{"product_id":"an-introduction-to-fuzzy-set-theory-and-fuzzy-logic-2-e","title":"An Introduction to Fuzzy Set Theory and Fuzzy Logic, 2\/e","description":"\u003cp\u003e\u003cspan style=\"text-decoration: underline;\"\u003e\u003cstrong\u003eDETAILS :\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eAuthor : by Chander Mohan\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003ePublisher ‏ : ‎ Viva Books\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eISBN-10 ‏ : ‎ 938715369X \u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eISBN-13 ‏ : ‎ 978-9387153691\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eHardcover : 372 pages\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eItem Weight ‏ : ‎ 850 g\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cspan style=\"text-decoration: underline;\"\u003e\u003cstrong\u003eABOUT THE BOOK\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"1\"\u003e\u003cb data-path-to-node=\"1\" data-index-in-node=\"0\"\u003eAn Introduction to Fuzzy Set Theory and Fuzzy Logic (Second Edition)\u003c\/b\u003e, authored by the distinguished applied mathematician Dr. Chander Mohan, is a highly structured, mathematically rigorous textbook. Published by \u003cb data-path-to-node=\"1\" data-index-in-node=\"212\"\u003eS. Chand Publishing\u003c\/b\u003e, this volume serves as an essential guide for senior undergraduate and postgraduate students of Computer Science, Information Technology, Applied Mathematics, and Engineering. The core philosophy of this text centers on \u003cb data-path-to-node=\"1\" data-index-in-node=\"452\"\u003ehandling epistemic uncertainty\u003c\/b\u003e—proving that real-world human reasoning and complex engineering challenges cannot always be confined to classic binary logic (true\/false or 1\/0), but must instead be modeled using degrees of truth ranging continuously between 0 and 1.\u003c\/p\u003e\n\u003cp data-path-to-node=\"2\"\u003eThe book is structurally organized into a progressive mathematical framework that bridges abstract set theory with practical computational engineering. Dr. Mohan avoids dense, unapproachable jargon, systematically laying down the mechanics of fuzzy systems through clear, scannable steps:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli data-path-to-node=\"3,0,0\"\u003e\n\u003cb data-path-to-node=\"3,0,0\" data-index-in-node=\"0\"\u003eClassical Sets vs. Fuzzy Sets:\u003c\/b\u003e Transitioning from crisp binary boundaries to flexible fuzzy membership functions (\u003cspan class=\"math-inline\" data-math=\"\\mu_A(x) \\in [0, 1]\" data-index-in-node=\"114\"\u003e$\\mu_A(x) \\in [0, 1]$\u003c\/span\u003e).\u003c\/li\u003e\n\u003cli data-path-to-node=\"3,1,0\"\u003e\n\u003cb data-path-to-node=\"3,1,0\" data-index-in-node=\"0\"\u003eFuzzy Relations and Operations:\u003c\/b\u003e Exploring fuzzy intersections (t-norms), unions (t-conorms), and the extension principle that allows standard mathematical operations to be applied to fuzzy numbers.\u003c\/li\u003e\n\u003cli data-path-to-node=\"3,2,0\"\u003e\n\u003cb data-path-to-node=\"3,2,0\" data-index-in-node=\"0\"\u003eFuzzy Logic and Approximate Reasoning:\u003c\/b\u003e Formulating linguistic variables, fuzzy propositions, and multi-valued implication rules.\u003c\/li\u003e\n\u003cli data-path-to-node=\"3,3,0\"\u003e\n\u003cb data-path-to-node=\"3,3,0\" data-index-in-node=\"0\"\u003eFuzzy Inference Systems (FIS):\u003c\/b\u003e Detailing the exact architectonic layout of Mamdani and Sugeno fuzzy inference methods, mapping out how real-world inputs are fuzzified, processed via a rule base, and defuzzified into crisp actions.\u003c\/li\u003e\n\u003cli data-path-to-node=\"3,4,0\"\u003e\n\u003cb data-path-to-node=\"3,4,0\" data-index-in-node=\"0\"\u003eApplications:\u003c\/b\u003e Reviewing the functional application of fuzzy logic in automated control systems, pattern recognition, decision-making algorithms, and artificial intelligence.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cspan style=\"text-decoration: underline;\"\u003e\u003cstrong\u003eABOUT THE AUTHOR\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"9\"\u003eDr. Chander Mohan is an elite Indian academician, research mathematician, and former Professor and Head of the Department of Mathematics at the Indian Institute of Technology (IIT) Roorkee. With a career spanning over four decades, his research footprint covers optimization techniques, fuzzy systems, and evolutionary computing, making him a highly respected pioneer in the South Asian computational mathematics space.\u003c\/p\u003e\n\u003cp data-path-to-node=\"10\"\u003eDr. Mohan’s authorial and pedagogical style is extraordinarily lucid, analytical, and derivation-centric. Writing with the logical precision of a veteran IIT professor, he presents every concept alongside worked-out numerical examples, proofs, and graphical representations of membership curves. He actively strips away speculative computing fluff to deliver a clear, balanced textbook that provides students with the foundational mathematical proofs required to build reliable automated software systems.\u003c\/p\u003e","brand":"Viva Books Private Limited","offers":[{"title":"Default Title","offer_id":52033364099370,"sku":"VASY-B0779RXVFC","price":45.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0693\/1218\/4618\/files\/61fJlJiaPPL._SL1168_77893880-344c-4777-879b-533cd909467d.jpg?v=1783050445","url":"https:\/\/crazyshelf.com\/products\/an-introduction-to-fuzzy-set-theory-and-fuzzy-logic-2-e","provider":"Crazyshelf.com","version":"1.0","type":"link"}