Search Results - (( data learning module algorithm ) OR ( java application learning algorithm ))
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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Article -
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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Thesis -
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking
Published 2018“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Thesis -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Thesis -
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Detection of surface defects of aluminium extrudants using artificial intelligence
Published 2024“…The objectives of this study include implement YOLOv8 model to identify and categorise the aluminium surface defect with the aid of data augmentation, transfer learning and addition of attention modules. …”
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Final Year Project / Dissertation / Thesis -
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Diagnostic And Classification System For Kids With Learning Disabilities
Published 2017“…Most experts are using manual techniques to diagnose dyslexia. Machine learning algorithms are capable enough to learn the knowledge of experts and thus, automation of the diagnosis process is possible. …”
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Proceeding -
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Conference or Workshop Item -
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Thesis -
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Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail
Published 2021“…By using remote sensing method, it can reduce time to collect data for a large area. The data can be gain in high or low resolution. …”
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Thesis -
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A framework for Malaysian Sign Language Recognition using deep learning initiatives / Imran Md Jelas
Published 2022“…Hence, the main objective of this paper is to develop a Framework for Malaysian Sign Language Recognition using Deep Learning. To achieve this objective, we propose a framework consisting of three main modules namely learning module, training module and detection module. …”
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)
Published 2017“…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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Monograph -
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan
Published 2024“…This paper proposes a sophisticated Job Position Prediction system utilizing Machine Learning algorithms and leveraging data from LinkedIn profiles. …”
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Thesis -
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The Effectiveness Of Steam Integrated Approach Using Scratch Module On Achievement And Computational Thinking In Learning Electricity Concepts
Published 2022“…This study examined the effectiveness of STEAM (Science, Technology, Engineering, Art, Mathematics) integrated approach via Scratch module in enhancing and retaining achievement, computational thinking (CT) and five subconstructs of CT in learning electricity concepts among 29 male and 30 female Form two secondary school students through Scratch module, which was developed based on ASSURE model. …”
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Thesis -
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Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024Conference Paper -
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Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities
Published 2018“…Most experts are using manual techniques to diagnose dyslexia. Machine learning algorithms are capable enough to learn the knowledge of experts and intelligently diagnose and classify dyslexics. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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