Partial Values

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

The ground is one of the most highly variable of engineering materials. It is therefore not surprising that geotechnical designs depend on local site conditions and local engineering experience. Engineering practices, relating to investigation and design methods site understanding and to safety levels acceptable to society, will therefore vary between different regions.The challenge in geotechnical engineering is to make use of worldwide geotechnical experience, established over many years, to aid in the development and harmonization of geotechnical design codes. Given the significant uncertainties involved, empiricism and engineering

A new edition of a well-known and respected book. This book provides a thorough guide for structural engineers on the use of concrete masonry. The second edition of the Concrete Masonry Designer's Handbook is the only handbook to provide information on all the new CEN TC125 masonry standards, as well as detailed guidance on design to Eurocode 6. Th

The purpose of this book is to explain the philosophy set out in Eurocode 7, the new European code of practice for geotechnical design, and, by means of series of typical examples, to show how this philosophy is used in practice. This book is aimed at: • practising engineers, to assist them to carry out geotechnical designs to Eurocode 7 using the limit state design method and partial factors; • lecturers and students on courses where design to Eurocode 7 is being taught. It is envisaged that practising engineers, using this book to assist them carry out geotechnical designs to Eurocode 7, will have access to the prestandard version of Eurocode 7, ENV 1997 -I, so the authors have concentrated on the main principles and have not provided a commentary on all the clauses. However sufficient detail has been included in the book to enable it to be used on its own by those learning the design principles who may not have access to Eurocode 7. For example, the values of the partial factors and the principal equations given in Eurocode 7 have been included and these are used in the design examples in this book. To assist the reader, the numbering, layout and titles of the chapters closely follow those presented in Eurocode 7.

Statistical Applications for Environmental Analysis and Risk Assessment guides readers through real-world situations and the best statistical methods used to determine the nature and extent of the problem, evaluate the potential human health and ecological risks, and design and implement remedial systems as necessary. Featuring numerous worked examples using actual data and “ready-made” software scripts, Statistical Applications for Environmental Analysis and Risk Assessment also includes: • Descriptions of basic statistical concepts and principles in an informal style that does not presume prior familiarity with the subject • Detailed illustrations of statistical applications in the environmental and related water resources fields using real-world data in the contexts that would typically be encountered by practitioners • Software scripts using the high-powered statistical software system, R, and supplemented by USEPA’s ProUCL and USDOE’s VSP software packages, which are all freely available • Coverage of frequent data sample issues such as non-detects, outliers, skewness, sustained and cyclical trend that habitually plague environmental data samples • Clear demonstrations of the crucial, but often overlooked, role of statistics in environmental sampling design and subsequent exposure risk assessment.

Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.