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排序方式: 共有80条查询结果,搜索用时 16 毫秒
1.
曹亚廷 《郑州航空工业管理学院学报(管理科学版)》2006,24(6):66-68
当基础货币发生变化时,货币乘数并不是保持不变的,尤其是在剔除我国频繁调整的法定存款准备金率对基础货币的影响后,基础货币的增长率和两个货币乘数K1、K2增长率之间可能存在反向关系。利用协整回归和向量误差纠正模型,对基础货币与货币乘数间关系进行分析后认为:基础货币无论是长期还是短期,对货币乘数都有显著的反向影响。 相似文献
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张明影 《西安航空技术高等专科学校学报》2002,20(1):49-50
在理论力学教学中,平面运动刚体的转动与基点无关的证明过于简单,本利用矢量代数的知识,证明平面运动刚体的角度与角加速度与基点的选择无关。 相似文献
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针对传统航空发动机性能参数时间序列预测方法存在的不足,提出了基于滑动时窗策略自适应优化支持向量机(Support Vector Machine,SVM)在线预测模型。该方法解决了训练样本动态适应性差的特点和老旧数据信息影响预测模型精度的问题。在该方法中,滑动时窗策略实时更新时窗数据训练样本,最终误差预报准则(Final Prediction Error,FPE)自适应地确定嵌入维数,遗传算法(Genetic Algorithm,GA)则实时自适应优化SVM建模参数。应用航空发动机排气温度偏差值(Delta Exhaust Gas Temperature,DEGT)数据进行实例验证,结果表明基于滑动时窗策略的自适应GA优化的SVM (GASVM)在线预测模型比传统的GASVM预测模型预测精度有显著提高。进一步分析了预测模型不同时窗宽度对短期预测精度的影响,展示了1步~10步预测的效果,结果表明在线预测模型在不同时窗宽度下短中期(5步以内)预测效果良好且稳定。文中提出的在线预测模型可用于航空发动机性能参数的预测,实现对航空发动机未来性能变化的预警。 相似文献
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Application of SVM on satellite images to detect hotspots in Jharia coal field region of India 总被引:1,自引:0,他引:1
R.S. Gautam D. Singh A. Mittal P. Sajin 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2008,41(11):1784-1792
The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data. 相似文献
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对特征向量导数之动柔度法的补充 总被引:2,自引:1,他引:1
一种计算很多特征向量导数的动柔度法在结构处于自由状态(具有刚体运动)下,因其工作方程之系数阵为满阵,使得计算效率不如结构处于约束状态下那样好、本文移频动柔度法可以消除原动柔度法的这一缺陷,因为它的工作方程之系数阵总是具有刚度阵那样的带状特点。另外,由于对动柔度采用的移频步骤与特征方程求解时的移频技术是一致的,故而对方法的程序化极为有利。 相似文献
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《中国航空学报》2021,34(3):1-12
The excellent vectoring characteristic of Dual Synthetic Jet (DSJ) provides a new control strategy for the active flow control, such as thrust vectoring control, large area cooling, separated flow control and so on. For incompressible flow, the influence relation of source variables, such as structure parameters of actuators, driving parameters and material attributes of piezoelectric vibrating diaphragm, on the vectoring DSJ and a theoretical model are established based on theoretical and regression analysis, which are all verified by numerical simulations. The two synthetic jets can be deemed as a main flow with a higher jet velocity and a disturbing flow with a lower jet velocity. The results indicate that the influence factors contain the low-pressure area formed at the exit of the disturbing flow, which could promote the vectoring deflection, and the impact effect of the disturbing flow and the suppressive effect of the main flow with the effect of restraining the vectoring deflection. The vectoring angle is a complex parameter coupled by all source variables. The detailed theoretical model, whose error is controlled within 3.6 degrees, can be used to quantitatively assess the vectoring feature of DSJ and thus to provide a guidance for designing the control law applied in the active flow control. 相似文献
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