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

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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
Yin Zuoming, Wang Desheng, Gao Zhaoshuai, Liang Shuchang
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.
采用采矿法开挖的城市浅埋隧道,特别是处于复杂环境中的隧道,爆破诱发振动会对建筑物产生不良影响。以北京地铁16号线工程为例,在输气管道下方、土石混合区、靠近建筑物的位置,将Sardolfski公式预测的爆破激振速度与正态反传播神经网络(BP-NN)进行了对比分析。研究表明,由于地震波传播介质、爆破技术和围岩性质的影响,Sardolfski公式的平均预测误差大于BP-NN公式的平均预测误差。BP-NN虽然具有较高的预测精度,但仍不能满足精确爆破控制的需要。在现场数据分析的基础上,提出了一种具有局部反馈特性的动态预测模型——Elman神经网络(Elman- nn)。Elman-NN预测的粒子速度精度提高了9.1%。因此,Elman-NN对城市浅埋隧道的安全高效开挖具有深远的指导意义。
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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
Huang Weiyan, Yang Peng
In the context of the digital information era, the 2D models with the major expression means of the traditional computer graphics software, such as Auto CAD, have become less and less able to meet the demands on interior design of large construction projects with complex geometry. In combination with the application of the BIM technology at the stage of design, construction design and anaphase project management of interior projects, BIM's strengths and its problems exposed at present were summarized to explore how this new technology can better serve specific interior projects and how practitioners should meet the changes brought by information technology in the industry.
在数字信息时代的背景下,以Auto CAD等传统计算机图形软件为主要表达手段的二维模型已经越来越不能满足大型建筑项目复杂几何结构的室内设计需求。结合BIM技术在室内项目设计、施工设计和后期项目管理阶段的应用,总结BIM的优势和目前暴露出的问题,探讨这种新技术如何更好地服务于具体的室内项目,以及从业者应该如何应对信息技术给行业带来的变化。
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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
Ye Guoqiang, L. Weiguang, Wang Hao
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.
神经网络的发展为非线性系统辨识提供了新的思路。RBF神经网络以其良好的逼近能力和快速的收敛性在非线性系统辨识中得到了广泛的研究。本文提出了基于PSO算法的RBF神经网络,利用PSO算法的全局搜索特性弥补了RBF局部逼近的缺陷,对RBF神经网络的初始权值和基宽度进行了全局优化,弥补了RBF神经网络随机初始权值和基宽度的不足;针对RBF神经网络在非线性系统辨识中存在的局部逼近和基宽随机初始化等问题,提高了RBF神经网络对非线性系统的辨识精度。仿真结果表明,本文提出的基于PSO算法的RBF神经网络对非线性系统的识别精度明显优于基于GA算法的RBF神经网络和传统的RBF神经网络,对非线性系统的识别具有重要意义。
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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
Z. Heng, Qian Xiaoming
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.
孔径分布是非织造土工布发挥过滤、分离、加固等多种功能的关键因素。对纺粘针刺非织造土工布的孔径分布进行了理论、实验和基于随机模拟的虚拟研究对比。此外,还研究了纤维直径、固体体积分数和非织造土工布厚度对非织造土工布孔径分布的影响。结果表明,基于随机模拟的Geodict®计算得到的孔隙尺寸分布与实验数据和理论数据吻合较好,对针刺非织造土工布的孔隙尺寸分布进行预测是可行的。结果表明:在相同丝径和相同腹板厚度的情况下,增加固体体积分数会减小非织造土工布的孔径;纤维直径增大,孔径减小,纤维厚度和固体体积分数保持不变。结果还表明,非织造土工布的孔隙尺寸随厚度的增加而减小,而固相体积分数和细丝直径则随厚度的增加而增大。
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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
Liu Xiao-ping
University Psychology Network teaching quality evaluation system is designed, and using multiple granularity semantic computing model to compute and process the language information. The method is not only simple calculation, accurate, but also can be used for Web pages to realize online assessment, at the same time it can be used for service quality evaluation in other service industry.
设计了大学心理学网络教学质量评价系统,并采用多粒度语义计算模型对语言信息进行计算和处理。该方法不仅计算简单、准确,而且可用于对网页实现在线评价,同时也可用于其他服务行业的服务质量评价。
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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
Li Xiaorun, Song Bo, Bi Xiaofang, Wang Pin, Wu Changdong, Chen Shuirong
Aiming at the existing problems of column-beam joint put forward the new wedge-box joint. The new joint shape is simple, avoid the inconvenience that add diaphragm in the square tube, as well as to the late process of building interior decoration, the way of joints force transmission is clear, mechanical and seismic performance is good, from the external shape is better than the traditional internal partition and outreach plate joints, and compare to the both, inner bearing capacity is not weak, it can satisfy the need of industrialization of steel structure well, and used in actual engineering design.
