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Soft Computing and Intelligent Systems: Theory and Applications

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TLDR
In this paper, the authors discuss the principles of and their experience with soft computing, an emerging discipline rooted in a group of technologies that aim to exploit the tolerance for imprecision and uncertainty in achieving solutions to complex problems.
Abstract
From the Publisher: Invited researchers from around the world discuss the principles of and their experience with soft computing, an emerging discipline rooted in a group of technologies that aim to exploit the tolerance for imprecision and uncertainty in achieving solutions to complex problems. Within the broad categories of foundations, theory, implications and applications, and future prospects, the 25 studies consider such topics as parallel and distributed architectures and biologically inspired computing, neural networks for identifying nonlinear systems, the knowledge- based adaptation of a neurofuzzy model in the predictive control of a heat exchanger, and toward intelligent machines. The field is so new that the bibliography claims comprehension.

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Is there a need for fuzzy logic

TL;DR: In this paper, fuzzy logic is viewed in a nonstandard perspective and the cornerstones of fuzzy logic-and its principal distinguishing features-are: graduation, granulation, precisiation and the concept of a generalized constraint.
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Toward a perception-based theory of probabilistic reasoning with imprecise probabilities

TL;DR: The perception-based theory of probabilistic reasoning which is outlined in this paper is not in the traditional spirit, but its principal aim is to lay the groundwork for a radical enlargement of the role of natural languages in probability theory and its applications, especially in the realm of decision analysis.
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Competitive spectrum sharing in cognitive radio networks: a dynamic game approach

TL;DR: This paper considers the problem of spectrum sharing among a primary user and multiple secondary users as an oligopoly market competition and uses a noncooperative game to obtain the spectrum allocation for secondary users.
Proceedings ArticleDOI

Toward deep learning software repositories

TL;DR: This work motivate deep learning for software language modeling, highlighting fundamental differences between state-of-the-practice software language models and connectionist models, and proposes avenues for future work, where deep learning can be brought to bear to support model-based testing, improve software lexicons, and conceptualize software artifacts.
Journal ArticleDOI

Review article: A review of soft computing applications in supply chain management

TL;DR: The aim of this paper is to summarise the findings by a systematic review of existing research papers concerning the application of soft computing techniques to supply chain management, such as customer relationship management and reverse logistics.