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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
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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Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim
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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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
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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A medical cyber-physical system utilizing the bayes algorithm for post-diagnosis patient supervision
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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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
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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Hidden markov model for decision making among heterogeneous systems in intelligent building
Published 2014“…In order to improve the response time a machine learning algorithm like Hidden Markov Model (HMM) instead of the rule-based is used. …”
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
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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Evaluation of fall detection classification approaches
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia
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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Spear- phishing attack detection using artificial intelligence
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Sleep as a predictor of depression level using Naïve Bayes / Nur Syakinah Md Roduan
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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Android Ransomware Detection Based on Dynamic Obtained Features
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Network bandwidth utilization based on collaborative web caching using machine learning algorithms in peer-to-peer systems for media web objects
Published 2018“…On the other hand, they do not consider the advantages that can be given by applying these approaches in peer-to-peer systems. In this work, intelligent collaborative web caching approaches based on C4.5 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging
Published 2022“…Several machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, support vector machine, decision tree, and Naïve Bayes were applied for the classification of pineapple varieties. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…In future, this research can be an initial work in automating tutorial decisions in an intelligent tutoring system which are able to adapt to the behaviour of the learners based on the detected mental states. …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. Naïve Bayes is an intelligent method that depends on Bayes’ probability theory integrated with Adaptive Weight Ranking Policy (AWRP) via dynamic aging factor to improve the response time and network performance. …”
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