Akademik Veri Yönetim Sistemi
International Journal Of Physical Sciences, cilt.5, ss.47-56, 2010 (SCI-Expanded)
By using an artificial intelligent approaches, the purpose of this study is to compare water content of
soils obtained from electrical resistivity in order to better results from conventional techniques system.
The input variables for this system are the electrical resistivity reading, the water content laboratory
measurements. The output variable is water content of soils. In this study, 148 data sets are clustered
into 120 training sets and 28 testing sets for constructing the fuzzy system and validating the ability of
system prediction, respectively. Soil is a heterogeneous medium consisting of liquid, solid, and
gaseous phases. The solid and liquid phases play an essential role in soil spontaneous electrical
phenomena and in behavior of electrical fields, artificially created in soil. For our aim, study area is
selected in Istanbul (Yesilkoy, Florya, Basinkoy) and Golcuk. In this area, the electrical resistivity is
measured by VES (Vertical Electrical Sounding) in many points of these locations by field resistivity
equipment. For geotechnical purposes, on the soil samples from borings, soil mechanics laboratory
procedures was applied and it determined the soil water contents from these samples. Relationships
between soil water content and electrical parameters were obtained by curvilinear models. The ranges
of our samples are changed between 1 - 50 ohm.m (for resistivity) and 20 - 60 (%, for water content). For
this range, it was found that classical regression relation between resistivity (R) and water content (W)
of soils was W = 49.21e-0.017R. An artificial intelligent system (artificial neural networks, Fuzzy logic
applications, Mamdani and Sugeno approaches) based on some comparisons about correlation
between electrical resistivity and soil-water content, for Istanbul and Golcuk Soils in Turkey was
constructed for identifying water content with electrical resistivity of soils.