Soft Ground Settlement Estimation Using Neural Network

인공신경망을 이용한 연약지반 침하량 산정

  • 노재호 (GS건설(주) 토목사업본부 토목공사팀) ;
  • 원효재 (GS건설(주) 토목사업본부 토목기술설계팀) ;
  • 오두환 (GS건설(주) 토목사업본부) ;
  • 황선근 (한국철도기술연구원 궤도노반연구팀)
  • Published : 2006.11.09

Abstract

Purpose of this research is that offers basic data for optimized design using neural network method to calculate consolidation settlement in study area. In this research, preformed the neural network method that analyzed the settlement characteristics of soft ground nearby study area. Thus, data base established on ground properties and consolidation settlement of neighboring area. In addition, designed the optimum neural network model for prediction of settlement through network learning and consolidation settlement prediction using consolidation settlement DB and ground properties DB. Optimized neural network model decided by repeated learning for various case of hidden layers. In this study, proposed that the optimized consolidation settlement calculation method using neural network and verified which is the optimized consolidation settlement calculation method using neural network.

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