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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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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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Student Project -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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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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Integrating finance dictionary in lexicon-based approach with machine learning algorithm to analyse the impact of OPEC news sentiment on financial market / Wu Ling
Published 2020“…The labelled sentences are then used to train the supervised machine learning classifiers. …”
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Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size
Published 2024Conference Paper -
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…To improve the detection accuracy for future research, it is suggested that the malware dataset be enhanced using several architectures, such as Linux and Android, and use additional supervised and unsupervised machine learning algorithms.…”
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Destination prediction based on past movement history
Published 2020“…In this paper we explore destination prediction using the past movement history, where the history is built using machine learning. …”
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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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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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The impact of news sentiment on the stock market fluctuation : the case of selected energy sector
Published 2021“…We developed a financial news sentiment classifier by combining machine learning algorithms and lexicon-based labelling methods. …”
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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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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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Noise reduction techniques in ECG signal
Published 2023“…The algorithm has been tested on the collected dataset using MATLAB. …”
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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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Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…Using a different initial point, all of them produced the correct results …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…In the online phase, the stream clustering algorithm for trajectories based on the lifespan of the cluster is proposed (CC_TRS) to overcome the limitations of the time window technique. …”
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