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Titlebook: LISS 2021; Proceedings of the 1 Xianliang Shi,Gábor Bohács,Xiaopu Shang Conference proceedings 2022 The Editor(s) (if applicable) and The A

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發(fā)表于 2025-3-21 16:18:05 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱LISS 2021
副標(biāo)題Proceedings of the 1
編輯Xianliang Shi,Gábor Bohács,Xiaopu Shang
視頻videohttp://file.papertrans.cn/581/580122/580122.mp4
概述Provides insights in solving the problems in logistics, informatics, service operations, and service science.Features research in areas as logistics, supply chain, information management, and service
叢書名稱Lecture Notes in Operations Research
圖書封面Titlebook: LISS 2021; Proceedings of the 1 Xianliang Shi,Gábor Bohács,Xiaopu Shang Conference proceedings 2022 The Editor(s) (if applicable) and The A
描述.This book aims to provide new research methods, theories and applications from various areas of management and engineering. In detail, the included scientific papers analyze and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of the papers delivers added value for both scholars and practitioners..Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations. To meet the needs of consumers and to promote core competences, many institutions and firms have been developing new types of services. This proceeding focus on “AI and data driven technical and management innovation in logistics, informatics and services.” In detail, the included scientific papers analyze the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. This book is the documentation of the conference “11th International Conference on Logistics, Informatics and Service Sciences,” which took place at the Shandong University. Due to the impact of COVID-19, LISS 2021
出版日期Conference proceedings 2022
關(guān)鍵詞information management; supply chain; service science; artificial intelligence and logistics; data drive
版次1
doihttps://doi.org/10.1007/978-981-16-8656-6
isbn_softcover978-981-16-8658-0
isbn_ebook978-981-16-8656-6Series ISSN 2731-040X Series E-ISSN 2731-0418
issn_series 2731-040X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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QL4POMR Interface as a Graph-Based Clinical Diagnosis Web Service,pose of diagnosis and prognosis with a varying backends. The QL4POMR implemented a mapping module to map graphs from POMR to HL7 FHIR and vise versa. Neo4j was used as backend to integrate all the data irrelevant of their nature as soon as the data is identified by objects and relations. The progres
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Prediction of Airway Management of Trauma Patients Based on Machine Learning, classifiers. The Adaboost model showed the best performance next, with an F-score of 0.8222 and the AUROC of 0.8935. The two algorithms based on decision tree are superior to Logistic Regression and SVM in this experiment. . Compared with the prediction model based on Logistic Regression, SVM or Ad
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