Controlling Epidemics With Mathematical And Machine Learning Models

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Controlling Epidemics With Mathematical and Machine Learning Models

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.
Design and Control Advances in Robotics

Robotics plays a pivotal role in many domains such as industry and medicine. Robots allow for increased safety, production rates, accuracy, and quality; however, robots must be well designed and controlled to achieve the required performance. The design and control of robotics involve many varying disciplines, such as mechanical engineering, electronics, and automation, and must be further studied to ensure the technology is utilized appropriately. Design and Control Advances in Robotics considers the most recent applications and design advances in robotics and highlights the latest developments and applications within the field of robotics. Covering key topics such as deep learning, machine learning, programming, automation, and control advances, this reference work is ideal for engineers, computer scientists, industry professionals, academicians, practitioners, scholars, researchers, instructors, and students.
Modeling, Control and Drug Development for COVID-19 Outbreak Prevention

This book is well-structured book which consists of 31 full chapters. The book chapters' deal with the recent research problems in the areas of modeling, control and drug development, and it presents various techniques of COVID-19 outbreak prevention modeling. The book also concentrates on computational simulations that may help speed up the development of drugs to counter the novel coronavirus responsible for COVID-19. This is an open access book.