國立虎尾科技大學 |

Artificial Intelligence for COVID-19

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Artificial Intelligence for COVID-19/ edited by Diego Oliva, Said Ali Hassan, Ali Mohamed.
其他作者:	Mohamed, Ali.
面頁冊數:	X, 594 p. 268 illus., 250 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data Engineering. -
電子資源:	https://doi.org/10.1007/978-3-030-69744-0
ISBN:	9783030697440

Artificial Intelligence for COVID-19
Artificial Intelligence for COVID-19[electronic resource] /edited by Diego Oliva, Said Ali Hassan, Ali Mohamed. - 1st ed. 2021. - X, 594 p. 268 illus., 250 illus. in color.online resource. - Studies in Systems, Decision and Control,3582198-4190 ;. - Studies in Systems, Decision and Control,27.

Simulation of the relation between the number of COVID-19 death cases as a result of the number of handwashing facilities by using artificial intelligence -- Big data and big data analytics for COVID-19 epidemic -- Big data in COVID-19 assistance – Concepts, motivations, advances and applications in real-world -- Two Layer Hybrid Scheme of IMO and PSO for Optimization of Local Aligner: COVID-19 as a case study -- Factors affecting medical mask purchase decision in COVID-19 pandemic -- Classification approach for COVID-19 gene based on Harris hawks optimization. .

This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations. .

ISBN: 9783030697440

Standard No.: 10.1007/978-3-030-69744-0doiSubjects--Topical Terms:

1226308
Data Engineering.

LC Class. No.: Q342

Dewey Class. No.: 006.3

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