2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)最新文献_第8页

Prediction and Analysis of Blast-Induced Vibration for Urban Shallow Buried Tunnel Using Various Types of Artificial Neural Networks 基于各类人工神经网络的城市浅埋隧道爆震预测与分析

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.163

Yin Zuoming, Wang Desheng, Gao Zhaoshuai, Liang Shuchang

{"title":"Prediction and Analysis of Blast-Induced Vibration for Urban Shallow Buried Tunnel Using Various Types of Artificial Neural Networks","authors":"Yin Zuoming, Wang Desheng, Gao Zhaoshuai, Liang Shuchang","doi":"10.1109/ICICTA.2015.163","DOIUrl":"https://doi.org/10.1109/ICICTA.2015.163","url":null,"abstract":"Urban shallow buried tunnel excavated in mining method may produce a bad effect on constructions by blast-induced vibration, especially for the tunnel in complex environment. Based on Beijing metro line16 engineering which is beneath the gas pipeline, in soil and rocks mixing zone, close to buildings, comparative analysis was done between the blast-induced vibration velocity predicted by Sardolfski formula and normal back propagation neural network(BP-NN). The research shows that the average predict error of Sardolfski formula is larger than that of BP-NN because of influences of medium for seismic wave propagation, blasting technology and surrounding rock properties. Even though the BP-NN has a higher prediction accuracy, it can not meet the needs of precision blasting control. A new dynamic prediction model with local feedback characteristics called Elman neural network(Elman-NN) is proposed based on field data analysis. The prediction particle velocity accuracy of Elman-NN results is improved by 9.1 percentage. Therefore, the Elman-NN has profound guiding significance on urban shallow buried tunnel excavated safety and efficient.","PeriodicalId":231694,"journal":{"name":"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)","volume":"307 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123627954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on the Application of BIM Model in Interior Design BIM模型在室内设计中的应用研究

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.195

Huang Weiyan, Yang Peng

引用次数: 0

Study of RBF Neural Network Based on PSO Algorithm in Nonlinear System Identification 基于粒子群算法的RBF神经网络在非线性系统辨识中的研究

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.217

Ye Guoqiang, L. Weiguang, Wang Hao

{"title":"Study of RBF Neural Network Based on PSO Algorithm in Nonlinear System Identification","authors":"Ye Guoqiang, L. Weiguang, Wang Hao","doi":"10.1109/ICICTA.2015.217","DOIUrl":"https://doi.org/10.1109/ICICTA.2015.217","url":null,"abstract":"Development of neural network provided new thought for nonlinear system identification. RBF neural network was widely studied in nonlinear system identification by good approximation ability and fast convergence thereof. In the paper, RBF neural network based on PSO algorithm was proposed, global searching property of PSO algorithm was utilized for remedying RBF local approximation, initial weights of RBF neural network and the base width were globally optimized, insufficiency in RBF neural network random initialization weights and base width was remedied, and identification precision of RBF neural network on nonlinear system was improved aiming at problems of RBF neutral network in nonlinear system identification application, such as local approximation and base width random initialization. The simulation results showed that RBF neural network based on PSO algorithm, proposed in the paper, had prominently better identification precision on nonlinear system than identification of RBF neural network based on GA algorithm and the traditional RBF neural network, and it had great significance on identification of nonlinear systems.","PeriodicalId":231694,"journal":{"name":"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126006499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Prediction of the Pore Size Distribution in Spunbond-Needlepunched Nonwoven Geotextiles Based on a Stochastic Simulation 基于随机模拟的纺-针刺非织造土工布孔径分布预测

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.166

Z. Heng, Qian Xiaoming

{"title":"Prediction of the Pore Size Distribution in Spunbond-Needlepunched Nonwoven Geotextiles Based on a Stochastic Simulation","authors":"Z. Heng, Qian Xiaoming","doi":"10.1109/ICICTA.2015.166","DOIUrl":"https://doi.org/10.1109/ICICTA.2015.166","url":null,"abstract":"Pore size distribution is the key factor of the nonwoven geotextiles for various functions including filtration, separation and reinforcement. The comparison of pore size distributions of spunbond-needle punched nonwoven geotextiles has been made among the theoretical, experimental and the virtual study based on a stochastic simulation. Moreover, the influence of fiber diameter, solid volume fraction, and the thickness of the nonwoven geotextiles on the pore size distribution of the nonwoven geotextiles has been investigated. It is demonstrated that the pore size distribution, which obtained using Geodict® based on a stochastic simulation, shows a good agreement with experimental data and theoretical, and it is feasible for the prediction of pore size distribution in spunbond-needle punched nonwoven geotextiles. The results show that increasing the solid volume fraction would decrease the pore size of the nonwoven geotextiles under the same filament diameter and same thickness of the webs. Increasing fiber diameter would cause the pore size decreasing, while thickness and solid volume fraction kept constant also found. The results also show that the pore size decreasing with the thickness of the nonwoven geotextiles increasing, while the constant of the solid volume fraction and filaments diameter.","PeriodicalId":231694,"journal":{"name":"2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127115778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Psychology Network Teaching Quality Evaluation System Design Based on Multiple Granularity Two-tuple Semantic Model 基于多粒度二元语义模型的心理学网络教学质量评价系统设计

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.169

Liu Xiao-ping

引用次数: 0

Analysis of a New Wedge-Shape Rectangular Tube Column and Girder Connection Joint 一种新型楔形矩形管柱梁连接节点分析

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.51

Li Xiaorun, Song Bo, Bi Xiaofang, Wang Pin, Wu Changdong, Chen Shuirong

引用次数: 0

Application Study of Hot Dip Aluminized Steel in Transformer Substation 热浸镀铝钢在变电站中的应用研究

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.63

Wang Xuming, Wang Xianpeng, Yang Zhanjin, Yao Boyan, H. Junke, Huang Yao

引用次数: 1

A 3D Numerical Model of Nearshore Wave-Induced Currents Based on the Discontinuous Galerkin Method 基于不连续伽辽金法的近岸波浪感应流三维数值模型

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.11

Zhao Zhangyi, Z. Qinghe

引用次数: 0

Teaching Evaluation Model Research Based on Integration of Information Technology 基于信息技术集成的教学评价模式研究

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.232

Zhang Jun, Zhang Ying

引用次数: 2

An Adaptive Data Management Model for Smart Grid 智能电网的自适应数据管理模型

2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) Pub Date : 2015-06-14 DOI: 10.1109/ICICTA.2015.40

Xu Daqing, Han Yinghua

引用次数: 4