The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on machine learning — spanning algorithms, applications, and techniques across computer science domains. One of the journal's largest and most active research areas.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
Rapid digitisation in communication and online platform growth have transformed information dissemination and facilitated rapid access while simultaneously amplifying the spread of fake news. This widespread issue underm…
Intent identification has become a difficult problem given the rising usage of multilingual and mixed-script inquiries, especially in areas where Roman transliteration is widely employed. Traditional intent detection sys…
Corrosion-induced damage poses a critical threat to the structural integrity of fluid transport pipelines, necessitating advanced detection strategies for early intervention. This study investigates the use of acoustic e…
This study examines the accuracy of order prediction and determines the grounds for order block predictions. It sets order deviation by calculating forecasted variation using R2 scores and mean absolute deviation. The bl…
Accurately predicting stock return can enhance the effectiveness of portfolio optimization models. Many previous studies typically divide machine learning algorithms and portfolio optimization into two separate stages: t…
The increased number of connected devices and the rise of Big Data have revolutionized industries and triggered a surge in cyberattacks, making security a top priority. Machine learning and Deep Learning algorithms are c…
An Artificial Intelligence-driven child learning system with a Machine Learning and Natural Language Processing-based approach to dynamically personalize educational experiences for children is proposed in this study. Us…
Algorithms for feature selection are growing in interest among researchers aiming to connect specific features in a dataset with specific classifications. Recent developments in machine learning, particularly Support Vec…
This study focuses on anomaly detection algorithms. Aiming at the limitations of traditional methods in complex data processing, an innovative algorithm that integrates random matrix theory and machine learning is propos…
This study aims to establish a dataset of kicks in Kempo martial arts to categorize athletes' kick types based on their movement patterns. The real problem addressed in this research is the lack of an accurate, efficient…
