Fuzzy Mathematics, Graphs, and Similarity Measures provides a solid foundation in core analytical tracks of mathematics of uncertainty, from fuzzy mathematics to graphs and similarity measures with applications in a range of timely cases studies and world challenges. Following a full grounding in fuzzy graph indices, connectivity in fuzzy graph structures, lattice isomorphisms, and similarity measures, the book applies these models in analyzing world challenges, from human trafficking to modern slavery, global poverty, global hunger, homelessness, biodiversity, extinction, terrorism and bioterrorism, pandemics, and climate change.
Connections and constructive steps forward are tied throughout to UN Sustainable Development Goals (SDGs). The authors demonstrate and instruct readers in applying techniques from mathematics of uncertainty in examining issues where accurate data is impossible to obtain. In addition to a diverse range of cases studies, exercises reinforce key concepts in each chapter, and an online instructor’s manual supports teaching across a range of course contexts.
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Dr. John N. Mordeson (1934-2025) was Professor Emeritus of Mathematics at Creighton University. He received his B.S., M.S., and Ph. D from Iowa State University. He was a member of Phi Kappa Phi, and published over 24 books and 270 journal articles. He was on the editorial board of numerous journals, and served as an external examiner of PhD candidates from various countries. He refereed for numerous journals and granting agencies, and was particularly interested in applying mathematics of uncertainty to combat global problems.
Dr. Sunil Mathew is Associate Professor in the Department of Mathematics at NIT, Calicut, India. He received his Masters from St. Joseph's College, Devagiri, in Calicut, and PhD from the National Institute of Technology, Calicut in the area of Fuzzy Graph Theory. He has published over 125 research papers and written 10 books. He is a member of several academic bodies and associations. He is an editor and reviewer of several international journals. He has experience of more than 20 years in teaching and research, and his current research topics include fuzzy graph theory, bio-computational modeling, graph theory, fractal geometry, and chaos.
Fuzzy Mathematics, Graphs, and Similarity Measures provides a solid foundation in core analytical tracks of mathematics of uncertainty, from fuzzy mathematics to graphs and similarity measures, with application to a range of timely cases studies and world challenges. Following a full grounding in fuzzy graph indices, connectivity in fuzzy graph structures, lattice isomorphisms, and similarity measures, the book applies these models in analyzing world challenges, from human trafficking to modern slavery, global poverty, global hunger, homelessness, biodiversity, extinction, terrorism and bioterrorism, pandemics, and climate change. Connections and constructive steps forward are tied throughout to UN Sustainable Development Goals (SDGs). The authors demonstrate and instruct readers in applying techniques from mathematics of uncertainty in examining issues where accurate data is impossible to obtain. In addition to a diverse range of cases studies, exercises reinforce key concepts in each chapter, and an online instructor’s manual supports teaching across a range of course contexts.
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