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99 results for “Decision Support Model”
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Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelliHealth: A Machine Learning Driven Disease Detectionand Diet recommendation SystemAnkita Wadhwan, Priyanka Chawla, Sandeep Kaur, Usha MittalPeople all around the world are afflicted with various ailments. An accurate diagnosis can lower the risk of significant health problems developing, but an inaccurate diagnosis could have adverse implications. In this study, an ensemble-based strategy "IntelliHealth" has been presented to identify disorders of the thyroid, liver, and breast cancer using three machine learning (ML) approaches consisting of Support Vector … …Journal of Computer Science, Vol. 21, Issue 6 · 28 May 2025 · 5,226 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,578 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Approaches for the Prediction of Gas Turbine TransientsArnaud Nguembang Fadja, Giuseppe Cota, Francesco Bertasi et al.Gas Turbine (GT) emergency shutdowns can lead to energy production interruption and may also reduce the lifespan of a turbine. In order to remain competitive in the market, it is necessary to improve the reliability and availability of GTs by developing predictive maintenance systems that are able to predict future conditions of GTs within a certain time. Predicting such situations … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 7,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasuring Customers’ Satisfaction Using Sentiment Analysis: Model and ToolAhmed Alqurafi, Tawfeeq AlsanoosyCustomer reviews are a valuable data resource for business owners and companies. Customers frequently write reviews on many platforms, such as eBay or Amazon. These reviews show, for instance, to what extent customers are satisfied with a service or a product. Therefore, these reviews can be used by companies and business owners to improve their services or products. However, numerous … …Journal of Computer Science, Vol. 20, Issue 4 · 7 Feb 2024 · 6,471 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeta Analysis of Growth Performance of Broilers in Response to Dietary Cassava Leaf Meal InterventionChristian Anayo Mbajiorgu, Ifeanyi Princewill OgbuewuThe use of Cassava Leaf Meal (CLM) in broiler diets has gained attention due to its high crude protein content (24-35%) and other valuable nutrients. Therefore, the objective of this meta-analysis was to assess the impact of diets with and without CLM on broiler growth performance. Search performed on four bibliographic databases produced 584 articles of which 11 were used … …American Journal of Animal and Veterinary Sciences, Vol. 21, Issue 3 · 30 Sep 2026 · 578 accessesView PDFCite