02211nam 2200397 450 991072978110332120230729121552.010.3390/books978-3-0365-7442-4(CKB)4960000000469018(NjHacI)994960000000469018(EXLCZ)99496000000046901820230729d2023 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierData/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships /edited by Yuanqiao Wen, Axel Hahn, Osiris Valdez BandaBasel :MDPI - Multidisciplinary Digital Publishing Institute,2023.©20231 online resource (262 pages)3-0365-7442-5 Includes bibliographical references and index.Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regulations (i.e., knowledge) offer valuable prior knowledge about ship manners at sea. Combining multisource heterogeneous big data and artificial intelligence techniques inspires innovative and important means for the development of MASS. This reprint collects twelve contributions published in "Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships" Special Issue during 2021-2022, aiming to provide new views on data-/knowledge-driven analytical tools for maritime autonomous surface ships, including data-driven behavior modeling, knowledge-driven behavior modeling, multisource heterogeneous traffic data fusion, risk analysis and management of MASS, etc.Dialectical behavior therapyDialectical behavior therapy.616.89142Valdez Banda OsirisHahn AxelWen YuanqiaoNjHacINjHaclBOOK9910729781103321Data892730UNINA