Aims and scope

Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.  

All items relevant to building practical systems are within its scope, including but not limited to:

    adaptive computing
    algorithms
    applicable neural networks theory
    applied statistics
    architectures
    artificial intelligence
    benchmarks
    case histories of innovative applications
    fuzzy logic
    genetic algorithms
    hardware implementations
    hybrid intelligent systems
    intelligent agents
    intelligent control systems
    intelligent diagnostics
    intelligent forecasting
    machine learning
    neural networks
    neuro-fuzzy systems
    pattern recognition
    performance measures
    self-learning systems
    software simulations
    supervised and unsupervised learning methods
    system engineering and integration

Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value.  They will be reviewed by at least two referees. 

Special Issue on Cognitive based Information Processing and Applications 2024
提出日: 2025-12-30

The 4th International Conference on Cognitive based Information Processing and Applications (CIPA2024) was held in Changzhou, China, on November 22-23, 2024. The conference will communicate around the theory, technology and application of information processing and applications, including data mining, intelligent computing, deep learning and all other theories, models and technologies.

The purpose of CIPA2024 is to provide a forum for presentation and discussion of innovative ideas, cutting edge research results, and novel techniques, methods and applications on all aspects of technology and intelligence in information processing and applications. CIPA conference was founded by Prof. Jim Jansen of Qatar Computing Research Institute and Prof. Qingyuan Zhou who is the vice chancellor of Changzhou Vocational Institute of Mechatronic Technology. The proceedings of CIPA conferences are published by Springer in the book series named Lecture Notes on Data Engineering and Communications Technologies. Prof. Jun Ye of Hainan University is the Program Chair of CIPA2024.

This topical collection includes selected papers (with no less than 60% new content of the journal version) from the 4th International Conference on Cognitive based Information Processing and Applications (CIPA2024) as well as an open call. Subject of interests include, but are not limited to:

● Cognitive-inspired computing fundamentals
● Cognitive-inspired computing systems
● Cognitive-inspired computing with big data
● Cognitive-inspired intelligent interaction
● AI-assisted cognitive computing approaches
● Brain analysis for cognitive-inspired computing
● Internet of cognitive things
● Cognitive environment, sensing and data
● Cognitive robots and agents
● Security issue in cognitive-inspired computing
● Test-bed, prototype implementation and applications

Special Issue on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2024)
提出日: 2026-10-30

The "Internet of Things" heralds the connections of a nearly countless number of devices to the internet thus promising accessibility, boundless scalability, amplified productivity and a surplus of additional paybacks. The hype surrounding the IoT and its applications is already forcing companies to quickly upgrade their current processes, tools, and technology to accommodate massive data volumes and take advantage of insights. Since there is a vast amount of data generated by the IoT, a well-analysed data is extremely valuable. However, the large-scale deployment of IoT will bring new challenges and IoT security is one of them. The philosophy behind machine learning is to automate the creation of analytical models in order to enable algorithms to learn continuously with the help of available data. Continuously evolving models produce increasingly positive results, reducing the need for human interaction. These evolved models can be used to automatically produce reliable and repeatable decisions. Today's machine learning algorithms comb through data sets that no human could feasibly get through in a year or even a lifetime's worth of work. As the IoT continues to grow, more algorithms will be needed to keep up with the rising sums of data that accompany this growth. One of the main challenges of the IoT security is the integration with communication, computing, control, and physical environment parameters to analyse, detect and defend cyber-attacks in the distributed IoT systems.

The 5th International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2024) is an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary agenda of Internet of things. This collection includes selected papers (with no less than 60% new content of the journal version) from SPIoT 2024, as well as an open call.

Topics of interests include, but are not limited to:

* Novel machine learning and big data analytics methods for IoT security. * Big data analytics/machine learning/deep learning for IoT security such as smart grid security analytics. * Data mining and statistical modelling for the secure IoT. * Machine learning and big data analytics architectures for IoT security. * Machine learning based security detecting protocols. * Machine learning experiments, test-beds and prototyping systems for IoT security. * Analytics and machine learning applications to IoT security. * Data based metrics and risk assessment approaches for IoT. * Data confidentiality and privacy in IoT. * Authentication and access control for data usage in IoT. * Data-driven co-design of communication, computing and control for IoT security. * Big data analytics/machine learning/deep learning edge/fog security. * Emerging standards for IoT security.

A detailed call for papers is available at https://link.springer.com/journal/521/updates/27047404