modeling uncertainty fuzzy logic de celikyilmaz asli (27 resultados)

Paperback. Condición: new. Paperback. The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New.

Condición: New.

Condición: New.

Hardcover. Condición: new. Hardcover. The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New. pp. 450.

Condición: New. This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function. Series: Studies in Fuzziness and Soft Computing. Num Pages: 400 pages, 134 black & white tables, biography. BIC Classification: PBF; PBW; UYQ. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 23. Weight in Grams: 682. . 2010. Softcover reprint of hardcover 1st ed. 2009. Paperback. . . . .

Condición: New. pp. 452.

Condición: New. This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function. Series: Studies in Fuzziness and Soft Computing. Num Pages: 400 pages, 134 black & white tables, biography. BIC Classification: UGC; UYQ. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 25. Weight in Grams: 807. . 2009. Hardback. . . . .

Condición: New. In.

Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon Should I take an umbrella with me Will I be able to find parking near the campus Should I go by bus Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future Should I buy Chevron stock What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed What will be the consequences Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability.

Condición: New. This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function. Series: Studies in Fuzziness and Soft Computing. Num Pages: 400 pages, 134 black & white tables, biography. BIC Classification: PBF; PBW; UYQ. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 23. Weight in Grams: 682. . 2010. Softcover reprint of hardcover 1st ed. 2009. Paperback. . . . . Books ship from the US and Ireland.

Condición: New. This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function. Series: Studies in Fuzziness and Soft Computing. Num Pages: 400 pages, 134 black & white tables, biography. BIC Classification: UGC; UYQ. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 25. Weight in Grams: 807. . 2009. Hardback. . . . . Books ship from the US and Ireland.

Paperback. Condición: Like New. Like New. book.

Paperback. Condición: new. Paperback. The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condición: new. Hardcover. The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon Should I take an umbrella with me Will I be able to find parking near the campus Should I go by bus Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future Should I buy Chevron stock What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed What will be the consequences Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, The only satisfactory description of uncertainty is probability. 400 pp. Englisch.

Condición: New. Print on Demand pp. 450 118 Illus.

Condición: New. Print on Demand pp. 452 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Condición: New. PRINT ON DEMAND pp. 450.

Condición: New. PRINT ON DEMAND pp. 452.