Intelligent and Soft Computing in Infrastructure Systems Engineering

Recent Advances

  • Kasthurirangan Gopalakrishnan
  • Halil Ceylan
  • Nii O. Attoh-Okine

Part of the Studies in Computational Intelligence book series (SCI, volume 259)

Table of contents

  1. Front Matter
  2. Sunghwan Kim, Kasthurirangan Gopalakrishnan, Halil Ceylan
    Pages 47-66
  3. A. Hilmi Lav, A. Burak Goktepe, M. Aysen Lav
    Pages 67-106
  4. Bor-Wen Tsai, John T. Harvey, Carl L. Monismith
    Pages 205-238
  5. Rongzong Wu, Jae Woong Choi, John T. Harvey
    Pages 239-253
  6. Pijush Samui, Sarat Kumar Das, T. G. Sitharam
    Pages 305-323
  7. Back Matter

About this book

Introduction

The use of intelligent and soft computing techniques in the field of geomechanical and pavement engineering has steadily increased over the past decade owing to their ability to admit approximate reasoning, imprecision, uncertainty and partial truth. Since real-life infrastructure engineering decisions are made in ambiguous environments that require human expertise, the application of soft computing techniques has been an attractive option in pavement and geomechanical modeling. The objective of this carefully edited book is to highlight key recent advances made in the application of soft computing techniques in pavement and geomechanical systems. Soft computing techniques discussed in this book include, but are not limited to: neural networks, evolutionary computing, swarm intelligence, probabilistic modeling, kernel machines, knowledge discovery and data mining, neuro-fuzzy systems and hybrid approaches. Highlighted application areas include infrastructure materials modeling, pavement analysis and design, rapid interpretation of nondestructive testing results, porous asphalt concrete distress modeling, model parameter identification, pavement engineering inversion problems, subgrade soils characterization, and backcalculation of pavement layer thickness and moduli. Researchers and practitioners engaged in developing and applying soft computing and intelligent systems principles to solving real-world infrastructure engineering problems will find this book very useful. This book will also serve as an excellent state-of-the-art reference material for graduate and postgraduate students in transportation infrastructure engineering.

Keywords

Racter data mining evolution evolutionary computation fuzzy system kernel knowledge knowledge discovery modeling neural network swarm intelligence

Editors and affiliations

  • Kasthurirangan Gopalakrishnan
    • 1
  • Halil Ceylan
    • 2
  • Nii O. Attoh-Okine
    • 3
  1. 1.Dept. of Civil, Constr. & Env. Engg.Iowa State UniversityAmesUSA
  2. 2.Dept. of Civil, Constr. & Env. Engg.Iowa State UniversityAmesUSA
  3. 3.Dept. of Civil and Environmental EngineeringUniversity of DelawareNewarkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-04586-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-04585-1
  • Online ISBN 978-3-642-04586-8
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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