Controlling epidemics with mathematical and machine learning models:
"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 be done with the help of python/matlab"--
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2023.
|
| Series: | Advances in computational intelligence and robotics (ACIR) book series.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "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 be done with the help of python/matlab"-- |
| Physical Description: | 15 PDFs (269 Seiten) : illustrations Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781799883449 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2023. | |
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 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. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | |a "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 be done with the help of python/matlab"-- |c Provided by publisher. | ||
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 12/08/2022). | ||
| 650 | 0 | |a Epidemiology |x Mathematical models. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 2 | |a Communicable Diseases |x epidemiology. | |
| 650 | 2 | |a Epidemiologic Methods. | |
| 650 | 2 | |a Epidemiological Models. | |
| 650 | 2 | |a Machine Learning. | |
| 653 | |a Classical Regression Model. | ||
| 653 | |a Compartmental Models. | ||
| 653 | |a Continuous Outcomes. | ||
| 653 | |a COVID-19 Patients. | ||
| 653 | |a Epidemiology Models. | ||
| 653 | |a Extended Compartmental Model. | ||
| 653 | |a Graph Theory Approach. | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Network and Epidemic Model. | ||
| 653 | |a Reproduction Number. | ||
| 653 | |a SIR Model Simulation. | ||
| 700 | 1 | |a Kolamban, Shajidmon |d 1983- |e author. | |
| 700 | 1 | |a Kumar, Kamal |d 1980- |e author. | |
| 700 | 1 | |a Lacap, Eduardo M. |d 1982- |e author. | |
| 700 | 1 | |a Sajath, Ibrahim |d 1957- |e author. | |
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| author | Varghese, Abraham, 1977- Kolamban, Shajidmon 1983- Kumar, Kamal 1980- Lacap, Eduardo M. 1982- Sajath, Ibrahim 1957- |
| author_facet | Varghese, Abraham, 1977- Kolamban, Shajidmon 1983- Kumar, Kamal 1980- Lacap, Eduardo M. 1982- Sajath, Ibrahim 1957- |
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| contents | 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. |
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| id | ZDB-98-IGB-00269752 |
| illustrated | Illustrated |
| indexdate | 2025-03-18T14:30:35Z |
| institution | BVB |
| isbn | 9781799883449 |
| language | English |
| oclc_num | 1310646628 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 15 PDFs (269 Seiten) : illustrations Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | IGI Global |
| record_format | marc |
| series | Advances in computational intelligence and robotics (ACIR) book series. |
| series2 | Advances in computational intelligence and robotics (ACIR) book series |
| spelling | Varghese, Abraham, 1977- author. Controlling epidemics with mathematical and machine learning models Abraham Varghese, Eduardo M. Lacap, Jr., Ibrahim Sajath, Kamal Kumar, and Shajidmon Kolamban. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2023. 15 PDFs (269 Seiten) : illustrations text rdacontent electronic isbdmedia online resource rdacarrier Advances in computational intelligence and robotics (ACIR) book series 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. Restricted to subscribers or individual electronic text purchasers. "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 be done with the help of python/matlab"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 12/08/2022). Epidemiology Mathematical models. Machine learning. Communicable Diseases epidemiology. Epidemiologic Methods. Epidemiological Models. Machine Learning. Classical Regression Model. Compartmental Models. Continuous Outcomes. COVID-19 Patients. Epidemiology Models. Extended Compartmental Model. Graph Theory Approach. Network and Epidemic Model. Reproduction Number. SIR Model Simulation. Kolamban, Shajidmon 1983- author. Kumar, Kamal 1980- author. Lacap, Eduardo M. 1982- author. Sajath, Ibrahim 1957- author. IGI Global, publisher. Print version: 1799883434 9781799883432 Advances in computational intelligence and robotics (ACIR) book series. |
| spellingShingle | Varghese, Abraham, 1977- Kolamban, Shajidmon 1983- Kumar, Kamal 1980- Lacap, Eduardo M. 1982- Sajath, Ibrahim 1957- Controlling epidemics with mathematical and machine learning models Advances in computational intelligence and robotics (ACIR) book series. 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. Epidemiology Mathematical models. Machine learning. Communicable Diseases epidemiology. Epidemiologic Methods. Epidemiological Models. Machine Learning. |
| title | Controlling epidemics with mathematical and machine learning models |
| title_auth | Controlling epidemics with mathematical and machine learning models |
| title_exact_search | Controlling epidemics with mathematical and machine learning models |
| title_full | Controlling epidemics with mathematical and machine learning models Abraham Varghese, Eduardo M. Lacap, Jr., Ibrahim Sajath, Kamal Kumar, and Shajidmon Kolamban. |
| title_fullStr | Controlling epidemics with mathematical and machine learning models Abraham Varghese, Eduardo M. Lacap, Jr., Ibrahim Sajath, Kamal Kumar, and Shajidmon Kolamban. |
| title_full_unstemmed | Controlling epidemics with mathematical and machine learning models Abraham Varghese, Eduardo M. Lacap, Jr., Ibrahim Sajath, Kamal Kumar, and Shajidmon Kolamban. |
| title_short | Controlling epidemics with mathematical and machine learning models |
| title_sort | controlling epidemics with mathematical and machine learning models |
| topic | Epidemiology Mathematical models. Machine learning. Communicable Diseases epidemiology. Epidemiologic Methods. Epidemiological Models. Machine Learning. |
| topic_facet | Epidemiology Mathematical models. Machine learning. Communicable Diseases epidemiology. Epidemiologic Methods. Epidemiological Models. Machine Learning. |
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