The application of automatic acquisition of knowledge to mix design of concrete

被引：0

作者：

Wang, JZ ^{[1
]}

Ni, HG ^{[1
]}

He, JY ^{[1
]}

机构：

[1] Hebei Inst Architecture Sch & Technol, Handan 056038, Hebei, Peoples R China

来源：

CEMENT AND CONCRETE RESEARCH | 1999年 / 29卷 / 12期

关键词：

mix design; compressive strength; workability; neural networks; knowledge-acquisition system;

D O I：

暂无

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

In this paper, an automatic knowledge-acquisition system based on neural networks is created to design concrete mix. This system consists of three models: the mix-design model, the slump-prediction model, and the strength-prediction model; the first model is the core of the system with the other two models supporting the core. Each model is made up of a mix-design database, a knowledge base, a neural network-learning block, and a problem solution block. The automatic acquisition of knowledge is realized through the learning process of a neural network from sample mix designs. The knowledge base is the network itself. This system not only makes full use of the workable mix designs that are already in existence but also provides a quick means to predict the slump and 28-day compressive strength of ready made concrete. Examples and experimental work show that the application of the system to concrete mix design is practicable. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：1875 / 1880

页数：6