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Titlebook: Handbook of Visual, Experimental and Computational Mathematics ; Bridges through Data Bharath Sriraman Living reference work 2025Latest edi

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發(fā)表于 2025-3-21 17:38:55 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Handbook of Visual, Experimental and Computational Mathematics
副標(biāo)題Bridges through Data
編輯Bharath Sriraman
視頻videohttp://file.papertrans.cn/423/422355/422355.mp4
概述Contains chapters curated by experts in the domains of visual, computational and experimental mathematics.Covers visual/computational proofs of old and contemporary results.Includes computational and
圖書封面Titlebook: Handbook of Visual, Experimental and Computational Mathematics ; Bridges through Data Bharath Sriraman Living reference work 2025Latest edi
描述.This Handbook examines the interaction of visual, computational and experimental approaches in modern mathematics through its interaction with data. Experimental mathematics made the first bold foray into using computational techniques to solve theoretical problems via data saturation and visualizations. Since computing power and powerful algorithms have changed the landscape of visualizing and doing mathematics, different sections of the book provide an access to data driven scenarios in contemporary society. These include data driven modeling in mathematical epidemiology; visualization of information patterns; climate science and ecology.? ?Other sections include chapters which provide visualizations of abstract (theoretical) mathematics; and the application of mathematics in areas such as sports analytics. In this Handbook, the interaction of visualization, computation and experimental mathematics is covered with forays into problems at the intersection of biology, sports, epidemiology, physics, information theory and mathematics both pure and applied. The book is of interest to graduate students of mathematics, computer science, information theory and the sciences as well as u
出版日期Living reference work 2025Latest edition
關(guān)鍵詞Computational mathematics; Data visualization; Experimental methods; Statistical Data; Data analytics
doihttps://doi.org/10.1007/978-3-030-93954-0
isbn_ebook978-3-030-93954-0
The information of publication is updating

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Using Markov Chains in Predictive Modeling of Sports,t times. Among many mathematically inspired sports ranking systems, linear algebra methods are among the most elegant and simple. This chapter highlights several research projects which apply Markov chains in a variety of ways to predict the future results of MLB, NCAA baseball, and NHL hockey.
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Computing the Degree of Black-Box Polynomials, with Applications,. evaluations of the polynomial or its derivatives, the knowledge of basic bounds for the size of the coefficients, and classical properties of complex-valued polynomials. We apply the techniques to discrete optimization problems.
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