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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In this thesis the research of a self-learning algorithm will be presented, outlined and discussed in detailed manner. …”
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur
Published 2007“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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4
Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The product developed is in the form of a VR application that presents learning by having a variety of learning styles. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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DESIGN AND DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA FOR LEARNING ALGORITHM AND DATA STRUCTURE
Published 2021“…One of the learning techniques is in the form of algorithms and data structures. …”
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network
Published 2024“…The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”
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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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13
Machine learning: tasks, modern day applications and challenges
Published 2019“…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…This paper introduced a new machine learning algorithm called impact learning. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions
Published 2024“…This paper seeks to conduct a thorough systematic literature review (SLR) and offer a taxonomy of machine learning methods for malware detection that considers these problems by analyzing 77 chosen research works related to malware detection using machine learning algorithm. …”
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Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
Published 2019“…A new taxonomy is created based on natured inspired algorithms for deep learning. …”
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Proceeding Paper -
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…Then, the outcomes demonstrated that the best classifier for categorizing our data with 0.96% accuracy is the Decision Tree machine learning algorithm. When comparing the accuracy of a malware detection model, it is excellent if there are numerous machine learning algorithms and more malware datasets included.…”
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Student Project -
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…This paper introduced a new machine learning algorithm called impact learning. …”
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