...
首页> 外文期刊>Construction and Building Materials >A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete
【24h】

A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

机译:改进的萤火虫算法-人工神经网络专家系统预测高性能混凝土的抗压强度

获取原文
获取原文并翻译 | 示例

摘要

The compressive and tensile strength of high-performance concrete (HPC) is a highly nonlinear function of its constituents. The significance of expert frameworks for predicting the compressive and tensile strength of HPC is greatly distinguished in material technology. This study aims to develop an expert system based on the artificial neural network (ANN) model in association with a modified firefly algorithm (MFA). The ANN model is constructed from experimental data while MFA is used to optimize a set of initial weights and biases of ANN to improve the accuracy of this artificial intelligence technique. The accuracy of the proposed expert system is validated by comparing obtained results with those from the literature. The result indicates that the MFA-ANN hybrid system can obtain a better prediction of the high-performance concrete properties. The MFA-ANN is also much faster at solving problems. Therefore, the proposed approach can provide an efficient and accurate tool to predict and design HPC. (C) 2018 Elsevier Ltd. All rights reserved.
机译:高性能混凝土(HPC)的抗压强度和拉伸强度是其成分的高度非线性函数。在材料技术中,专家框架对于预测HPC的抗压强度和抗拉强度的意义非常重要。本研究旨在开发一种基于人工神经网络(ANN)模型并结合改进的萤火虫算法(MFA)的专家系统。 ANN模型是根据实验数据构建的,而MFA用于优化ANN的一组初始权重和偏差以提高此人工智能技术的准确性。通过将获得的结果与文献中的结果进行比较,可以验证所提出的专家系统的准确性。结果表明,MFA-ANN混合系统可以较好地预测高性能混凝土的性能。 MFA-ANN在解决问题方面也要快得多。因此,所提出的方法可以提供一种有效且准确的工具来预测和设计HPC。 (C)2018 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号