In an era where Big Data has permeated every aspect of our lives, the importance of Computational Intelligence (CI) cannot be overstated. CI is not merely a set of computational techniques; it is a dynamic amalgamation of soft computing, machine learning, engineering disciplines, and more. It investigates, simulates, and analyzes exceptionally intricate issues and phenomena, closely related to Evolutionary Intelligence. This special issue aims to explore the rapid strides made in CI in the context of Big Data.

The confluence of CI with Big Data has emerged as a novel research front, capturing the imagination of both academia and industry. Big Data, characterized by large, complex data sets that defy traditional processing and analysis tools, has found a powerful ally in CI. This collaboration enhances decision-making, insight discovery, and optimization processes. However, the journey is far from over, with numerous technical challenges and issues that still beg exploration and improvement.

This special issue seeks to illuminate the latest advances in the techniques of the CI domain, including Evolutionary Algorithms, Swarm Intelligence, Artificial Neural Networks, among others. The following is an overview of the accepted papers.

  • Time Series and Prediction: a paper introducing a new algorithm for time series prediction using machine learning models.

  • Education and Culture: contributions include AI-based English teaching, metaverse-driven new energy of Chinese traditional culture education, and basketball-assisted teaching in instructional videos.

  • Optimization and Analysis: research on a self-learning particle swarm optimization algorithm, a hybrid approach to talent demand forecast in the IT industry, and an improved binary particle swarm optimization are part of this category.

  • Health and Wellness: there are noteworthy papers on psychological balance detection of athletes through EEG signal analysis and a classification model for meticulous prediction of heart disease.

  • Energy and Environment: papers include metaverse-driven remote management solutions for energy storage power stations and a prediction method of intelligent building electricity consumption.

  • Language and Text Analysis: several papers delve into English text analysis, including big data-driven English teaching, sentiment analysis, and style recognition of English novels.

  • Technology and Sports: topics include track and field training state analysis and data-driven intelligent action recognition in sports training and teaching.

  • Industry and Business Applications: this includes smart advertising design, adaptive industrial control data analysis, and building detection in remote sensing images.

The compilation of these 27 papers spans a broad spectrum of the field, mirroring the latest breakthroughs, methodologies, and groundbreaking solutions. We trust that readers will draw inspiration from these contributions and that they will catalyze continued growth and exploration in this swiftly progressing domain.