization algorithm with feed-forward deep learning to minimize the error function and training the model using five layers with different activation functions. …”
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Campus study buddy : collaborative learning and resource sharing app
Published 2024“…The application is developed using Flutter and uses a tag recommendation algorithm to push content that users may be interested in, thereby intelligently providing users with an online learning environment that suits them and improving their learning efficiency. …”
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Final Year Project / Dissertation / Thesis -
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A review on machine learning in smart antenna: methods and techniques
Published 2022“…These systems require constant monitoring in order to function properly, allowing users to apply machine learning algorithms to analyse large amounts of data from various antenna settings. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…Addressing this issue, we propose to integrate the memory into EMCQ for combinatorial t-wise test suite generation using reinforcement learning based on the Q-learning mechanism, called Q-EMCQ. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…The aim of this paper is using an ensemble machine learning algorithm to develop a WAG incremental recovery factor predictive model that can be used by reservoir engineers to estimate WAG incremental recovery factor prior kick-off of laboratory experiments and comprehensive technical studies. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Unified neural network controller of series active power filter for power quality problems mitigation
Published 2013“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain
Published 2020“…The evaluation of the classifier that are developed are done by accuracy test and the system are evaluated by functionality test. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Application of deep learning technique to predict downhole pressure differential in eccentric annulus of ultra-deep well
Published 2021“…The data generated from this model, field data, and experimental data are used to train and test the FFBP-DNN networks. The network is developed used Kerasâ��s deep learning framework. …”
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