Wallach D., Makowski D., Jones J.W., Brun F. (2014). Working with dynamic crop models: methods, tools and examples for agriculture and environment. 2 ed. Londres (Royaume-Uni) : Academic Press. 487 p.
Titre : | Working with dynamic crop models: methods, tools and examples for agriculture and environment |
Auteurs : | D. Wallach ; D. Makowski ; J.W. Jones ; F. Brun |
Type de document : | Ouvrage |
Mention d'édition : | 2 |
Editeur : | Londres [Royaume-Uni] : Academic Press, 2014 |
ISBN/ISSN/EAN : | 978-0-12-397008-4 |
Format : | 487 p. |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 06 - AGRICULTURE. FORÊTS. PÊCHES ; 6.4 - Production Agricole. Système de ProductionThésaurus IAMM MODELE ; EVALUATION ; MODE DE CULTURE ; SYSTEME DE CULTURE ; CONCEPT ; METHODE ; MODELE DYNAMIQUE ; AGRICULTURE ; SYSTEME DE PRODUCTION ; MODELE DE SIMULATION ; METHODE STATISTIQUE |
Résumé : | This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines. |
Note de contenu : |
SECTION 1: BASICS
Chapter 1. Basics of Agricultural System Models Chapter 2. Statistical Notions Useful for Modeling Chapter 3. The R Programming Language and Software Chapter 4. Simulation with Dynamic System Models SECTION 2: METHODS Chapter 5. Uncertainty and Sensitivity Analysis Chapter 6. Parameter Estimation with Classical Methods (Model Calibration) Chapter 7. Parameter Estimation with Bayesian Methods Chapter 8. Data Assimilation for Dynamic Models Chapter 9. Model Evaluation Chapter 10. Putting It All Together in a Case Study |
Cote : | I03-WAL-2014 |
Exemplaires (1)
Code-barres | Cote | Support | Localisation | Section | Disponibilité |
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27321 | I03-WAL-2014 | Papier | Centre de documentation | Espace Thématique | Disponible |