Search Results - (( intelligence system bayes algorithm ) OR ( intelligence systems _ 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

“…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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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

“…This paper presents the intelligent parking system which apply Dijkstra’s algorithm in finding the shortest path. …”
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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.

“…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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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

“…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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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

“…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 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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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

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

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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

“…This paper presents the design and development of an Automated Nutritional Guidance System aimed at enhancing obesity management through intelligent, user-centered dietary recommendations. …”
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Spear- phishing attack detection using artificial intelligence by Rajkumaradevan, Sanglidevan

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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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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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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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