Completely updated for a new edition, this book introduces reliability and risks analysis, for both practicing engineers and engineering students at the undergraduate and graduate levels. Since reliability analysis is a multidisciplinary subject, this book draws together a wide range of topics and presents them in a way that applies to most engineering disciplines.Reliability and Risk Analysis, Second Edition, emphasizes an introduction and explanation of the practical met...

This undergraduate and graduate textbook provides a practical and comprehensive overview of reliability and risk analysis techniques. Written for engineering students and practicing engineers, the book is multi-disciplinary in scope. The new edition has new topics in classical confidence interval estimation; Bayesian uncertainty analysis; models for physics-of-failure approach to life estimation; extended discussions on the generalized renewal process and optimal maintenance; and further m...

Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p

"Examining reliability, availability, and risk analysis and reviewing in probability and statistics essential to understanding reliability methods, this outstanding volume describes day-to-day techniques used by practicing engineers -- discussing important reliability aspects of both components and complex systems. "

This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, ...

Confused by business statistics? Problem solved.Schaum's Outline of Business Statistics helps you understand basic concepts and offers extra practice on topics you'll encounter in your introductory- and intermediate-level courses. With this book, you'll understand and master the basic methods of statistical description, statistical inference, decision analysis, and process control. You will also learn about frequency distributions, histograms and frequency...

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decisi...

Here is a sample chapter from Six Sigma Black Belt Handbook, which offers the best and the latest information to assist you in solving some of the most complex problems imaginable. In this book written by the instructors of the world renowned Motorola University, you'll find valuable advice on how to integrate research and development, manufacturing, human resources, finance, marketing, quality, and customer service goals with their corporate vision, mission and key strategies.

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and...

This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom ...

Reliability, Maintainability and Risk: Practical Methods for Engineers, Eighth Edition, discusses tools and techniques for reliable and safe engineering, and for optimizing maintenance strategies. It emphasizes the importance of using reliability techniques to identify and eliminate potential failures early in the design cycle. The focus is on techniques known as RAMS (reliability, availability, maintainability, and safety-integrity). The book is organized into five parts. Part 1 on reliab...

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncer...