Abstract

As substitution method, artificial neural network instructed based on numerical analyzed patterns except than more feasibility and speed than other methods can also reach the accuracy required in numerical modeling. In this paper a model based on Perspetron multilayer artificial neural network have been presented for intelligent regressive analysis of Narmab water conveyance tunnel base on monitoring data. Our input data were 27 parameters categorized in three classes including: tunneling data, geological data and average of in situ horizontal stress. For network instruction, data bank of regressive analysis results of 18 Survey Convergence stations was prepared in 980 classes by using FLAC3D software. Then according to network behavior in instructing step, optimum values for medial layers number, neurons number and, activity functions obtained. By this way a model was mad based on artificial neural network that was able to regressive analyzing of displacements in future Survey Convergence station projects in every time of monitoring. In back analysis algorithms, for example, with a large number of correct answers received and produce plans with a problem. If properly used, for example, new programs will work correctly. The neural network may improve the accuracy of the analysis. This is where the advantage of neural networks or ANN determined.

1 Introduction

Neural Network abilities in learning from widely dispersed and erroneous data caused this technique to be successful in solving problems related to geotechnical engineering. Although, teaching a neural network is a time-consuming process, when running at high speed, it can be time-saving, though. Therefore, it can be taken into account as an appropriate alternative for time-consuming and complex numerical back analysis of monitoring results.

This research is aimed at using ANN technique for learning relations between geological engineering parameters, tunneling methods and monitoring results in instrumented sections and geomechanical parameters of average horizontal in situ stress as well as elasticity module of rock masses surrounding Narmab Water Conveyance Tunnel using to estimate geomechanical parameters for similar future monitoring stations in non-excavated sections of Narmab Tunnel.

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