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Research ArticleOpen accessIn the keywordsA Weighted Voting Deep Learning Approach for Plant Disease ClassificationAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabPlant destruction is usually caused by plant diseases. Without early and reliable detection, it can affect the plants and may eventually cause permanent losses, especially for inexperienced farmers. Therefore, intelligence in agriculture is becoming more and more required. Thereafter early diagnosis and classification are crucial and a very challenging research field in the agriculture sector for its treatment. In this … …Journal of Computer Science, Vol. 17, Issue 12 · 16 Dec 2021 · 6,557 accessesView PDFCite
Review ArticleOpen accessIn the keywordsAn Insight into Rare Class Problem: Analysis and Potential SolutionsSatyam Maheshwari, R.C. Jain, R.S. JadonThe class imbalance problem presents an important challenge to the data mining community, in which the number of examples of one class is more than the others. This problem is characterized by a different distribution of cases between all the classes. In this paper, our goal is to study the various challenges of class imbalance problem and provide a comparative … …Journal of Computer Science, Vol. 14, Issue 6 · 9 May 2018 · 8,387 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Five Decomposition Techniques for Monthly Rainfall Time Series from 1991 to 2020 in Guinea (West Africa)Noukpo Médard Agbazo, Oumar Keita, Alpha Oumar Baldé et al.The selection of an optimal time series decomposition’ technique is crucial for enhancing rainfall prediction by using sophisticated methods as deep learning hybrid approaches. This study evaluates the effectiveness of five times series decomposition techniques in analyzing monthly rainfall datasets across Guinea geographical regions (Lower-Guinea (Boké, Conakry, Kindia), Middle-Guinea (Labé, Mamou), Upper-Guinea (Faranah, Kankan) and Forest-Guinea (Nzérékoré)) and identifies the … …American Journal of Applied Sciences, Vol. 22, Issue 1 · 27 Jan 2026 · 3,040 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat DiseasesSajjad Saleem, Adil Hussain, Nabila Majeed et al.Wheat is an important source of dietary fiber and protein that is negatively impacted by a number of risks to its growth. The difficulty of identifying and classifying wheat diseases is discussed with an emphasis on wheat loose smut, leaf rust, and crown and root rot. Addressing conditions like crown and root rot, this study introduces an innovative approach that … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Jan 2025 · 6,344 accessesView PDFCite
Research ArticleOpen accessIn the abstractContext Tamil Llama-QA: A Question and Answering Framework for Semantic Information Retrieval Using Tamil Large Language ModelJeevit Davidson S., M. MuraliThe Question Answering System (QA) is essential for effectively retrieving and providing relevant information, and its performance is heavily reliant on the efficiency of information retrieval mechanisms. As the volume of information within the corpus continues to grow, the complexity of generating accurate and pertinent answers also increases substantially. This challenge is particularly significant when designing QA systems for regional … …Journal of Computer Science, Vol. 22, Issue 10 · 7 Oct 2026 · 442 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Weighting Technique Based Arctic Puffin Optimization for Energy Efficient Data Transmission in Wireless Sensor NetworksM. Bharathraj Kumar, S. Avinash, Prakash G. Gani, Prathapchandra ShettyWireless Sensor Networks (WSNs) are designed using various sensor nodes, which are employed for communication in diverse applications that include healthcare, industrial areas, and smart cities. Specifically, WSNs demand energy-efficient clustering and routing mechanisms that assist in extending network lifetime due to the limited battery capacity of sensor nodes. However, many existing meta-heuristic-based approaches incorporate fixed objective weights that struggle … …Journal of Computer Science, Vol. 22, Issue 9 · 10 Sep 2026 · 767 accessesView PDFCite