Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

349 results for “Model Evaluation”
Set a search alert
Research ArticleOpen accessIn the abstractValidating and Evaluating a Dynamic Enterprise Architecture Model: A Case StudyImane Ettahiri, Latifa Rassam, Karim Doumi, Ahmed ZellouIn today’s rapidly changing business environment, adapting to evolving circumstances is a fundamental capability for organizations. Enterprise Architecture (EA) provides a holistic view of an organization’s structure, processes and technology, ensuring alignment with strategic objectives. However, traditional EA frameworks often lack the flexibility to dynamically respond to both predictable and unpredictable internal and external changes. This study proposes a novel, … …Journal of Computer Science, Vol. 21, Issue 3 · 7 Feb 2025 · 7,488 accessesView PDFCite
Research ArticleOpen accessIn the abstractHigh Accurate Multicriteria Cluster-Based Collaborative Filtering Recommender SystemZhila Yaseen Taha, Sadegh Abdollah AminifarA Recommender System (RS) is one of the appropriate answers by researchers for alleviating the problem of customers' overload with information from an internet source. In RS, users' evaluation of the items assists in quickly determining the user's preferences and removing the choosing overhead for the user the next time they search. However, using user ratings for an item based … …Journal of Computer Science, Vol. 18, Issue 12 · 10 Dec 2022 · 5,914 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecision Support Model for Determining the Best Employee using Fuzzy Logic and Simple Additive WeightingLucky Christopher Chen, Ditdit Nugeraha UtamaSpecifically, for an information technology company, identifying the best employees (the best programmers) is valuable. The election is intended to improve the performance of the company's programmers. The company's performance will improve as programmers' performance improves. This study attempts to develop a Decision Support Model (DSM) to identify the best employees (i.e., programmers) in the firm. The model considered nine … …Journal of Computer Science, Vol. 18, Issue 6 · 24 Jun 2022 · 6,100 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Convolutional Neural Network Approach for Skin Lesion Classification Using Imbalanced Dataset with Image AugmentationZhyar Yassin Abdalla, Nor Hazlyna Harun, Mohammed Shihab AhmedA significant threat to people's health all over the world is skin cancer. The purpose of this research is to improve the detection of skin cancer by utilizing a CNN classification model that makes use of preprocessing and augmentation techniques. The HAM10000 dataset is used, and the imbalance it contains is addressed by resizing the images to 120×120 pixels and … …Journal of Computer Science, Vol. 20, Issue 11 · 10 Sep 2024 · 5,427 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 670 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite
Research ArticleOpen accessIn the abstractLess Biased Approach for Sandstone Pore SegmentationDaffa Abiyyu Murtadha Kurnia, Iman Herwidiana KartowisastroReservoir characterization is a fundamental process in estimating reserves within petroleum and hydrogeological systems, where the precise determination of pore space dictates the validity of fluid flow models. Although X-Ray Computerized Tomography (XRCT) has become the standard non-destructive evaluation method for visualizing the internal structure of rocks, the data interpretation process still faces challenges during the image segmentation stage. Conventional … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,191 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Cloud Load Balancing Using Deep Q-Learning With Inverted S-Shaped Hierarchical Reverse Superb Fairy-Wren OptimizationB. R. Yogeetha, S. P. AnandarajCloud computing offers a scalable and cost-effective platform by providing on-demand access to shared computational resources. However, effective load balancing is essential to maintain optimal performance and maximize resource utilization for ensuring even distribution of network traffic across servers, preventing overload, improving response time and enhancing the system reliability. This manuscript proposes the Deep Q-Network with Inverted S-shaped Hierarchical Reverse … …Journal of Computer Science, Vol. 22, Issue 6 · 4 Jun 2026 · 1,497 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 Novel Deep Learning Approach for Tomato Leaf Disease Detection Using Optimized CNN ArchitectureSunil K. Vithalani, Vipul K. DabhiEarly disease detection in plants is essential for sustaining agricultural yield and guaranteeing food security. A comparative analysis of transformer-based and convolutional based deep learning models for classifying tomato leaf diseases is presented. Specifically, it examines the performance of a Vision Transformer (ViT), tested both in a form of scratch training setup and through transfer learning, against well-known CNN architectures … …Journal of Computer Science, Vol. 22, Issue 1 · 7 Feb 2026 · 3,917 accessesView PDFCite