Search Results - (((( based learning algorithm ) OR ( e learning algorithm ))) OR ( patterns among algorithm ))

STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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Application of machine learning and artificial intelligence in detecting SQL injection attacks by Md Sultan, Abu Bakar, Agiliga, Nwabudike Augustine, Osman, Mohd Hafeez Bin, Sharif, Khaironi Yatim

“…Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored, these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions, with some algorithms scoring up to an 80 percent success rate in identifying SQL injections. …”
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E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

“…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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Transformer-Based Model for Malicious URL Classification by Do N.Q., Selamat A., Lim K.C., Krejcar O., Ghani N.A.M.

Q-Learning-based detection of IPv6 intrusions: a behavioral and performance study by Daru, April Firman, Hirzan, Alauddin Maulana, Mahmod Attar Bashi, Zainab Senan, Fanani, Fajriannoor

“…To address this limitation, the present study proposes a self-learning model using reinforcement learning techniques, specifically the Q-Learning algorithm, to classify network intrusions based on learned behavioural patterns autonomously. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan by Jamel, Shafie, Sayan, Giuseppina Sherry

“…This new trend gives an advantage to cryptanalyst since types of algorithm(s) used are no longer a secret. Cryptanalysis steps can be easily explained using algorithm animation that can be easily integrated with any e-learning platform. …”
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An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…Both techniques are used to devise an adaptive algorithm which efficiently manages the clustering of students based on their VAK aptitudes and predicts the future e-learning framework for these students. …”

A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

Subjects: “…e-Learning…”

Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Subjects:

Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

Subjects: “…Deep learning algorithms…”

The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

Subjects:

Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Nevertheless, many metaheuristic algorithms are still suffering from a low convergence rate because of the poor balance between exploration (i.e. roaming new potential search areas) and exploitation (i.e., exploiting the existing neighbors). …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…Recently, more robust algorithms based on deep reinforcement learning (DRL) have been proposed. …”

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization by Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.

“…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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