Search Results - (( pattern machine algorithm ) OR ( self ((learning algorithm) OR (learning algorithms)) ))
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1
BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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2
Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Self-Organizing Feature (SOM) was used to visualize and identify the relationship and pattern between factors affecting mortality after ACS. …”
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3
Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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4
Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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5
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…As cyber threats grow in complexity and frequency, the importance of Network Intrusion Detection Systems in modern cybersecurity defense becomes increasingly critical. Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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6
Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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7
Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
Published 2023“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection
Published 2021“…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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10
Computer-aided system for extending the performance of diabetes analysis and prediction
Published 2021“…The machine learning algorithms used to predict the risks of Type 2 diabetes. …”
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
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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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13
Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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15
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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16
An early warning system for students at risk using supervised machine learning
Published 2024“…For that, this study will perform a study of the current issues, factors, and solutions in education student’s data, determine the supervised machine learning algorithms, compare which model is the best predict the students’ performances, develop an early warning system for the educators to make an early decision in order to assist and consult the at-risk students, and finally conduct testing and evaluation of the system. …”
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17
A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby
Published 2006“…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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Student Project -
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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19
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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Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning
Published 2023Conference Paper
