Controlling epidemics with mathematical and machine learning models [electronic resource] / Abraham Varghese, Eduardo M. Lacap, Jr., Ibrahim Sajath, Kamal Kumar, and Shajidmon Kolamban.
- 作者： Varghese, Abraham, 1977-.
- 其他作者：
- 其他題名：
- Advances in computational intelligence and robotics (ACIR) book series.
- 出版： Hershey, Pennsylvania : IGI Global 2023.
- 叢書名： Advances in computational intelligence and robotics (ACIR) book series
- 主題： Machine learning. , Epidemiology--Mathematical models. , Epidemiological Models. , Epidemiologic Methods. , Machine Learning. , Communicable Diseases--epidemiology. , Electronic books.
- ISBN： 9781799883449 (electronic bk.) 、 1799883434 、 9781799883432
- URL：
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- 一般註：Includes bibliographical references and index. Chapter 1. Epidemiology models -- Chapter 2. The basic reproduction number -- Chapter 3. Basic compartmental models -- Chapter 4. Simulation of SIR model -- Chapter 5. Extended compartmental model -- Chapter 6. Graph theory approach to epidemic study -- Chapter 7. Network and epidemic model -- Chapter 8. Introduction to machine learning -- Chapter 9. Pairing regression model and R programming -- Chapter 10. Adaptive neuro fuzzy inference system for likelihood of admission to ICU for Covid-19 patients. 112年度臺灣學術電子書暨資料庫聯盟採購
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讀者標籤：
- 系統號： 000306530 | 機讀編目格式
館藏資訊
Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians.
摘要註
"The objective of this book is to make mathematical models for epidemical diseases, especially Covid-19, focusing on quarantine, isolation and vaccine effect for the control of the disease and providing simulation of the model to bedone with the help of python/matlab"--
