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      Soft Numerical Computing in Uncertain Dynamic Systems

      2 in stock

      Firm sale: non returnable item
      SKU 9780128228555 Categories ,
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      Soft Numerical Computing in Uncertain Dynamic Systems is intended for system specialists interested in dynamic systems that operate at different time scales. The book discusses several types of errors and their propagation, covering numerical methods—including convergence an...

      £115.00

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      Description

      Product ID:9780128228555
      Product Form:Paperback / softback
      Country of Manufacture:NL
      Title:Soft Numerical Computing in Uncertain Dynamic Systems
      Authors:Author: Tofigh Allahviranloo, Witold, Ph.D. Pedrycz
      Page Count:388
      Subjects:Artificial intelligence, Artificial intelligence
      Description:Select Guide Rating
      Soft Numerical Computing in Uncertain Dynamic Systems is intended for system specialists interested in dynamic systems that operate at different time scales. The book discusses several types of errors and their propagation, covering numerical methods—including convergence and consistence properties and characteristics—and proving of related theorems within the setting of soft computing. Several types of uncertainty representation like interval, fuzzy, type 2 fuzzy, granular, and combined uncertain sets are discussed in detail. The book can be used by engineering students in control and finite element fields, as well as all engineering, applied mathematics, economics, and computer science students. One of the important topics in applied science is dynamic systems and their applications. The authors develop these models and deliver solutions with the aid of numerical methods. Since they are inherently uncertain, soft computations are of high relevance here. This is the reason behind investigating soft numerical computing in dynamic systems. If these systems are involved with complex-uncertain data, they will be more practical and important. Real-life problems work with this type of data and most of them cannot be solved exactly and easily—sometimes they are impossible to solve. Clearly, all the numerical methods need to consider error of approximation. Other important applied topics involving uncertain dynamic systems include image processing and pattern recognition, which can benefit from uncertain dynamic systems as well. In fact, the main objective is to determine the coefficients of a matrix that acts as the frame in the image. One of the effective methods exhibiting high accuracy is to use finite differences to fill the cells of the matrix.
      Imprint Name:Academic Press Inc
      Publisher Name:Elsevier Science Publishing Co Inc
      Country of Publication:GB
      Publishing Date:2020-08-20

      Additional information

      Weight628 g
      Dimensions156 × 229 × 23 mm