Forecasting maximum entropy interface de fort hugo (4 resultados)

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  • Idioma: Inglés

    Editorial: IOP Publishing Nov 2022, 2022

    0750339322 / 9780750339322

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 45,98

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    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. Neuware.

  • Idioma: Inglés

    Editorial: Iop Publishing Ltd, 2023

    0750339292 / 9780750339292

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    Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections

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    Condición: Nuevo

    EUR 109,04

    Envío por EUR 13,31 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New. In English.

  • Idioma: Inglés

    Editorial: Iop Publishing Ltd, 2023

    0750339292 / 9780750339292

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Condición: Nuevo

    EUR 140,04

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    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: IOP Publishing Ltd Nov 2022, 2022

    0750339292 / 9780750339292

    • Tapa dura

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 177,10

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    Cantidad disponible: 2 disponibles

    Buch. Condición: Neu. Neuware - This book aims at providing a unifying framework, based on Information Entropy and its maximization, to connect the phenomenology of evolutionary biology, community ecology, financial economics, and statistical physics. This more comprehensive view, besides providing further insight into problems, enables problem-solving strategies by applying proven methods in one discipline to formally similar problems in other areas. The book also proposes a forecasting method for important practical problems in these disciplines and is directed to researchers, students and practitioners working on modelling the dynamics of complex systems. The common thread is how the flux of information both controls and serves to predict the dynamics of complex systems. It is shown how maximizing the Shannon information entropy allows one to infer a central object controlling the dynamics of complex systems, such as ecosystems or markets. The resulting models, which are known as pairwise maximum-entropy models, can be used to infer interactions from data in a wide variety of systems. Here, two examples are analysed in detail. The first is an application to conservation ecology, namely the issue of providing early warning indicators of population crashes of species of trees in tropical forests. The second is about forecasting the market values of firms through evolutionary economics. An interesting lesson is that PME modelling often produces accurate predictions despite not incorporating explicit interaction mechanisms. Key features - Written to be suitable for a broad spectrum of readers and assumes little mathematical specialism. - Includes pedagogical features: Worked examples, case studies and summaries. - The interdisciplinary approach builds bridges between disciplines. - Oriented to solve practical problems. - Includes a combination of analytical derivations and numerical simulations with experiments.…