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Towards analytical techniques for sy...

Acosta, Griselda.

Towards analytical techniques for systems engineering applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Towards analytical techniques for systems engineering applicationsby Griselda Acosta, Eric Smith, Vladik Kreinovich.
作者:	Acosta, Griselda.
其他作者:	Smith, Eric.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	x, 101 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Systems engineering.
電子資源:	https://doi.org/10.1007/978-3-030-46413-4
ISBN:	9783030464134$q(electronic bk.)

Towards analytical techniques for systems engineering applications
Acosta, Griselda.

Towards analytical techniques for systems engineering applications[electronic resource] /by Griselda Acosta, Eric Smith, Vladik Kreinovich. - Cham :Springer International Publishing :2020. - x, 101 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.2862198-4182 ;. - Studies in systems, decision and control ;v.3..

Formulation of the Problem -- Analytical Techniques for Describing User Preferences: 80/20 Rule Partially Explains 7 Plus Minus 2 Law -- Analytical Techniques Help Enhance the Results of Data Mining: Case Study of Cow Insemination -- Case When Analytical Techniques Invalidate the Conclusions of Data Mining: Reversed Flynn Effect of Decreasing IQ Test Scores -- Analytical Techniques for Taking into Account Several Aspects of a Designed Systems: Case Study of Computation-Communication Tradeoff -- Analytical Techniques for Testing: Optimal Distribution of Testing Resources Between Different System Levels -- Index.

This book is intended for specialists in systems engineering interested in new, general techniques and for students and practitioners interested in using these techniques for solving specific practical problems. For many real-world, complex systems, it is possible to create easy-to-compute explicit analytical models instead of time-consuming computer simulations. Usually, however, analytical models are designed on a case-by-case basis, and there is a scarcity of general techniques for designing such easy-to-compute models. This book fills this gap by providing general recommendations for using analytical techniques in all stages of system design, implementation, testing, and monitoring. It also illustrates these recommendations using applications in various domains, such as more traditional engineering systems, biological systems (e.g., systems for cattle management), and medical and social-related systems (e.g., recommender systems)

ISBN: 9783030464134$q(electronic bk.)

Standard No.: 10.1007/978-3-030-46413-4doiSubjects--Topical Terms:

182491
Systems engineering.

LC Class. No.: A168 / .A267 2020

Dewey Class. No.: 003

Towards analytical techniques for systems engineering applications
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245 1 0 $a Towards analytical techniques for systems engineering applications $h [electronic resource] / $c by Griselda Acosta, Eric Smith, Vladik Kreinovich.
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505 0 $a Formulation of the Problem -- Analytical Techniques for Describing User Preferences: 80/20 Rule Partially Explains 7 Plus Minus 2 Law -- Analytical Techniques Help Enhance the Results of Data Mining: Case Study of Cow Insemination -- Case When Analytical Techniques Invalidate the Conclusions of Data Mining: Reversed Flynn Effect of Decreasing IQ Test Scores -- Analytical Techniques for Taking into Account Several Aspects of a Designed Systems: Case Study of Computation-Communication Tradeoff -- Analytical Techniques for Testing: Optimal Distribution of Testing Resources Between Different System Levels -- Index.
520 $a This book is intended for specialists in systems engineering interested in new, general techniques and for students and practitioners interested in using these techniques for solving specific practical problems. For many real-world, complex systems, it is possible to create easy-to-compute explicit analytical models instead of time-consuming computer simulations. Usually, however, analytical models are designed on a case-by-case basis, and there is a scarcity of general techniques for designing such easy-to-compute models. This book fills this gap by providing general recommendations for using analytical techniques in all stages of system design, implementation, testing, and monitoring. It also illustrates these recommendations using applications in various domains, such as more traditional engineering systems, biological systems (e.g., systems for cattle management), and medical and social-related systems (e.g., recommender systems)
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