신경망을 이용한 콘크리트의 압축강도 및 슬럼프값 추정

다국어 초록 (Multilingual Abstract)

An artificial neural network is applied to the prediction of compressive strength, slump value of concrete. Standard mixed tables arc trained and estimated, and the results are compared with those of experiments. To consider the varieties of material properties, the standard mixed tables of two companies of Ready Mixed Concrete are used. And they are trained with the neural network. In this paper, standard back propagation net work is used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of 210, 240kgf/㎠ and target slump value of 12, 15㎝ are used because the amount of production of that range arc the most at ordinary companies. In results, in the prediction of compressive strength and slump value, the predicted values are converged well to those of standard mixed tables at the target error of 0.10, 0.05, 0.001 regardless of two companies.<br/>

목차 (Table of Contents)

• Abstract
  
• 1. 서론
  
• 2. 신경망에 대한 이론적 고찰
  
• 3. 신경망을 이용한 압축강도 및 슬럼프값의 추정
  
• 4. 결론
  
• 참고문헌