基于人工神经网络的等离子熔积层形貌试验研究     

徐继彭  林柳兰  胡庆夕  方明伦 《上海大学学报(英文版)》2006,10(5):443-448

1IntroductionPlasma deposition manufacturing(PDM)is a newlydeveloped direct metal fabrication process based onplasma transferred arc surfacing[1],as shown in Fig.1.Unlike most existing rapid prototyping techn-ologies,this technique is characterized by sup…  相似文献   

工程陶瓷磨削力建模的研究     

周会娜 《天津职业院校联合学报》2008,10(5)

通过对Si3N4、Al2O3和ZrO2三种工程陶瓷材料进行磨削加工试验,获得磨削力的实验数据。利用人工神经网络和遗传算法建立工程陶瓷磨削力数学模型。在相同的加工条件下参照试验数据对这两种模型进行分析,得出人工神经网络建立的数学模型相对误差小些。  相似文献   

Evaluation of accelerated deterioration in NAPTF flexible test pavements     

Kasthurirangan Gopalakrishnan 《浙江大学学报(A卷英文版)》2008,9(9):1157-1166

Previous research studies have successfully demonstrated the use of artificial neural network （ANN） models for predicting critical structural responses and layer moduli of highway flexible pavements. The primary objective of this study was to develop an ANN-based approach for backcalculation of pavement moduli based on heavy weight deflectometer （HWD） test data, especially in the analysis of airport flexible pavements subjected to new generation aircraft （NGA）. Two medium-strength subgrade flexible test sections, at the National Airport Pavement Test Facility （NAPTF）, were modeled using a finite element （FE） based pavement analysis program, which can consider the non-linear stress-dependent behavior of pavement geomaterials. A multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD back- calculation function using the FE program generated synthetic database. At the NAPTF, test sections were subjected to Boeing 777 （B777） trafficking on one lane and Boeing 747 （B747） trafficking on the other lane using a test machine. To monitor the effect of traffic and climatic variations on pavement structural responses, HWD tests were conducted on the trafficked lanes and on the untrafficked centerline of test sections as trafficking progressed. The trained ANN models were successfully applied on the actual HWD test data acquired at the NAPTF to predict the asphalt concrete moduli and non-linear subgrade moduli of the medium-strength subgrade flexible test sections.  相似文献   

Exponential synchronization of general chaotic delayed neural networks via hybrid feedback     

Mei-qin Liu  Jian-hai Zhang 《浙江大学学报(A卷英文版)》2008,9(2):262-270

This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, and covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks （CNNs）, bidirectional associative memory （BAM） networks, recurrent multilayer perceptrons （RMLPs）. By virtue of Lyapunov- Krasovskii stability theory and linear matrix inequality （LMI） technique, some exponential synchronization criteria are derived. Using the drive-response concept, hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria. Finally, detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.  相似文献   

An artificial neural network approach for prediction of long-term strength properties of steel fiber reinforced concrete containing fly ash     

Okan Karahan  Harun Tanyildizi  Cengiz D. Atis 《浙江大学学报(A卷英文版)》2008,9(11):1514-1523

In this study, an artificial neural network （ANN） model for studying the strength properties of steel fiber reinforced concrete （SFRC） containing fly ash was devised. The mixtures were prepared with 0 wt%, 15 wt%, and 30 wt% of fly ash, at 0 vol.%, 0.5 vol.%, 1.0 vol.% and 1.5 vol.% of fiber, respectively. After being cured under the standard conditions for 7, 28, 90 and 365 d, the specimens of each mixture were tested to determine the corresponding compressive and flexural strengths. The pa- rameters such as the amounts of cement, fly ash replacement, sand, gravel, steel fiber, and the age of samples were selected as input variables, while the compressive and flexural strengths of the concrete were chosen as the output variables. The back propagation learning algorithm with three different variants, namely the Levenberg-Marquardt （LM）, scaled conjugate gradient （SCG） and Fletcher-Powell conjugate gradient （CGF） algorithms were used in the network so that the best approach can be found. The results obtained from the model and the experiments were compared, and it was found that the suitable algorithm is the LM algorithm. Furthermore, the analysis of variance （ANOVA） method was used to determine how importantly the experimental parameters affect the strength of these mixtures.  相似文献   

基于人工神经网络的企业知识管理评价模型   总被引：22，自引：0，他引：22  

朱启红  张钢 《科学学与科学技术管理》2003,24(8):32-34

文章提出了基于人工神经网络的企业知识管理评价模型。实例表明，人工神经网络方法应用于企业知识管理评价是可行和有效的。  相似文献   

基于主成分-神经网络风险预警模型研究     

蔡炜华  陈翔  王秋红  张慧玲 《中国科技信息》2006,(2):120

本文研究了主成分和人工神经网络混合算法在建筑施工项目风险预警中的应用;建立了基于主成分神经网络风险预警模型;并用实例验证了模型的有效性.  相似文献   

我国受限技术的监测与评估理论方法研究     

胡望斌 《科研管理》2007,28(6):76-84

技术强国对华技术出口限制严重影响了我国经济、技术的自由和快速发展,然而我国对这些受限技术深入系统的研究很少。本文首先应用技术监测方法,进行了技术强国针对我国实施的技术出口限制内容动态监测研究。然后综合运用模糊评价法以及人工神经网络等理论方法,对我国受限技术与我国重点发展领域的对比、与技术强国之间的技术差距、我国发展的重要性等进行分析和研究,建立我国受限技术评估的理论方法。从而可以准确认识我国受限技术的本质特征,为我国受限技术的发展和决策提供科学的指导和帮助。  相似文献   

基于BP人工神经网络的物流配送中心选址决策   总被引：25，自引：0，他引：25  

韩庆兰  梅运先 《中国软科学》2004,(6):140-143

物流配送中心的选址在整个物流系统规划中占有十分重要的地位,需要决策者综合考虑多种因素。但在传统的算法中,有些重要的定性因素被忽略。本文通过建立选址决策的模糊评价矩阵,利用BP人工神经网络来处理数据,可避免传统算法的不足,较客观地对多个选址方案的优劣进行评价,并引用实例说明该方法的实现过程。  相似文献   

CAPP中人工神经网络的应用     

盖凌云 《中国科技信息》2006,3(18):300-301

本文阐述了人工神经网络技术，研究分析了BP神经网络模型的基本原理。在此基础上，将神经网络理论应用于CAPP之中，提出了基于此理论的系统模型。  相似文献