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91 articles for “accuracy metric”
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Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning-Based Spectrum Sensing in Cognitive Radio Networks using Stacked LSTM: Performance Analysis of SNR and BERKavitha Veerappan, Seetharaman GopalakrishnanRapid evolution of wireless communication technologies and emergence of 5G networks have addressed lack of spectrum resources, highlighting the need for innovative topologies to improve the spectrum utilization. Due to this reason, Cognitive Radio (CR) has evolved as an optimized solution to overcome these difficulties by allowing dynamic spectrum access, thereby reducing the under-usage of available spectrum. Considering this, precise … …Journal of Computer Science, Vol. 21, Issue 11 · 19 Dec 2025 · 2,226 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Modified Enhancement Method for Dental Images - Towards the Effective Detection of Dental DisordersKrishnaveni R, Sudarmani RDental health maintenance is essential for overall physiological well-being, and X-ray imaging remains a fundamental diagnostic tool for comprehensive dental examination. While direct clinical observation by dentists is primary, computer-aided diagnostic tools serve as valuable secondary readers, enhancing diagnostic accuracy and efficiency. This study proposes and evaluates the Gaussian CLAHE Enhancement (GCE) method, which combines Gaussian filtering (GF) with Contrast … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,723 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploratory Data Analysis of Applications of Encryption for Netflix by ML ModelsAnanth Maria Pushpa, Subramanian ShanmugamThis study examines the performance of various machine learning algorithms in analyzing Netflix's dataset, with a focus on encryption methods used for data protection. We evaluated several models including Ada BoostM1, IBk, Random Forest, and Decision Stump using multiple performance metrics. This work analysis revealed that the Ada BoostM1 model achieved the highest accuracy at 97.14%, outperforming other algorithms. It … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 1,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,905 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 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstract3D-QSAR and SVM Prediction of BRAF-V600E and HIV Integrase Inhibitors: A Comparative Study and Characterization of Performance with a New Expected Prediction Performance MetricLeonard Wesley, Saihitha Veerapaneni, Rachana Desai et al.The results of directly comparing the prediction accuracy of optimized 3D Quantitative Structure-Activity Relationship (3D-QSAR) models and linear Support Vector Machine (SVM) classifiers to identify small molecule inhibitors of the BRAF-V600E and HIV Integrase targets are reported. Performance comparisons were carried out using 303 compounds (68 active) against BRAF-V600E and 204 compounds (159 active) against HIV Integrase. A SVM prediction … …American Journal of Biochemistry and Biotechnology, Vol. 12, Issue 4 · 17 Oct 2016 · 7,804 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Density Based Dynamic Data Clustering Algorithm based on Incremental DatasetS. Angel Latha Mary, K.R. Shankar KumarProblem statement: Clustering and visualizing high-dimensional dynamic data is a challenging problem. Most of the existing clustering algorithms are based on the static statistical relationship among data. Dynamic clustering is a mechanism to adopt and discover clusters in real time environments. There are many applications such as incremental data mining in data warehousing applications, sensor network, which relies on dynamic … …Journal of Computer Science, Vol. 8, Issue 5 · 20 Feb 2012 · 7,469 accessesView PDFCite
Research ArticleOpen accessIn the abstractPattern Trees for Fault-Proneness Detection in Object-Oriented SoftwareRomana Ishrat, Rafat Parveen, Syed I. AhsonProblem statement: This study introduced an application of pattern tree based classification technique in the area of object-oriented software quality estimation. This application explored the fault prediction accuracy of pattern trees. Approach: Similarity measures and fuzzy aggregations employed in the pattern tree technique had been used to generate tree models for fault detection in software modules. Experiments had been performed … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Jul 2010 · 6,953 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Control-Oriented Coverage Metric and its Evaluation for Hardware DesignsShireesh Verma, Kiran Ramineni, Ian G. HarrisProblem statement: Dynamic verification, the use of simulation to determine design correctness, is widely used due to its tractability for large hardware designs. A serious limitation of dynamic techniques is the difficulty in determining whether or not a test sequence is sufficient to detect all likely design errors. Coverage metrics are used to address this problem by providing a set … …Journal of Computer Science, Vol. 5, Issue 4 · 30 Apr 2009 · 7,531 accessesView PDFCite