£97.00

CRC Press Modeling Invasive Alien Plant Species: Fuzzy-Based Uncertainty

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Description

Modelling Invasive Alien Plant Species: Fuzzy Based Uncertainty presents the application of different fuzzy set theory techniques in developing risk assessment models for invasive plant species- those whose introduction and spread outside their natural range threatens local biodiversity. Invasion risk of species is expressed by biological traits which would be considered as the risk factors accompanied with uncertainty and imprecision. The book considers both quantitative and qualitative inputs in modelling the invasive risk by incorporating different mathematical models based on fuzzy set theory operators, interval methods, and fuzzy linguistic operators. The proposed models can be applied for investigating risk of invasive alien plant species in various regions and conditions. Features: Uniquely merges mathematical models with biological expressions. Presents different factor-based models as a case study on the risk of invasive alien plant species. Explains how users can perform primary-level risk assessment through fuzzy modeling techniques. Appropriate for upper-level students, researchers, and practicing professionals, this book shows how conventional approaches such as probability theory can be of limited use to solve issues of uncertainty, and how they fuzzy set theory plays a better role in understanding uncertain system dynamics, such invasive plant modelling. About the Author Dr. H.O.W. Peiris received the B.Sc. (Honors) Degree in Mathematics and Ph.D. degree in Mathematical modeling from the University of Sri Jayewardenepura and University of Colombo, Sri Lanka, respectively. Currently, she is a Lecturer in the Department of Mathematics, Faculty of Natural Science, the Open University of Sri Lanka. She has published several research papers and book chapters in journals and conferences. She received National Research Council (NRC) Merit Award for scientific publications for 2019 for the research paper published in Applied Soft Computing, Elsevier. Her research interests include Fuzzy set theory and Fuzzy uncertainty modeling. Prof. S. Chakraverty has 30 years of experience as a researcher and teacher. Presently he is working in the Department of Mathematics (Applied Mathematics Group), National Institute of Technology Rourkela, Odisha as a Senior (Higher Administrative Grade) Professor. Prior to this, he was with CSIR-Central Building Research Institute, Roorkee, India. After completing Graduation from St. Columba’s College (Ranchi University), his career started at the University of Roorkee (Now, Indian Institute of Technology Roorkee) and did M. Sc. (Mathematics) & M. Phil. (Computer Applications) from there securing the First positions in the university. Dr. Chakraverty received his Ph. D. from IIT Roorkee in 1992. Thereafter he did his post-doctoral research at the Institute of Sound and Vibration Research (ISVR), University of Southampton, U.K. and at the Faculty of Engineering and Computer Science, Concordia University, Canada. He was also a visiting professor at Concordia and McGill universities, Canada, during 1997-1999 and visiting professor of University of Johannesburg, South Africa during 2011-2014. He has authored/co-authored 21 books, published 382 research papers (till date) in journals and conferences, two more books are in Press and two books are ongoing. Recently Prof. Chakraverty is in the list of 2% world scientists (to be more precise within 1%) in the Artificial Intelligence & Image Processing category based on an independent study done by Stanford University, USA scientists where his world rank is 1862 out of 215114 researchers throughout the globe. He is in the Editorial Boards of various International Journals, Book Series and Conferences. Prof. Chakraverty is the Chief Editor of "International Journal of Fuzzy Computation and Modelling" (IJFCM), Inderscience Publisher, Switzerland (http://www.inderscience.com/ijfcm), Associate Editor of "Computatio

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
23 August 2021
Listed Since
11 February 2021

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