Search Results - intelligence ai ((tree algorithm) OR (bayes algorithm))

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.

“…It's a type of Artificial Intelligence (AI) that makes predictions using statistical models. …”
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Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis by Baashar Y., Alkawsi G., Alhussian H., Capretz L.F., Alwadain A., Alkahtani A.A., Almomani M.

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

“…By employing Artificial Intelligence (AI), this study examines the interconnected nature of these complications. …”
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Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

Machine Learning Applications in Offense Type and Incidence Prediction by Balaji, R., Manjula Sanjay, Koti, Harprith, Kaur

“…We can develop targeted strategies to prevent and respond to such incidents by analyzing these patterns. Artificial Intelligence (AI) techniques encompass variouscomputational methods and algorithms designed to enable machines to perform tasks that typically require human intelligence. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. …”
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AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites by Alsariera, Y.A., Adeyemo, V.E., Balogun, A.O., Alazzawi, A.K.

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A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results by Ahmad Amin, Afifah Munirah, Abdullah, Adilah Syahirah, Lestari, Widya, Sukotjo, Cortino, Utomo, Chandra Prasetyo, Ismail, Azlini

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Optimized Model Inputs Selections for Enhancing River Streamflow Forecasting Accuracy Using Different Artificial Intelligence Techniques by Tofiq Y.M., Latif S.D., Ahmed A.N., Kumar P., El-Shafie A.

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

“…It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself as an area of computational intelligence. …”
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An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique by Almalawi, A., Alsolami, F., Khan, A.I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., Alfakeeh, A.S.

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

“…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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Prescription: Issue No. 7 (July 2024) by UiTM, Faculty of Pharmacy

“…ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. …”
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Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria by Zakaria, Yuslina

“…ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. …”
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An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM by Shozib, I.A., Ahmad, A., Rahaman, M.S.A., Abdul-Rani, A.M., Alam, M.A., Beheshti, M., Taufiqurrahman, I.

“…The four AI models applied in this study were Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF) and Extra Trees (ET). …”
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