Mathematical Problems in Engineering

Computational Intelligence in Civil and Hydraulic Engineering


Publishing date
22 Feb 2013
Status
Published
Submission deadline
05 Oct 2012

Lead Editor

1Department of Computer Science and Technology, Zhejiang University of Science & Technology, Hangzhou, China

2Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China

3Marand Faculty of Engineering, University of Tabriz, Tabriz, Iran

4Department of Civil, Construction & Environmental Engineering, Iowa State University, IA, USA

5Computer Engineering Department, Dumlupinar University, Kütahya, Turkey


Computational Intelligence in Civil and Hydraulic Engineering

Description

Computational intelligence (CI) is a set of nature-inspired computational methodologies and approaches to address complex problems of the real-world applications to which traditional methodologies and approaches are ineffective or infeasible. CI methods and techniques, including neural networks, evolutionary computation, and fuzzy logic systems, have rapidly evolved over the last decades, and they have already been applied in various fields of civil and hydraulic engineering.

We invite investigators to contribute original research articles as well as review articles that will stimulate the continuing efforts to research on applications of computational intelligence approaches to solve real-world infrastructure engineering problems. Potential topics include, but are not limited to:

  • Methodologies
    • Evolutionary computation, swarm intelligence
    • Neural networks, support vector machines
    • Fuzzy logic and fuzzy systems
    • Hybrid algorithms
  • Domains of CI applications
    • Civil and hydraulic engineering
    • Geotechnical engineering
    • Transportation engineering
    • Structural design, diagnostics, health monitoring

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2013
  • - Article ID 852875
  • - Research Article

Factors Influencing Quasistatic Modeling of Deformation and Failure in Rock-Like Solids by the Smoothed Particle Hydrodynamics Method

X. W. Tang | Y. D. Zhou | Y. L. Liu
  • Special Issue
  • - Volume 2013
  • - Article ID 416941
  • - Research Article

Combined Data with Particle Swarm Optimization for Structural Damage Detection

Fei Kang | Junjie Li | Sheng Liu
  • Special Issue
  • - Volume 2012
  • - Article ID 383749
  • - Research Article

Inverse Parametric Analysis of Seismic Permanent Deformation for Earth-Rockfill Dams Using Artificial Neural Networks

Xu Wang | Fei Kang | ... | Xin Wang
  • Special Issue
  • - Volume 2012
  • - Article ID 618979
  • - Research Article

Intelligent Risk Assessment for Dewatering of Metro-Tunnel Deep Excavations

X. W. Ye | L. Ran | ... | X. B. Dong
  • Special Issue
  • - Volume 2012
  • - Article ID 712974
  • - Research Article

Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks

Reza Kamyab Moghadas | Kok Keong Choong | Sabarudin Bin Mohd
  • Special Issue
  • - Volume 2012
  • - Article ID 474282
  • - Research Article

Optimal Placement of Passive Energy Dissipation Devices by Genetic Algorithms

Ji-ting Qu | Hong-nan Li
  • Special Issue
  • - Volume 2012
  • - Article ID 829451
  • - Research Article

Combination of Interacting Multiple Models with the Particle Filter for Three-Dimensional Target Tracking in Underwater Wireless Sensor Networks

Xin Wang | Mengxi Xu | ... | Haiyan Shi
  • Special Issue
  • - Volume 2012
  • - Article ID 207318
  • - Research Article

Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer

Yu-Jun Zheng | Hai-Feng Ling | Qiu Guan
  • Special Issue
  • - Volume 2012
  • - Article ID 498690
  • - Research Article

Particle Swarm Optimization Algorithm Coupled with Finite Element Limit Equilibrium Method for Geotechnical Practices

Hongjun Li | Hong Zhong | ... | Xuedong Zhang
  • Special Issue
  • - Volume 2012
  • - Article ID 237693
  • - Research Article

Sludge Bulking Prediction Using Principle Component Regression and Artificial Neural Network

Inchio Lou | Yuchao Zhao
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Impact Factor1.009
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