國立高雄大學圖資館 |

登入

回首頁

Multigrammatical framework for knowledge-based digital economy

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multigrammatical framework for knowledge-based digital economyby Igor A. Sheremet.
作者:	Sheremet, I. A.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xiv, 461 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Expert systems (Computer science)
電子資源:	https://doi.org/10.1007/978-3-031-13858-4
ISBN:	9783031138584$q(electronic bk.)

Multigrammatical framework for knowledge-based digital economy
Sheremet, I. A.

Multigrammatical framework for knowledge-based digital economy[electronic resource] /by Igor A. Sheremet. - Cham :Springer International Publishing :2022. - xiv, 461 p. :ill., digital ;24 cm.

Preface -- Introduction -- Sociotechnological systems and associated problems -- Syntax, semantics and mathematical properties of multiset grammars -- Basic algorithmics of multiset grammars and metagrammars -- Resource-consuming sociotechnological systems -- Industrial sociotechnological systems -- Economical sociotechnological systems and economical combinatorics -- Resilience and recovery of sociotechnological systems -- Resource-based games -- Multigrammatical representation of classic problems of operations research -- Interconnections between multiset grammars and models of computation -- Implementation issues and future developments -- Conclusion -- References -- Index -- List of Acronyms.

This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS) This framework is meant to enable smart operation not only in a "business-as-usual" mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming. The mathematical background needed for MGF, its algorithmics, applications, implementation issues, as well as its nexus with known models from operations research and theoretical computer science areas are considered. The resilience and recovery issues of an STS are studied by applying the MGF toolkit and on paying special attention to the multigrammatical assessment of resilience of energy infrastructures. MGF-represented resource-based games are introduced, and directions for further development are discussed. The author presents multiple applications to business intelligence, critical infrastructure, ecology, economy and industry. This book is addressed to scholars working in the areas of theoretical and applied computer science, artificial intelligence, systems analysis, operations research, mathematical economy and critical infrastructure protection, to engineers developing software-intensive solutions for implementation of the knowledge-based digital economy and Industry 4.0, as well as to students, aspirants and university staff. Foundational knowledge of set theory, mathematical logic and routine operations on data bases is needed to read this book. The content of the monograph is gradually presented, from simple to complex, in a well-understandable step-by-step manner. Multiple examples and accompanying figures are included in order to support the explanation of the various notions, expressions and algorithms.

ISBN: 9783031138584$q(electronic bk.)

Standard No.: 10.1007/978-3-031-13858-4doiSubjects--Topical Terms:

182450
Expert systems (Computer science)

LC Class. No.: QA76.76.E95 / S44 2022

Dewey Class. No.: 006.33

Multigrammatical framework for knowledge-based digital economy
LDR:03961nmm a2200325 a 4500 001 631180
003 DE-He213
005 20221029145826.0
006 m d
007 cr nn 008maaau
008 230411s2022 sz s 0 eng d
020 $a 9783031138584$q(electronic bk.)
020 $a 9783031138577$q(paper)
024 7 $a 10.1007/978-3-031-13858-4 $2 doi
035 $a 978-3-031-13858-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.76.E95 $b S44 2022
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.33 $2 23
090 $a QA76.76.E95 $b S551 2022
100 1 $a Sheremet, I. A. $3 936823
245 1 0 $a Multigrammatical framework for knowledge-based digital economy $h [electronic resource] / $c by Igor A. Sheremet.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xiv, 461 p. : $b ill., digital ; $c 24 cm.
505 0 $a Preface -- Introduction -- Sociotechnological systems and associated problems -- Syntax, semantics and mathematical properties of multiset grammars -- Basic algorithmics of multiset grammars and metagrammars -- Resource-consuming sociotechnological systems -- Industrial sociotechnological systems -- Economical sociotechnological systems and economical combinatorics -- Resilience and recovery of sociotechnological systems -- Resource-based games -- Multigrammatical representation of classic problems of operations research -- Interconnections between multiset grammars and models of computation -- Implementation issues and future developments -- Conclusion -- References -- Index -- List of Acronyms.
520 $a This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS) This framework is meant to enable smart operation not only in a "business-as-usual" mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming. The mathematical background needed for MGF, its algorithmics, applications, implementation issues, as well as its nexus with known models from operations research and theoretical computer science areas are considered. The resilience and recovery issues of an STS are studied by applying the MGF toolkit and on paying special attention to the multigrammatical assessment of resilience of energy infrastructures. MGF-represented resource-based games are introduced, and directions for further development are discussed. The author presents multiple applications to business intelligence, critical infrastructure, ecology, economy and industry. This book is addressed to scholars working in the areas of theoretical and applied computer science, artificial intelligence, systems analysis, operations research, mathematical economy and critical infrastructure protection, to engineers developing software-intensive solutions for implementation of the knowledge-based digital economy and Industry 4.0, as well as to students, aspirants and university staff. Foundational knowledge of set theory, mathematical logic and routine operations on data bases is needed to read this book. The content of the monograph is gradually presented, from simple to complex, in a well-understandable step-by-step manner. Multiple examples and accompanying figures are included in order to support the explanation of the various notions, expressions and algorithms.
650 0 $a Expert systems (Computer science) $3 182450
650 0 $a Recursive functions. $3 185632
650 0 $a Industry 4.0. $3 884221
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Knowledge Based Systems. $3 913337
650 2 4 $a Operations Research, Management Science. $3 511451
650 2 4 $a Building Information Modeling. $3 922102
650 2 4 $a Game Theory. $3 737094
650 2 4 $a Formal Languages and Automata Theory. $3 914922
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-13858-4
950 $a Computer Science (SpringerNature-11645)