针对柱-梁节点存在的问题,提出了新型楔箱节点。新型接头形状简单,避免了在方管中添加隔膜的不便,以及对建筑内部装修的后期处理,接头的传力方式清晰,力学和抗震性能好,从外部形状上优于传统的内隔断和外展板接头,并与两者相比,内部承载力不弱,可以很好地满足钢结构工业化的需要。并应用于实际工程设计中。
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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
Wang Xuming, Wang Xianpeng, Yang Zhanjin, Yao Boyan, H. Junke, Huang Yao
Based on the experiment method, the mechanical properties, adhesion, corrosion performance, appearance of the hot dip aluminized steel, and the thickness of aluminized layer were analyzed. The study showed that, after the hot dip aluminized process, the corrosion performance was improved, adhesion and appearance can meet the requirements of application in transformer substation. But the mechanical properties of materials was reduced, the problems of bolt plating leakage may be occurred. This paper provides a reference for the application of aluminized steel in transformer substation.
基于实验方法,对热浸镀铝钢的力学性能、附着力、腐蚀性能、外观及镀铝层厚度进行了分析。研究表明,经热浸镀铝处理后,防腐性能得到改善,附着力和外观均能满足变电站应用要求。但材料的力学性能降低,有可能出现螺栓镀漏的问题。本文为渗铝钢在变电站中的应用提供了参考。
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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
Zhao Zhangyi, Z. Qinghe
Based on the discontinuous Galerkin methods, the concept of three-dimensional radiation stress, surface roller and wave turbulent mixing effects were applied to develop the three-dimensional, unstructured grids numerical model for wave-induced currents. Validation of the model was carried out by comparing the model simulation with laboratory measurements for wave-induced currents over a slope, e.g. Undertow and long shore currents. The model results showed that the agreement between the simulated results and the laboratory measurements is generally good, the proposed model could be used to describe three-dimensional wave induced currents in near shore zone.
基于不连续伽辽金方法,引入三维辐射应力、表面滚子和波浪湍流混合效应的概念,建立了波浪感应电流的三维非结构网格数值模型。通过将模型模拟与实验室测量的斜坡上波浪引起的流(如底流和长岸流)进行比较,对模型进行了验证。模型结果表明,模拟结果与实验室测量结果吻合较好,该模型可用于近岸区三维波浪感应流的描述。
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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
Zhang Jun, Zhang Ying
The teaching evaluation model based on information technology is established, which finds out the factor influencing teaching quality according to the relation between teaching evaluation data and students' achievement. Association rules are used for in-depth data mining to find out the key impact factor that determines the quality so as to find a strong theoretical and practical basis to improve the teaching quality. The experiment results show this classroom teaching quality evaluation mechanism is effective.
建立了基于信息技术的教学评价模型,根据教学评价数据与学生成绩之间的关系,找出影响教学质量的因素。利用关联规则进行深度数据挖掘,找出决定教学质量的关键影响因素,为提高教学质量提供有力的理论和实践依据。实验结果表明,该课堂教学质量评价机制是有效的。
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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
Xu Daqing, Han Yinghua
Application of big data techniques in power system will contribute to the sustainable development of power industry companies and the establishment of strong smart grid. There are significant challenges for big data analytics because of heterogeneous data and scalability, system complexity, reliability, and real time requirements for smart grid. In this paper, a data management model is proposed based on knowledge cube, which is an intelligent and adaptive database. The knowledge cube is established based on Topical, Association, Spatial and Temporal. The proposed data management model could handle data that is only relevant to its semantics. And the cube could be combined adaptively with the necessary information about other relevant knowledge cubes by the association component. The proposed knowledge cubes can support the capture and tracking of dynamic data. The proposed model provides a powerful and extensible framework that is particularly well suited to analyzing big variety data in smart grid.
大数据技术在电力系统中的应用,将有助于电力企业的可持续发展和强智能电网的建设。由于异构数据和可扩展性、系统复杂性、可靠性和智能电网的实时性要求,大数据分析面临着重大挑战。本文提出了一种基于知识立方体的数据管理模型,它是一种智能的自适应数据库。知识立方体是基于主题、关联、空间和时间构建的。所建议的数据管理模型可以处理仅与其语义相关的数据。该多维数据集可以通过关联组件自适应地与其他相关知识多维数据集的必要信息进行组合。所提出的知识多维数据集可以支持动态数据的捕获和跟踪。该模型提供了一个功能强大、可扩展的框架,特别适合于智能电网中海量数据的分析。
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引用次数: 4
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2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)
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