Special Issue on ML Algorithms, Techniques, and Systems for CPS
摘要截稿:
全文截稿: 2019-04-20
影响因子: 3.954
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 计算机科学 - 2区
• 小类 : 计算机:跨学科应用 - 3区
Overview
Cyber Physical Systems (CPS) are integrations of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. Cyber physical systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Industrial cyber physical systems is to conduct pre-competitive research on architectures and design, modeling, and analysis techniques for cyber-physical systems, with emphasis on industrial applications. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Nowadays, machines can learn und develop self-maintaining procedures, meaning that those systems can provide a broad range of substantial improvements if introduced in production. Due to the highly complex intertwining among different components, Industrial cyber physical systems poses fundamental challenges in multiple aspects, such as real-time data processing, efficient parallel computing, data sensing and collection, and distributed computing. Over the last decade, Machine Learning (ML) algorithms have achieved impressive results providing solutions to practical large-scale complex problems. Not surprisingly, ML is being used in Industrial cyber physical systems-systems that are integrations of computation with physical processes. The special issue will include current and future research directions in ML algorithms for Industrial cyber physical systems in aerospace, automotive, medical, energy and other sectors such as manufacturing.
The following is a non-exhaustive list of topics considered for this special issue:
Learning theory (supervised/unsupervised) for Industrial cyber physical systems
Deep learning for Industrial cyber physical systems
Cognitive systems for Industrial cyber physical systems
Multimodal Learning algorithms for Industrial cyber physical systems
Incremental learning for Industrial cyber physical systems
Structure learning for Industrial cyber physical systems
ML algorithms for audio, video and image processing in Industrial cyber physical systems
Signal transformations in Industrial cyber physical systems using ML
Mathematical foundations of ML for Industrial cyber physical systems
ML algorithms for signal detection and synchronization in Industrial cyber physical systems
Distributed, decentralized, and cooperative Industrial cyber physical systems using ML algorithms
ML algorithms in commercial/standardized (LTE, LTE/A, WiMAX etc.) techniques for Industrial cyber physical systems
ML based optical communications in Industrial cyber physical systems
ML based smart grid and powerline communications in Industrial cyber physical systems
ML algorithms for localization, positioning and tracking techniques in Industrial cyber physical systems
ML based fast or low-complexity algorithms for ubiquitous communication in Industrial cyber physical systems