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  1. 1
    Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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  2. 2
    Intelligent guidance parking system using modified Dijkstra's algorithm

    Intelligent guidance parking system using modified Dijkstra's algorithm by Jaafar, Haslina, Zabidi, Muhamad Hidayat, Che Soh, Azura, Thong, Peng Hoong, Shafie, Suhaidi, Ahmad, Siti Anom

    Published 2014
    “…This paper presents the intelligent parking system which apply Dijkstra’s algorithm in finding the shortest path. …”
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  3. 3
    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms

    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

    Published 2022
    “…For the objective of classifying FI in terms of fraud or not, the Intelligent Information System for Financial Institutions (IISFI) relying on Supervised ML (SML) Algorithms has been created in this work. …”
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  4. 4
    A medical cyber-physical system utilizing the bayes algorithm for post-diagnosis patient supervision

    A medical cyber-physical system utilizing the bayes algorithm for post-diagnosis patient supervision by Mizanur, Rahman, Talha, Sarwar, Ahmed, Zahiduddin, Miah, M. Saef Ullah, Bhowmik, Abhijit, Nusrat, Fahmeda, Junaida, Sulaiman

    Published 2024
    “…Therefore, this article proposes an adaptive system based on the Bayes algorithm for performing medical interventions on patients, leading to a reduction in the dependence on caregivers, particularly in the post-diagnosis scenario.…”
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  5. 5
    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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  6. 6
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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  7. 7
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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  8. 8
    Hidden markov model for decision making among heterogeneous systems in intelligent building

    Hidden markov model for decision making among heterogeneous systems in intelligent building by Abba, Babakura

    Published 2014
    “…The inability of systems, devices and sensors to interoperate is the main drawback in intelligent building. …”
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  9. 9
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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  10. 10
    Evaluation of fall detection classification approaches

    Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

    Published 2012
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  11. 11
    iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems

    iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

    Published 2024
    “…For this intelligent TMM, a variant of Frequency Pattern Growth (FP-Growth), called enhanced FP-Growth (EFP-Growth) algorithm is developed by altering the internal data structures for faster execution and by developing a modified exponential decay function (MEDF) to automatically calculate minimum supports for adapting trust evolution characteristics. …”
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  12. 12
    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification

    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification by Nurcahyawati, Vivine, Mustaffa, Zuriani

    Published 2021
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  13. 13
    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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  14. 14
    Automated Nutritional Guidance for Obesity Management: Insights from Machine Learning, Naïve Bayes, Random Forest

    Automated Nutritional Guidance for Obesity Management: Insights from Machine Learning, Naïve Bayes, Random Forest by A., Rupa, Ch. Akshaya, Reddy, E., Shravya, E., Akshaya, K., Rajasri

    Published 2025
    “…The system utilizes a combination of machine learning algorithms, nutritional databases, and user input to provide personalized dietary plans aligned with individual health goals, dietary preferences, and lifestyle patterns. …”
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  15. 15
    Spear- phishing attack detection using artificial intelligence

    Spear- phishing attack detection using artificial intelligence by Rajkumaradevan, Sanglidevan

    Published 2024
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  16. 16
    Sleep as a predictor of depression level using Naïve Bayes / Nur Syakinah Md Roduan

    Sleep as a predictor of depression level using Naïve Bayes / Nur Syakinah Md Roduan by Md Roduan, Nur Syakinah

    Published 2017
    “…So, a prediction system was developed to predict students' level of depression based on their sleep behaviors that uses Naïve Bayes method, which implement Artificial Intelligence (AI) as result of survey conducted to the target user proved that majority of them need a system that can predict depression level. …”
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  17. 17
    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia

    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

    Published 2025
    “…This study proposes an Intelligent Teacher Placement Selection (ITPS) system based on a Staff Placement Model (SPM), expanding the attribute set to 27 by incorporating personal, staffing position, placement type, and human factors to enhance decision-making fairness. …”
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  18. 18
    Non-Invasive Diabetes Level Monitoring System using Artificial Intelligence and UWB

    Non-Invasive Diabetes Level Monitoring System using Artificial Intelligence and UWB by Islam, Minarul, Sabira, Khatun, Shoumy, Nusrat Jahan, Ali, Md Shawkat, Mohamad Shaiful, Abdul Karim, Bari, Bifta Sama

    Published 2020
    “…To overcome this drawbacks, a non-invasive ul-tra-wideband (UWB) BGCL measurement system is proposed here with en-hanced software module. …”
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  19. 19
    Bayesian Network Classifiers for Damage Detection in Engineering Material

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
    “…The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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  20. 20
    Empirical study on intelligent android malware detection based on supervised machine learning

    Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

    Published 2020
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