Regular Issues
K. Kantha Raju
India
KL University
Text mining, a crucial field within data mining, focuses on extracting meaningful patterns, trends, and knowledge from unstructured textual data. With the exponential growth of digital content, effective classification techniques have become essential for organizing and interpreting large text datasets. This paper reviews various data mining classification techniques applied in...
K. Sujatha
India
Dadi Institute of Engineering & Technology
Stock price forecasting is a critical task in financial analytics, aiming to predict future price movements and assist investors in making informed decisions. Traditional statistical approaches often struggle to capture the complex, nonlinear, and dynamic nature of financial markets. Supervised learning methods, a subset of machine learning, have shown significant...
K. Sujatha
India
Dadi Institute of Engineering & Technology
Disaster management requires rapid, accurate decision-making based on diverse and often unstructured data sources. Machine learning (ML) algorithms, particularly Naïve Bayes and Decision Trees, offer effective computational frameworks for predicting, classifying, and managing disaster-related information. This paper presents an architectural approach for applying these algorithms in disaster management systems. The...
K. Sujatha
India
Dadi Institute of Engineering & Technology
The rapid advancement of Artificial Intelligence (AI) and Deep Learning (DL) technologies has transformed industrial automation by enabling intelligent, adaptive, and self-optimizing systems. This paper proposes a two-level hybrid architecture for smart industrial automation based on AI-driven deep learning models. The architecture integrates both machine-level and system-level intelligence to enhance...
K. Sujatha
India
Dadi Institute of Engineering & Technology
The rapid advancement of Artificial Intelligence (AI) and Deep Learning (DL) technologies has transformed industrial automation by enabling intelligent, adaptive, and self-optimizing systems. This paper proposes a two-level hybrid architecture for smart industrial automation based on AI-driven deep learning models. The architecture integrates both machine-level and system-level intelligence to enhance...
Impact Factor
Scopus & Web of Science under Evalution
