Search Results - (( java implication based algorithm ) OR ( using sliding learning algorithm ))
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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning
Published 2024“…The FOSMC parameters are set by the ANN algorithm and then adapted through reinforcement learning to enhance the results. …”
Article -
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Date store management in sliding window based on-line identification algorithms
Published 2001“…Sliding window identification algorithms use information from a store of data to optimise on-line learning. …”
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Conference or Workshop Item -
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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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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh
Published 2019“…Standard base machine learning algorithms, which include a total of twelve individual methods as well as the AdaBoost and Bagging methods, are firstly used. …”
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Using streaming data algorithm for intrusion detection on the vehicular controller area network
Published 2022“…This has prompted researchers to develop statistical and machine learning based intrusion detection systems for the CAN bus that use various features such as message timing and frequency to detect attacks. …”
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Proceeding Paper -
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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Stock price prediction using machine learning: evidence from Pakistan stock exchange
Published 2024“…The model is trained using a sliding window approach and is evaluated using precision, recall, and F1-score metrics. …”
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Conference or Workshop Item -
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
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Model rangkaian neural bagi penentuan gaya pembelajaran pelajar berasaskan model Felder-Silverman
Published 2022“…These neural network models have been trained using records of how often a student visits learning content such as lecture notes, learning videos, teaching slides and online exercises. …”
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Content-based indexing of low resolution documents
Published 2016“…The database can be used for the purpose of file archiving, teaching and learning, research and knowledge management, which concern image search. …”
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Designing an integrated AIOT system for tracking class attendance
Published 2024“…Basics and ensures that the software is more secure than the previous traditional attendance method using roll-less slides. For face detection the system uses a YOLO (You Only Look Once) algorithm, which allows quick and efficient recognition of student faces in the classroom context. …”
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Final Year Project / Dissertation / Thesis -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Advanced data mining techniques for landslide susceptibility mapping
Published 2021“…SVM, RT, and NBM algorithms were used to produce predicted datasets from the training datasets. …”
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Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani
Published 2023“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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