CHAIN (CHAIN)

Chain, a scholarly peer-reviewed journal, aims to publish great advances made in the transportation related cutting-edge inter disciplines of information technology (artificial intelligence, intelligent control, computers, etc.), materials science (materials, chemical, metallurgy, etc.) and advanced manufacturing (transportation, aerospace, etc.). Chain is expected to foster the fusion of data and model for internet-of-things so as to pave a cross-disciplinary way in foundations, methodologies and applications. The journal considers full length article, short communications, perspective, review articles and paper previews, and publishes 4 volumes per year. Focal areas and topics of interest of the journal include, but are not limited to: Advanced design of energy materials, devices, and systems Reliability, durability and safety of intelligent energy management and control systems Internet-of-things and cyber-physical energy system and internet Advanced material design, signal processing techniques, data fusion techniques, intelligent algorithms, and artificial intelligence for intelligent sensors Hybrid model, data science, artificial intelligence, internet of things, digital twin, computational intelligence, evolutionary computation, machine, and deep learning Stereo-traffic network including new energy vehicles, aeronautics, and astronautics New technologies, processes, methods, materials, systems, and applications in the field of additive manufacturing

CHAIN (CHAIN) is :-

• International, Peer-Reviewed, Open Access, Refereed, Hybrid model, data science, artificial intelligence, internet of things, digital twin, computational intelligence, evolutionary computation , Print , Monthly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 2097-3470, Established: 2024,
• Provides Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE