Soil-Moisture Constants and Their Variation (Classic Reprint)
Soil-Moisture Constants and Their Variation (Classic Reprint)

Author: Walter M. Broadfoot

Publisher: Forgotten Books

Published: 2018-03-18

Total Pages: 34

ISBN-13: 9780364844458

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Excerpt from Soil-Moisture Constants and Their Variation This paper summarizes the data gathered in the library and the field. The authors believe that it may be a useful reference for other researchers. For students, it may illustrate the fact that soil-moisture constants, far from being fixed, vary considerably with the physical condition of the soil. Some explanation is due of the procedure followed in compiling the information, together with some precautions as to its use. The data are from 901 samples of surface soil and 400 samples of subsoil. Data from published sources were combined with those obtained in studies at the Vicksburg Research Center. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Handbook of Probabilistic Models
Handbook of Probabilistic Models

Author: Pijush Samui

Publisher: Butterworth-Heinemann

Published: 2019-10-05

Total Pages: 590

ISBN-13: 0128165464

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Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. Explains the application of advanced probabilistic models encompassing multidisciplinary research Applies probabilistic modeling to emerging areas in engineering Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems