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Mehrdad Ranaie Alireza Soffianian Saeid Pourmanafi Noorollah Mirghaffari Mostafa Tarkesh 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2018,61(6):1558-1572
In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other. 相似文献
243.
The opportunistic replacement of multiple Life-Limited Parts(LLPs) is a problem widely existing in industry.The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment.This article focuses on finding a quick and effective algorithm for this problem.To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality.Based on these six reduction rules, a search algorithm is proposed.This search algorithm can identify one or several optimal solutions.A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than11.A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining tobe-replaced LLPs when determining the maintenance workscope of an aircraft engine.Therefore,the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines. 相似文献
244.
Qiaoyun Fan Xuyang Zhong 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2018,61(4):1132-1142
A novel autonomous star identification algorithm is presented in this study. In the proposed algorithm, each sensor star constructs multi-triangle with its bright neighbor stars and obtains its candidates by triangle voting process, in which the triangle is considered as the basic voting element. In order to accelerate the speed of this algorithm and reduce the required memory for star database, feature extraction is carried out to reduce the dimension of triangles and each triangle is described by its base and height. During the identification period, the voting scheme based on double feature constraints is proposed to implement triangle voting. This scheme guarantees that only the catalog star satisfying two features can vote for the sensor star, which improves the robustness towards false stars. The simulation and real star image test demonstrate that compared with the other two algorithms, the proposed algorithm is more robust towards position noise, magnitude noise and false stars. 相似文献
245.
Mazlan Hashim Samsudin Ahmad Mohd Amin Md Johari Amin Beiranvand Pour 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2013
Lineament extraction from satellite remotely sensed data has been one of the widely used applications of remote sensing in geology. In fact, recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. However, satellite remotely sensed data acquired in heavily vegetated regions such as tropical rainforest, are vulnerable to higher inherent noise levels attributed to the resultant effects of scattering by clouds and adjacency effects of highly inhomogeneous vegetation cover within the pixel dimension. In this study, we examined the effects of noise levels to lineament extraction using a fully automatic approach, consisting of a combination of edge-line detection algorithms. Ancillary information from a digitized topographic map and image classification was used to discriminate between cultural and natural lineaments from the extracted lineaments. Adapting the combination of edge detection and a line-linking algorithm, we have found the optimal parameters for automatic lineament extraction of such complex areas using Enhanced Thematic Mapper (ETM+) data. A noise level of 30% is the maximum threshold before artifacts are generated. It is therefore concluded that the combination of edge-based and line-linking digital image processing operations with the priori local optimal parameters is crucial in lineament feature extraction in heavily vegetated regions. 相似文献
246.
针对航空器地面滑行过程中出现的冲突避让问题,采用多Agent方法,在满足航空器规则与流程的基础上,设计了符合管制员思维的分布式多Agent模型.对每个Agent的功能以及Agent之间的交互进行了详细的描述,同时利用事件驱动(event-condition-action)语言描述了Agent推理过程.最后利用Anylogic仿真平台对多Agent模型进行验证,验证结果证明采用规则的算法可智能有效地避免航空器冲突,且符合航空器的运行流程. 相似文献
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248.
研究了准确反映Costas编码信号特点的关键参数集合。基于循环谱相关密度估计方法,分析了Costas编码的循环谱特征及其与辐射源侍号参数的对应关系,提出了一种没有先验知识条件下Costas编码截获信号特征提取方法。通过对典型的Costas编码信号参数提取归一化均方根误差的计算,验证了该算法的有效性。 相似文献
249.
高分辨率遥感图像分割在军事、民用等领域具有良好的应用前景,但由于复杂的背景条件以及干扰物的遮挡,导致现有算法无法较好地从遥感影像中提取道路细节信息。研究基于改进U Net网络模型,提出了MDAU-Net(multi dimension attention U-Net)网络结构模型,通过对U-Net网络结构加深至七层结构来提升精细分割道路的能力;并提出了一种多维注意力模块MD-MECA(multi dimension modified efficient channel attention),将其添加至编码部分的特征传递步骤中,以达到对编码部分的特征传递进行优化的目的;其中利用DropBlock与Batch Normalization解决网络训练过程中出现的过拟合。试验结果表明:改进后算法可以有效提升道路的提取效果,在测试集上的准确率达到了97.04%。 相似文献
250.
高动态情况下,星点像斑在星敏感器探测器上会呈现出拖尾现象,星点质心无法被准确提取。针对上述难点,本文提出了一种高动态条件下基于差异哈希算法的星点质心提取方法。该方法分为三步:第一,建立动态星斑的数学模型;第二,利用差异哈希算法和汉明距离实现星跟踪窗口内星体目标粗定位;第三,在粗定位区域使用阈值分割与连通域法提取星点质心。实验结果表明,该方法能够适应各种长度的曝光时间,并实现星敏感器在3(°)/s条件下的稳定跟踪。在曝光时间50ms,角速度3(°)/s的条件下,星对角距误差为13”,平均提取率为96%,相比于传统方法,分别提高了29.6%和22.9%。 相似文献