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226 articles for “Learning Algorithms”

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Research ArticleOpen accessIn the abstractA Transformer Based Model to Detect Environmental Related Distress on Online Social MediaUtkarsh Sharma, Prateek Pandey, Shishir KumarOnline social media has been recently employed as the source of data for the detection of traffic-related activities and to control the flow of traffic in smart cities all over the world. Till now an ample amount of research work has been done in identification of traffic-related incidents with the help of online social media platforms (mostly Twitter). Along with … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 475 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning Framework for Strategic Gameplay Optimization in Scrabble Using Reinforcement LearningMohd Kaleem, Kanta Prasad Sharma, Tapsi Nagpal et al.This paper explores and compare various artificial intelligence-based techniques used for playing classic board game Scrabble. As the world is evolving around finding quick and efficient techniques for the solution of each problem using Machine learning, gaming industry is also a flourishing industry and has grown 9.8% compared to previous year and has generated a revenue of 26.14 billion dollars … …Journal of Computer Science, Vol. 22, Issue 9 · 22 Sep 2026 · 682 accessesView PDFCite
Research ArticleOpen accessIn the abstractChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 657 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,220 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 · 1,011 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 924 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCWDRL: Multi-Cloud Workflow Scheduling Using Deep Reinforcement Learning and Improved Workflow Segmentation for Multi-Cloud EnvironmentsS. Gowri, A. SumathiThe rapid growth of cloud computing has led to complex workflow scheduling challenges in multi-cloud environments, where efficient resource utilization, minimized makespan, and reduced costs are paramount. Traditional scheduling algorithms often struggle to adapt to the dynamic nature of cloud resources and workflows, leading to suboptimal performance. To overcome this issue, the paper proposed a novel Multi-Cloud Workflow Scheduling using … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 941 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Crow Search Optimization Based Feature Selection With Optimal DNN for Big Data ClassificationC. Mahesh, J. Ruby Elizabeth, S. Gnana Selvan et al.Big data analytics has become popular due to its applicability in various real-time applications. To attain better performance, big data can be analyzed using the machine learning and deep learning models at recent times, various domains have started to deal with big dataset which involves numerous sets of features. Repetitive and unwanted features, which reduces the classification performance can be … …Journal of Computer Science, Vol. 22, Issue 6 · 30 Jun 2026 · 1,257 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,351 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 · 1,504 accessesView PDFCite