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169 articles for “machine learning algorithms”
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Research ArticleOpen accessIn the keywordsHighly-Available, Collaborative, Trainable Communication – a Policy – Neutral ApproachChristian Schreibaumer, Isabella Stein, Eberhard DobermannScalable theory have led to many advances. Data flow is constantly growing and systems are expanding. Theoretical principles of red-black trees can help to build a scalable system, where data easily can expand and in the end energy is saved. We propose a novel solution, an organizational platform, an algorithm for the analysis of agents, which we call Mop. With … …Journal of Computer Science, Vol. 14, Issue 6 · 5 Apr 2018 · 9,778 accessesView PDFCite
Research ArticleOpen accessIn the abstractProbabilistic Learning Models for Secure E-Commerce Transaction AnalysisAnanth Maria Pushpa, S. SubramaniaanThe tremendous expansion of e-commerce requires well-developed security mechanisms of transactions coupled with cryptography systems. This paper explores how probabilistic learning algorithms can be used to promote fraud and transaction validation in e-commerce systems that are cryptographically secured. A study compared different machine learning models to analyze retail data, including Naïve Bayes, Bayes Network, and Logistic learning. The results showed … …Journal of Computer Science, Vol. 22, Issue 11 · 20 Oct 2026 · 527 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 632 accessesView PDFCite
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 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 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