Application of Modularized Neural Network to Predicting the Strength of High Performance Concrete
碩士 === 國立交通大學 === 土木工程系 === 88 === In addition to the four basic ingredients of the conventional| concrete, i.e., Portland cement, fine and coarse aggregates, and water, the making of HPC needs to incorporate the supplementary cementations materials, such as fly ash and blast furnace...
Main Authors: | Ming-Kuan Tsai, 蔡閔光 |
---|---|
Other Authors: | Shin-Lin Hung |
Format: | Others |
Language: | zh-TW |
Published: |
2000
|
Online Access: | http://ndltd.ncl.edu.tw/handle/91885448748645719345 |
Similar Items
-
Application of Unsupervised Fuzzy Neural Network Reasoning Model for the prediction of the strength of High-Performance Concrete
by: Yu-Chao Chen, et al.
Published: (2000) -
Application of Artificial Neural Network to Predicting the Strength and Young''s Modulus of Concrete
by: Lee, Cherng-Shing, et al.
Published: (1997) -
Study on Prediction Model for Concrete Compressive Strength Using Artificial Neural Network and Regression Analysis
by: Chien-Cheng Tsai, et al.
Published: (2003) -
Torsional Strength of Plain High-Strength Concrete Beams
by: Wu Kuan-Yu, et al.
Published: (1995) -
Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks
by: Mehdi Nikoo, et al.
Published: (2015-01-01)