Journal of Soft Computing in Civil Engineering

ISO Abbreviation:

J. Soft Comput. Civ. Eng.


Journal Metrics

Acceptance Rate: 42%

 Review Speed: 76 days


Publication Start Year: 2017

No. of Citations (WOS): 39

No. of Citations (Scopus): 57

Scopus h-index: 5

No. of Citations (Google Scholar): 126

Google Scholar h-index: 6

Google Scholar i-10index: 4

Issue Per Year: 4

No. of Volumes: 3

No. of Issues: 8

No. of Articles: 61

No. of Indexing Databases: 3

No. of Reviewers: 458

No. of Contributors: 136

Contributing Countries: 16


Article View: 71,575

PDF Download: 30,661

View Per Article: 1173.36

PDF Download Per Article: 502.64




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The Journal of Soft Computing in Civil Engineering (SCCE) is an international open-access journal (online) published quarterly by Pouyan Press which was founded in 2016. The idea behind soft computing is to model the cognitive behavior of human mind. Soft computing is the foundation of conceptual intelligence in machines. Unlike hard computing, soft computing is tolerant of imprecision, uncertainty, partial truth, and approximation. Soft computing aims to surmount NP-complete problems, uses inexact methods to give useful but inexact answers to intractable problems, and also it is well suited for real world problems where ideal models are not available. Today, soft computing algorithms are becoming important classes of efficient tools for developing intelligent systems and providing solutions to complicated civil engineering problems.

The focus of this journal is on applications of soft computing methods in civil engineering. Domains of applications include structural engineering, design, diagnostics, and health monitoring, hydraulic engineering, geotechnical engineering, transportation engineering, environmental engineering, coastal and ocean engineering and construction management. Articles submitted to this journal could also be concerned about the most significant recent developments on the topics of soft computing and its application in civil engineering. The journal also provides a forum where civil engineering researchers can obtain information on relevant new developments in optimization. We encourage the submission of articles that make a genuine soft computing contribution to a challenging civil engineering problem.


Top Cited (Scopus)

Artificial neural networks for construction management: A review

Using of backpropagation neural network in estimating of compressive strength of waste concrete

Comparison study of soft computing approaches for estimation of the non-ductile RC joint shear strength

No-deposition sediment transport in sewers using of gene expression programming

Development of intelligent systems to predict diamond wire saw performance

Current Issue: Volume 3, Issue 2 - Serial Number 8, Spring 2019, Pages 1-100 

Regular Article

1. Neural Network based model to Estimate Dynamic Modulus E* for mixtures in Costa Rica

Pages 1-15

Fabricio Leiva-Villacorta; Adriana Vargas-Nordcbeck

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