Virtual Special Issue on New Paradigms, Trends and Applications of Machine Learning and Soft Computing in Cyber-Physical Systems
For this Virtual Special Issue in Applied Soft Computing, authors are invited to submit their original works focusing on how Cyber-Physical Systems can benefit from its synergy with Soft Computing techniques and Machine Learning models, with an emphasis on evidences of the practicability of the reported findings. Topics of interest for this special issue include, but are not limited to, the following:
- Novel Soft Computing techniques and their application to problems related to CPS, such as distributed predictive modelling, hybrid optimization techniques, online learning over data streams, concept drift adaptation, automated model construction, large-scale deployment of Soft Computing techniques, collaborative reasoning and weakly/semi-supervised learning, among others
- Data analytics and scalable/parallel/distributed computing algorithms for CPS
- Artificial Intelligence (AI) as a service (AIaaS) for CPS
- Energy efficiency paradigms for CPS tackled via Soft Computing and Machine Learning
- Distributed computing, data fusion and aggregation over large-scale CPS
- Predictive and clustering models for CPS self-configuration, self-resilience and self-autonomy
- Optimization algorithms for optimal sensor actuation
- Autonomic computing, inference of human patterns, analysis, monitoring, and situation alertness in CPS
- Federated learning, collaborative machine learning and distributed AI for large scale CPS
- Soft Computing techniques to enable ultra-reliable, low-latency applications in CPS scenarios.
For further information about the deadlines or the editorial board, please, check the journal’s S.I. webpage.