Titlebook: Intelligent and Soft Computing in Infrastructure Systems Engineering; Recent Advances Kasthurirangan Gopalakrishnan,Halil Ceylan,Nii O. Bo

Ardent

lavish

直言不讳

Pijush Samui,Sarat Kumar Das,T. G. Sitharame been known to fail in achieving efficient or fair allocations. On the other hand, many citizens take the democratic system for granted as they have yet to experience an alternative. In this book the vision we propose is that the potential of democ­ racies has not yet been exhausted, and that optim

Endoscope

e been known to fail in achieving efficient or fair allocations. On the other hand, many citizens take the democratic system for granted as they have yet to experience an alternative. In this book the vision we propose is that the potential of democ­ racies has not yet been exhausted, and that optim

符合规定

Rapid Interpretation of Nondestructive Testing Results Using Neural Networks,operties are complex and either require a significant computational effort and/or frequent operator intervention. Studies are presented that show the power of artificial neural networks to estimate pavement layer properties and allow for capabilities in developing pavement performance curves and for estimating and monitoring remaining life.

嘲笑

MITE

苦笑

Book 2009gic, and Bayesian statistics. Although each one has its separate strengths, the complem- tary nature of these techniques when used in combination (hybrid) makes them a powerful alternative for solving complex problems where conventional mat- matical methods fail. The use of intelligent and soft comp

轻而薄

Extended Kalman Filter and Its Application in Pavement Engineering,t using frequency sweep test data. In both cases, EKF-WGI is shown to provide consistent results that are independent of the seed values for both linear and nonlinear problems. It is believed that EKF-WGI provides an efficient, consistent and robust tool for optimization that has many potential applications.

过分

Probabilistic Inversion: A New Approach to Inversion Problems in Pavement and Geomechanical Engineeertainties can have significant effects on the obtained results. In this chapter, a general probabilistic approach to the solution of the inverse problems is introduced. The approach offers the framework required to obtain uncertainty measures for the solution. To provide the necessary background of