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Intelligent systems in industrial ap...

(1998 :)

Intelligent systems in industrial applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent systems in industrial applicationsedited by Martin Stettinger ... [et al.].
其他作者:	Stettinger, Martin.
團體作者:
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xvi, 208 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligenceCongresses.Industrial applications
電子資源:	https://doi.org/10.1007/978-3-030-67148-8
ISBN:	9783030671488$q(electronic bk.)

Intelligent systems in industrial applications
Intelligent systems in industrial applications[electronic resource] /edited by Martin Stettinger ... [et al.]. - Cham :Springer International Publishing :2021. - xvi, 208 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9491860-949X ;. - Studies in computational intelligence ;v. 216..

Part I: Applications in the Automotive and Transport Sector -- Parameter Tuning for Speed Changes Detection in On-Road Audio Recordings of Single Drives? -- Attempt to better trust classiﬁcation models: Application to the Ageing of Refrigerated Transport Vehicles -- Part II: Perspectives on Artiﬁcial Learning -- Automatic Stopwords Identiﬁcation from Very Small Corpora -- BacAnalytics: A Tool to Support Secondary School Examination inFrance -- Towards Visual Concept Learning and Reasoning: On Insights into Representative Approaches -- The Impact of Supercategory Inclusion on Semantic Classiﬁer Performance -- Recognition of the Flue Pipe Type Using Deep Learning -- Part III: Industrial Applications -- Adaptive Autonomous Machines - Modeling and Architecture? -- Automated completion of partial conﬁgurations as a diagnosis task Using FastDiag to improve performance -- Exploring conﬁgurator users' motivational drivers for digital social interaction -- Impact of the Application of Artiﬁcial Intelligence Technologies in a Content Management System of a Media -- A Conversion of Feature Models into an Executable Representation in Microsoft Excel -- Part IV: Basic Research and Algorithmic Problems -- Explainable Artiﬁcial Intelligence. Model Discovery with Constraint Programming -- Deep Distributional Temporal Diﬀerence Learning for Game Playing.

This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.

ISBN: 9783030671488$q(electronic bk.)

Standard No.: 10.1007/978-3-030-67148-8doiSubjects--Topical Terms:

439227
Artificial intelligence
--Industrial applications--Congresses.

LC Class. No.: TA347.A78

Dewey Class. No.: 620.0028563

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520 $a This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.
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