Topic: Optimization of Big Data Analysis and Complex Database Systems

The increasing reliance on big data across sectors such as engineering, healthcare, transportation, and energy has significantly transformed the design, analysis, and management of complex engineering systems. Integrating big data analytics with complex database systems is crucial for unlocking the potential of large-scale data, improving decision-making, enhancing efficiency, and driving innovation. However, the rapid growth in data volume, variety, and complexity presents challenges in storage, retrieval, processing, and real-time analysis.

This Special Issue aims to explore innovative approaches to optimizing big data analysis and improving the performance of complex database systems. By leveraging advanced techniques such as machine learning, data mining, and artificial intelligence, the issue will focus on enhancing scalability, reliability, and efficiency in managing vast amounts of heterogeneous data. It will also address challenges such as ensuring data consistency, optimizing query performance, and maintaining data security and privacy in distributed systems. Topics of interest include, but are not limited to:

● Big Data Analytics in Complex Engineering Systems;

● Optimization Techniques for Large-Scale Database Systems;

● Data Integration and Fusion for Interconnected Systems;

● Machine Learning and AI Approaches for Big Data Optimization;

● Distributed Database Systems for Real-Time Data Processing;

● Cloud and Edge Computing for Big Data Management;

● Data Privacy, Security, and Integrity in Complex Databases;

● Efficient Query Processing in Complex Database Systems;

● Advanced Data Mining and Pattern Recognition for Complex Networks;

● Data Storage Architectures and Big Data Scalability;

● Parallel Computing Methods for Big Data Optimization;

● High-Performance Computing in Complex Engineering Systems;

● Case Studies on the Application of Big Data in Engineering;

● AI-Driven Optimization for Complex Systems and Databases;

● Fault Tolerance and Reliability in Big Data Systems.

We invite academics, research students, and professionals to submit their original work. Extended conference papers with at least 50% new content are also welcome.

Data analytics optimization, complex database systems, AI-driven optimization