Search Results - (( intelligence system from algorithm ) OR ( intelligence system bayes algorithm ))*

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

“…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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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

“…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 by Masmuhallim, Anis Athirah

“…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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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

“…The intelligent algorithm ML-ADR fault classifier model could discriminate 10 different far-end short circuit fault types from two network topology changes with and without midpoint integrated STATCOM on the Matlab/Simulink power grid system model. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

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

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

“…A classifier model is developed using Naive Bayes characteristics. 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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Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

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

“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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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

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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 by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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Sleep as a predictor of depression level using Naïve Bayes / Nur Syakinah Md Roduan by Md Roduan, Nur Syakinah

“…Busy with abundance of works and not having any time to seek a doctor for check-up may worsen the patient condition. 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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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

“…The hardware can be controlled through the graphical user interface (GUI) of software and can execute signal processing, feature ex-traction, and feature classification using artificial intelligence (AI). As AI, cas-cade forward neural network (CFNN) and naïve bayes (NB) algorithms are in-vestigated, then CFNN with four independent features (skewness, kurtosis, vari-ance, mean-absolute-deviation) are found to be best-suited for BGCL estimation. …”
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Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

“…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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Analysing the performance of classification algorithms on diseases datasets by Lydia E.L., Sharmil N., Shankar K., Maseleno A.

“…To advance such automatic healthcare prediction system, modern Artificial Intelligent technology has been developed an easy way to identify the existence of the diseases. …”

Android Ransomware Detection Based on Dynamic Obtained Features by Abdullah Z., Muhadi F.W., Hamid I.R.A., Foozy C.F.M., Madihah Mohd Saudi

Network bandwidth utilization based on collaborative web caching using machine learning algorithms in peer-to-peer systems for media web objects by Mohammed, Waheed Yasin

“…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 by Mohd Ali, Maimunah

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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…This study addresses this gap by leveraging data from the Behavioral Risk Factor Surveillance System (BRFSS)from 2016 to 2021 to categorize seven diabetes complications simultaneously. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…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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