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Towards Discrete Interval, Set, and Fuzzy Computations

机译:走向离散区间,集合和模糊计算

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摘要

In many applications, we know the function f(x1,...,xn), we know the intervals [xi] of possible values of each quantity xi, and we are interested in the range of possible values of y=f(x1,...,xn); this problem is known as the problem of interval computations. In other applications, we know the function f(x1,...,xn), we know the fuzzy sets Xi that describe what we know about each quantity xi, and we are interested in finding the fuzzy set Y corresponding to the quantity y=f(x1,...,xn); this problem is known as the problem of fuzzy computations. There are many efficient algorithms for solving these problems; however, most of these algorithms implicitly assume that each quantity xi can take any real value within its range. In practice, some quantities are discrete: e.g., xi can describe the number of people. In this paper, we provide feasible algorithms for interval, set, and fuzzy computations for such discrete inputs.
机译:在许多应用中,我们知道函数f(x1,...,xn),我们知道每个量xi的可能值的间隔[xi],并且我们对y = f(x1)的可能值的范围感兴趣,...,xn);这个问题被称为区间计算问题。在其他应用程序中,我们知道函数f(x1,...,xn),我们知道描述每个量xi的模糊集Xi,并且对找到与量y对应的模糊集Y感兴趣。 = f(x1,...,xn);这个问题被称为模糊计算问题。有许多有效的算法可以解决这些问题。然而,大多数这些算法都隐含地假设每个量xi可以取其范围内的任何实数值。实际上,一些数量是离散的:例如,xi可以描述人数。在本文中,我们为此类离散输入的区间,集合和模糊计算提供了可行的算法。

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