Hanifi Canakci

TL;DR: This paper makes an attempt to apply a promising set of genetic programming techniques which are known as multi expression programming, gene expression programming (GEP) and linear genetic programming (LGP) to the uniaxial compressive strength (UCS) and tensile strength prediction of chalky and clayey soft limestone.

TL;DR: In this article, the fluidity and rheological properties of the cement-based grout mixed with rice husk ash (RHA) were investigated, and it was shown that increasing replacement level for the RHA amount increases marsh cone flow time, plate cohesion, plastic and apparent viscosity, and the yield stress, but also decreases mini slump diameter.

TL;DR: In this paper, a special injection system was prepared for inducing a bacterial solution into several samples and the bacterial solution was supplied to the samples by gravity for 4 days in specific molds designed for this work.

TL;DR: Two soft computing approaches, which are known as artificial neural networks and Gene Expression Programming are used in strength prediction of basalts which are collected from Gaziantep region in Turkey and it is found out that neural networks are quite effective in comparison to GEP and classical regression analyses in predicting the strength of the basalts.

TL;DR: In this article, the authors investigated the use of cement-based grout combined with glass powder to enhance the clay soil via deep mixing technique, and the results indicated that the setting times of the mixture pastes increase, while the bulk densities of the soilcrete samples do not significantly change with the replacement of glass powder.