Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model

Autor: Danial Mohammadzadeh S., Seyed-Farzan Kazemi, Amir Mosavi, Ehsan Nasseralshariati, Joseph H. M. Tah

Publikováno v: Infrastructures, Vol 4, Iss 2, p 26 (2019)

In construction projects, estimation of the settlement of fine-grained soils is of critical importance, and yet is a challenging task. The coefficient of consolidation for the compression index (Cc) is a key parameter in modeling the settlement of fi

Externí odkaz: https://doaj.org/article/351c588604984fac9f4123948aa81d4c

Prediction of remaining service life of pavement using an optimized support vector machine (case study of Semnan–Firuzkuh road)

Autor: Shahaboddin Shamshirband, Amir Mosavi, Pouria Hajikhodaverdikhan, Nader Karballaeezadeh, Danial Mohammadzadeh S., Kwok Wing Chau

Publikováno v: Engineering Applications of Computational Fluid Mechanics, Vol 13, Iss 1, Pp 188-198 (2019)
Engineering Applications of Computational Fluid Mechanics

Accurate prediction of the remaining service life (RSL) of pavement is essential for the design and construction of roads, mobility planning, transportation modeling as well as road management systems. However, the expensive measurement equipment and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42ed7274ce3492ae34dcbf8fbc352c49
https://doaj.org/article/4da1810891ae4ef4aedf85c443106916

Evolutionary Prediction Model for Fine-Grained Soils Compression Index Using Gene-Expression Programming

Autor: Danial Mohammadzadeh S, Kazemi, Seyed-Farzan, Mosavi, Amir, Nasseralshariati, Ehsan

Appropriate estimation of soil settlement is of significant importance since it directly influences the performance of building and infrastructures that are built on soil. In particular, the settlement of fine-grained soils is critical because of low

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=sharePrprorg::30264b2a1145f40f4863e701122f38a8

Deriving an intelligent model for soil compression index utilizing multi-gene genetic programming

Autor: S. H. Vafaee Jani Yazd, Amir H. Alavi, Jafar Bolouri Bazaz, Danial Mohammadzadeh S.

Publikováno v: Environmental Earth Sciences. 75

Multi-gene genetic programming (MGGP) is a new nonlinear system modeling approach that integrates the capabilities of standard GP and classical regression. This paper deals with the prediction of compression index of fine-grained soils using this rob

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b381c525333858db32823375f236a083
https://doi.org/10.1007/s12665-015-4889-2

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