Автор: Alfio Quarteroni Название: Numerical Models for Differential Problems ISBN: 3319493159 ISBN-13(EAN): 9783319493152 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the basic concepts for the numerical modelling of partial differential equations. It details algorithmic and computer implementation aspects and provides a number of easy-to-use programs.
Автор: Pundir Название: Numerical Methods in Science and Engineering (PB) ISBN: 9386217643 ISBN-13(EAN): 9789386217646 Издательство: CBS India Рейтинг: Цена: 6218.00 р. Наличие на складе: Нет в наличии.
Автор: Platen Название: Numerical Solution of Stochastic Differential Equations with Jumps in Finance ISBN: 3642120571 ISBN-13(EAN): 9783642120572 Издательство: Springer Рейтинг: Цена: 12717.00 р. 18167.00-30% Наличие на складе: Есть (1 шт.) Описание: It presents many new results on higher-order methods for scenario and Monte Carlo simulation, including implicit, predictor corrector, extrapolation, Markov chain and variance reduction methods, stressing the importance of their numerical stability.
Автор: Burden Annette, Burden Richard, Faires J. Douglas Название: Numerical analysis ISBN: 1305253663 ISBN-13(EAN): 9781305253667 Издательство: Cengage Learning Рейтинг: Цена: 9423.00 р. 13462.00-30% Наличие на складе: Есть (1 шт.) Описание: Introduces readers to the theory and application of modern numerical approximation techniques. Providing an accessible treatment that only requires a calculus prerequisite, the authors explain how, why, and when approximation techniques can be expected to work - and why, in some situations, they fail.
Описание: This is a lively, narrative history of the world`s great weather tragedies - the greatest storms in history - and the epic quest by pioneering scientists to figure out how to accurately predict the weather. It tells the story of the development of meterology from the time of Aristotle up to current-day breakthroughs in weather prediction.
Описание: Climate forecasts show the potential to improve agriculture's ability to withstand climate shocks, but it is still uncertain how farmers will use this data in crop management decisions plus whether doing so will profit them. This volume introduces the most commonly used forecasting strategies in agriculture, like probability forecasting, real-time forecasting and ultra-short distance forecasting. These determine the pattern of planting dates and crop varieties, the latter being more common where more extensive weather forecasting methods exist. Hybrid strategies usually use more input elements (such as crop varieties) to define the strategy (such as sowing period). Production estimates indicate that, in most cases, using forecasted values can increase production with relatively minimal loss.The impact depends on the nature of actual rainy season, the forecast accuracy and the kind of response. In wet years, with the consolidation of the policy and accurate forecast, the positive response will be higher. This proves that climate prediction can help farmers acclimatize to climate variability, particularly to help them take advantage of the expected favorable conditions. The realization of possible advantages is related to the context of greater variety selection and enhanced selection. Even so, modern advances in weather modeling have improved the ability to accurately forecast rainfall through dynamic forecasting and statistical techniques.
Автор: John M. Stewart Название: Python for Scientists ISBN: 1316641236 ISBN-13(EAN): 9781316641231 Издательство: Cambridge Academ Рейтинг: Цена: 5067.00 р. Наличие на складе: Поставка под заказ.
Описание: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.
Автор: Taras Gerya Название: Introduction to Numerical Geodynamic Modelling ISBN: 1107143144 ISBN-13(EAN): 9781107143142 Издательство: Cambridge Academ Рейтинг: Цена: 10611.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The second edition of this popular introduction to numerical geodynamic modelling theory and applications features four new chapters. Based on the author`s experience of teaching the material, and including practical exercises and MATLAB (R) examples, this user-friendly resource encourages students and researchers to experiment with geodynamic models.
Numerical simulation is a technique of major importance in various technical and scientific fields. Whilst engineering curricula now include training courses dedicated to it, numerical simulation is still not well-known in some economic sectors, and even less so among the general public.
Simulation involves the mathematical modeling of the real world, coupled with the computing power offered by modern technology. Designed to perform virtual experiments, digital simulation can be considered as an "art of prediction".
Embellished with a rich iconography and based on the testimony of researchers and engineers, this book shines a light on this little-known art. It is the second of two volumes and gives examples of the uses of numerical simulation in various scientific and technical fields: agriculture, industry, Earth and universe sciences, meteorology and climate studies, energy, biomechanics and human and social sciences.
Описание: Lewis Fry Richardson dreamt that scientific weather prediction would become a practical reality. This book, first published in 2006, tells the story of Richardson`s trial forecast, and the fulfilment of his dream of practical numerical weather forecasting. It will appeal to everyone in numerical weather forecasting, from researchers and graduate students to professionals.
Автор: Olafsson, Haraldur Название: Olafsson-Uncertainties in Numerical Weather Prediction ISBN: 0128154918 ISBN-13(EAN): 9780128154915 Издательство: Elsevier Science Рейтинг: Цена: 17854.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides a general knowledge of all aspects of uncertainties in the weather prediction models in a single, easy to use reference. Uncertainties in Numerical Weather Prediction illustrates the particular uncertainties in observations and data assimilation, as well as the errors associated with the numerical integration methods. Stochastic methods in parameterisation of subgrid processes are also assessed, as well as uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer. Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts.
This is an essential work for anyone wanting to improve the accuracy of weather and climate forecasting, or developing tools to enhance the quality of such forecasts.
Provides a comprehensive overview of the state of numerical weather prediction at spatial scales, from hundreds of meters, to thousands of kilometers
Focuses on short-term 1-15 day atmospheric predictions, with some coverage appropriate for longer-term forecasts
Includes references to climate prediction models to allow applications of these techniques for climate simulations
Автор: Hackbusch Название: Tensor Spaces and Numerical Tensor Calculus ISBN: 3642280269 ISBN-13(EAN): 9783642280269 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Special numerical techniques are already needed to deal with nxn matrices for large n.Tensor data are of size nxnx...xn=n^d, where n^d exceeds the computer memory by far. They appear for problems of high spatial dimensions. Since standard methods fail, a particular tensor calculus is needed to treat such problems. The monograph describes the methods how tensors can be practically treated and how numerical operations can be performed. Applications are problems from quantum chemistry, approximation of multivariate functions, solution of pde, e.g., with stochastic coefficients, etc. ?
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