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Uncertain mathematical models play a crucial role in addressing communication and signal transmission challenges, a concept pioneered by Claude Shannon in 1948. The book emphasizes the importance of formulating precise questions to measure the value of information in reducing uncertainty. It presents a quantitative approach for developing diverse models applicable across various scientific disciplines, highlighting their relevance in statistical physics, thermodynamics, nonlinear physics, and quantum computation. The volume aims to construct models that incorporate probability and fuzzy distributions for broader applications in mathematical sciences.
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Uncertain Mathematical Modeling And Applications, Jatinder Kumar
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- 2014
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