商品描述
This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.
商品描述(中文翻譯)
本書介紹了旨在建模和提取個人聯絡網絡信息的算法和工具，這些網絡代表了在某一群體中哪些個體彼此之間有實際接觸。作者基於他們在 COVID-19 大流行期間進行的研究開發了這些工具，目的是為了改善未來對疫情的應對。本書提供了在群體中建模感染傳播的方法。作者解釋了如何利用疫情模型來戰略性地分配疫苗並最小化病毒的擴散。本書展示了如何利用進化計算、圖壓縮和網絡歸納來管理疫情所帶來的問題。
作者簡介
James Alexander Hughes, Ph.D., is a Professor in the Department of Computer Science at St. Francis Xavier University. He received his Ph.D. from the University of Western Ontario. His research interests include machine learning, artificial intelligence, evolutionary computation, artificial neural networks, mathematical modelling, brain connectivity, and other real world applications.Sheridan Houghten, Ph.D., is a Professor in the Department of Computer Science at Brock University. She received her Ph.D. from Concordia University. Her research interests include combinatorial optimization, computational intelligence, and algorithms, with various application areas including bioinformatics, graphs, and coding theory.Michael Dubé is a Ph.D. student at the University of Guelph. He earned his Master's degree from Brock University. His thesis investigated epidemic modeling, simulation, and deployment of vaccination strategies on personal contact networks using evolutionary computation.Matthew Stoodley, Ph.D., is a Senior Bioinformatics Analyst at the University Health Network in Toronto. He received his Ph.D. from the University of Guelph. His interest lies in designing effective solutions for complex problems using computational analysis of large biological datasets. Daniel Ashlock, Ph.D., was the Chair of the Department of Mathematics and Statistics at the University of Guelph. He authored over 300 articles and several books. His primary research areas were evolutionary computation, bioinformatics, mathematical biology, and graph theory, Joseph Alexander Brown, Ph.D., is an Assistant Teaching Professor at Thompson Rivers University. He earned his Ph.D. from the University of Guelph. His research interests include evolutionary computation, computational creativity, computational intelligence, game design, game theory, and bioinformatics. Wendy Ashlock, Ph.D., is the Chief Data Scientist at Ashlock and McGuinness Consulting, Inc. She earned her Ph.D. from York University. She is an expert in applying computational intelligence and machine learning to bioinformatics.
作者簡介(中文翻譯)
詹姆斯·亞歷山大·休斯（James Alexander Hughes），博士，是聖法蘭西斯·澤維爾大學計算機科學系的教授。他在西安大略大學獲得博士學位。他的研究興趣包括機器學習、人工智慧、進化計算、人工神經網絡、數學建模、大腦連接性及其他現實世界應用。
謝里丹·霍亨（Sheridan Houghten），博士，是布洛克大學計算機科學系的教授。她在康考迪亞大學獲得博士學位。她的研究興趣包括組合優化、計算智能和算法，應用領域涵蓋生物信息學、圖論和編碼理論。
邁克爾·杜貝（Michael Dubé）是圭爾夫大學的博士生。他在布洛克大學獲得碩士學位。他的論文研究了流行病建模、模擬及在個人接觸網絡上使用進化計算的疫苗接種策略部署。
馬修·斯圖德利（Matthew Stoodley），博士，是多倫多大學健康網絡的高級生物信息學分析師。他在圭爾夫大學獲得博士學位。他的興趣在於利用計算分析大型生物數據集來設計有效的解決方案以應對複雜問題。
丹尼爾·阿什洛克（Daniel Ashlock），博士，曾任圭爾夫大學數學與統計系主任。他撰寫了超過300篇文章和幾本書籍。他的主要研究領域包括進化計算、生物信息學、數學生物學和圖論。
約瑟夫·亞歷山大·布朗（Joseph Alexander Brown），博士，是湯普森河大學的助理教學教授。他在圭爾夫大學獲得博士學位。他的研究興趣包括進化計算、計算創造力、計算智能、遊戲設計、遊戲理論和生物信息學。
溫迪·阿什洛克（Wendy Ashlock），博士，是阿什洛克與麥金尼斯顧問公司的首席數據科學家。她在約克大學獲得博士學位。她是將計算智能和機器學習應用於生物信息學的專家。
