4 results for “Artificial Neural Networks (ANNs)”

Set a search alert

Research ArticleOpen accessIn the keywordsSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,378 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsBehaviour Based Worm Detection and Signature AutomationMohammed Anbar, Selvakumar Manickam, Al-Samarraie Hosam et al.Problem statement: A worm is a malicious piece of code that self-propagates, often via network connections, to exploit security flaws in computers connected through the network. In general, worms do not need any human intervention to propagate and are considered a real threat to network assets and the properties of organizations. An Intrusion Detection Systems (IDSs) are employed to detect … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 6,895 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeep Learning Analysis of Drug Reviews: Identifying Patient Conditions, Predicting Drug Ratings, and Sentiment AnalysisRafat Hammad, Mohammad Ashraf Ottom, Ayah Bani BakerUnderstanding patients' experiences with medications is essential for improving drug effectiveness, detecting potential side effects, and enhancing overall patient satisfaction. This research investigates applying machine learning to patient drug reviews across three main tasks: Identifying patient conditions, predicting drug ratings, and performing sentiment analysis. We implemented and evaluated Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Recurrent Neural Networks … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 736 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparative Analysis of the Artificial Neural Networks Options Pricing Model Under Constant and Time-Variant VolatilitiesHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiOption pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 20 Jul 2019 · 7,010 accessesView PDF Cite