Cognitive Intelligence With Neutrosophic Statistics In Bioinformatics

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Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics

Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics
Author :
Publisher : Elsevier
Total Pages : 495
Release :
ISBN-10 : 9780323994576
ISBN-13 : 0323994571
Rating : 4/5 (571 Downloads)

Book Synopsis Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics by : Florentin Smarandache

Download or read book Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics written by Florentin Smarandache and published by Elsevier. This book was released on 2023-02-11 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown. Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data. Introduces the field of neutrosophic statistics and how it can solve problems working with indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data Presents various applications of neutrosophic statistics in the fields of bioinformatics, medicine, cognitive science and agriculture Provides practical examples and definitions of neutrosophic statistics in relation to the various types of indeterminacies


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