Hydrology
Ghazaleh Mohebbi Tafreshi; Mohammad Nakhaei; razieh Lak
Abstract
Land subsidence is a nonlinear and complex process that data-driven computational intelligence models can model it. In this study, the accuracy and efficiency of hybrid fuzzy logic gene expression planning hybrid model in estimating land subsidence risk and its factors in Varamin aquifer standardized. ...
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Land subsidence is a nonlinear and complex process that data-driven computational intelligence models can model it. In this study, the accuracy and efficiency of hybrid fuzzy logic gene expression planning hybrid model in estimating land subsidence risk and its factors in Varamin aquifer standardized. For this purpose, after selecting and gathering information from 15 factors affecting the subsidence event based on research records in the GIS environment, they were first standardized by fuzzy membership functions and then gene expression programming method was used to integrate the layers. Finally, using seven important statistical benchmarks based on radar image data, the model was validated in 4 different scenarios in input data and operators. The results showed scenario 1 with input parameters of bedrock level, Debi of pumping wells, groundwater drawdown, geology and operators, +, - ×, ÷, sqr, exp, Ln, ^ 2, ^ 3,3Rt, sin, cos, Atan, is the best model in training and testing. Accordingly, the groundwater drawdown parameter had the highest effect on land subsidence in the study area.
K. Habibi; M. Behzadfar; A. Meshkini; S. Nazari
Abstract
Due to its geographic position and located on the World earthquake belt; Iran is always under threat from earthquakes and several shakes are recorded every year all over the country. The most recent earthquake with 6.8 degree magnitude on the Richter scale hit the city of Bam in 2003 and caused large ...
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Due to its geographic position and located on the World earthquake belt; Iran is always under threat from earthquakes and several shakes are recorded every year all over the country. The most recent earthquake with 6.8 degree magnitude on the Richter scale hit the city of Bam in 2003 and caused large losses of human life and infrastructure. The 2003 Bam earthquake, with more than 30,000 casualties and 10,000 injuries, was the most Destructive earthquake in the current century in Iran. We aim to recognize the main reasons causing these deterioration problems. To this end, we first conceptualize thirteen physical-spatial factors. These factors are analyzed using fuzzy logic and IHPW (Inverse Hierarchy Process Weight) within Geographical Information System. We also attempt to identify the Correlation coefficient analyses between urban vulnerability and damage using Fuzzy logic and GIS. In statistics, correlation and dependence are any of a broad class of statistical relationships between two or more random variables or observed data values. With respect to the covariance between two variables (urban vulnerability map and damage post earthquake) the correlation coefficient is calculated 0.59. The results of the model as applied to the structures of the city of Bam illustrate that a fuzzy approach is a basic tool that can be used to identify urban vulnerability and damage post earthquake incident. Its application to the problem assists in unifying relevant theories and practices.
