Geo.Engineerings

Daiheng Ni ... 412 pages - Publisher: Butterworth-Heinemann; 1st edition (November 5, 2015)
Language: English - ISBN-10: 012804134X - ISBN-13: 978-0128041345 

Creating Traffic Models is a challenging task because some of their interactions and system components are difficult to adequately express in a mathematical form. Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques provide traffic engineers with the necessary methods and techniques for mathematically representing traffic flow. The book begins with a rigorous but easy to understand exposition of traffic flow characteristics including Intelligent Transportation Systems (ITS) and traffic sensing technologies.

Includes worked out examples and cases to illustrate concepts, models, and theories + Provides modeling and analytical procedures for supporting different aspects of traffic analyses for supporting different flow models + Carefully explains the dynamics of traffic flow over time and space.

From the Back Cover: Concise and readable, Traffic Flow Theory: Characteristics, Experimental Methods and Numerical Techniques incorporates the most current developments in traffic flow modeling techniques for mathematically expressing flow characteristics. The book begins with a rigorous but easy to understand exposition of traffic flow characteristics including Intelligent Transportation Systems (ITS) and traffic sensing technologies. This is followed by self-contained chapters involving traffic flow modeling on a macroscopic, microscopic and picoscopic level. The book’s objective is to establish a theoretical foundation for traffic modeling and simulation at multiple scales, seamlessly within a single system.

Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation.

This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.