Study of CNG/diesel dual fuel engine's emissions by means of RBF neural network     

刘震涛  费少梅 《浙江大学学报(A卷英文版)》2004,5(8):960-965

Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resume, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.  相似文献   

基于神经网络的CAI课件的综合评价研究与应用     

曹世华  赵方  沈惠惠 《实验室研究与探索》2008,27(8)

利用神经网络的自适应性和自学习功能,提出了一种CAI课件的综合评价方法,给出了CAI课件的各参考评价指标,并讨论了如何使用综合评价方法获得综合评价的结果,。研究表明该方法比传统评价过程更具客观、准确、科学、高效的特点。  相似文献   

应用神经网络专家系统预测浅层地下水水质     

李云先 《淮南职业技术学院学报》2005,5(2):92-95

在系统介绍神经网络专家系统基本原理和工作步骤的基础上，利用开发出的神经网络专家系统，总结分析出影响淮南市区浅层地下水水质的主要参数，并通过B-P网络对大量实例的学习，自动生成符合实际的专家知识库；对实际问题，只要输入区块的特征参数，系统就能由推理机根据专家知识库给出预测区的水质，权值不受人因素为干扰．并以淮南市区16已知水样点的评价参数及水质级别为学习样本，对6预测水样点的水质进行了预测，结果表明效果良好；从而指出运用神经网络专家系统可以克服指数法和聚类法等不易准确确定参数的隶属度和权重分配等局限性，保证了预测结果的精确度和可靠性；只要测得预测目标的特征参数后，输入系统，很快就能得出预测结果，从而提高了预测速度和工作效率。  相似文献   

基于粗糙集和神经网络理论的入侵检测分类器的设计与实现     

张小松  郭琳虹  窦炳琳 《唐山学院学报》2007,20(2):18-20

入侵检测系统中分类器的设计是整个系统中重要部分。提出一种基于粗糙集约简算法的神经网络分类器模型,将粗糙集能够在保持系统精度的情况下去掉冗余属性引入到神经网络中,优化网络结构。实验测试表明,此模型能够保证系统检测的准确性,具有一定的实用性。  相似文献   

神经网络模拟嗅觉行为研究     

钟艳花 《广东教育学院学报》2003,23(2):92-95

以人类嗅觉机理为研究对象，研究建立了一种基于高斯函数(GPFN)神经网络的气味鉴别模型．计算表明，该模型能较为准确地鉴别学习过的气体．模拟精度较高，便于应用．  相似文献   

径向基函数网络在优化机械加工参数中的应用   总被引：1，自引：0，他引：1  

朱喜林  吴博达  武星星 《上海大学学报(英文版)》2004,8(Z1)

In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.  相似文献   

基于BP神经网络的高性能混凝土早龄期自干燥收缩预测     

许利惟  郑建岚 《福建工程学院学报》2008,6(1)

采用人工神经网络方法,建立高性能混凝土原材料配合比与其早龄期自干燥收缩之间的非线性映射关系.计算结果表明,该模型可以预测不同配合比混凝土的早龄期自干燥收缩,为高性能混凝土体积稳定性的研究提供一种思路.  相似文献   

A Second Order Training Algorithm for Multilayer Feedforward Neural Networks     

谭营  何振亚  邓超 《东南大学学报》1997,(1)

ＡＳｅｃｏｎｄＯｒｄｅｒＴｒａｉｎｉｎｇＡｌｇｏｒｉｔｈｍｆｏｒＭｕｌｔｉｌａｙｅｒＦｅｅｄｆｏｒｗａｒｄＮｅｕｒａｌＮｅｔｗｏｒｋｓＴａｎＹｉｎｇ（谭营）ＨｅＺｈｅｎｙａ（何振亚）（ＤｅｐａｒｔｍｅｎｔｏｆＲａｄｉｏＥｎｇｉｎｅｅｒｉｎｇ，Ｓｏｕ...  相似文献   

利用Hopfield神经网络实现自适应滤波器     

刘茜君  陈钧量 《中山大学学报论丛》1992,(2)

针对两种不同结构的Hopfield神经网络,本文提出分别适当选取该神经网络的连接权值来实现LMS自适应滤波和自适应格型滤波的方法。并分析了实现自适应滤波的HOP-field神经网络的稳定性及其滤波性能.  相似文献   

格式塔理论对美术的实用价值何在     

王令中 《新乡师范高等专科学校学报》2005,19(4):92-94

格式塔理论的艺术价值并不完全体现在具体结论的实用性上,更多地体现在综合分析的辩证方法论中。格式塔注重形式表现的整体关系,强调形式作用的可塑性、伸延性,兼顾形式自身的性质和视觉心理的能动反映。这些辩证的观念符合艺术实践中的实际情况,具有更好的艺术指导意义和可操作性。进一步研究和补充实质性内容,是将艺术规律转化为实用价值的良好途径。  相似文献