基于Stacking集成学习的恒星/星系分类研究

机器学习在当今诸多领域已经取得了巨大的成功,但是机器学习的预测效果往往依赖于具体问题.集成学习通过综合多个基分类器来预测结果,因此,其适应各种场景的能力较强,分类准确率较高.基于斯隆数字巡天(Sloan Digital Sky Survey,SDSS)计划恒星/星系中最暗源星等集分类正确率低的问题,提出一种基于Stacking集成学习的恒星/星系分类算法.从SDSS-DR7(SDSS Data Release 7)中获取完整的测光数据集,并根据星等值划分为亮源星等集、暗源星等集和最暗源星等集.仅针对分类较为复杂且困难的最暗源星等集展开分类研究.首先,对最暗源星等集使用10折嵌套交叉验证,然后使用支持向量机(Support Vector Machine,SVM)、随机森林(Random Forest,RF)、XGBoost(eXtreme Gradient Boosting)等算法建立基分类器模型;使用梯度提升树(Gradient Boosting Decision Tree,GBDT)作为元分类器模型.最后,使用基于星系的分类正确率等指标,与功能树(Function Tree,FT)、SVM、RF、GBDT、XGBoost、堆叠降噪自编码(Stacked Denoising AutoEncoders,SDAE)、深度置信网络(Deep Belief Network,DBN)、深度感知决策树(Deep Perception Decision Tree,DPDT)等模型进行分类结果对比分析.实验结果表明,Stacking集成学习模型在最暗源星等集分类中要比FT算法的星系分类正确率提高了将近10%.同其他传统的机器学习算法、较强的提升算法、深度学习算法相比,Stacking集成学习模型也有较大的提升.     

ASO-S卫星工程科学应用系统的数据库设计

先进天基太阳天文台(Advanced Space-based Solar Observatory, ASO-S)卫星是我国首颗太阳观测卫星, 主要观测太阳耀斑和日冕物质抛射以及产生它们的磁场结构. ASO-S卫星的科学应用系统是科学卫星工程的6大系统之一, 它连接科学用户和卫星数据, 为将卫星的科学数据转化为科学成果提供保障. 科学应用系统的数据库是连接软件与海量数据的枢纽, 为科学数据生产和用户服务及运行提供数据层的支撑. 介绍了科学应用系统的数据库架构设计、数据库的选择以及数据库性能优化和表样例. 这里的数据库包括观测计划、工程参数、运维日志、科学数据、定标数据和特征事件识别等数据库. 这些数据库的建设将为ASO-S卫星工程科学应用系统的顺利运行提供数据支撑, 也可以为未来其他科学卫星类似数据库的搭建提供参考和借鉴.     

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.     

Formation of Carbon-Enhanced Metal-Poor RR Lyrae Stars

Carbon-enhanced metal-poor (CEMP) stars are considered to be related to the first generation of stars, and responsible for the chemical evolution of the early Galaxy. More than half of them are in binaries, and could be explained by the binary evolution, but the formation channel of them is still not fully understood. Among the hundreds of CEMP stars, there are nine CEMP RR Lyrae stars identified, and at least seven of which are very likely not binaries. The usual binary star evolution channel is difficult to produce such a single star, particularly that of carbon enrichment. One way in which such a single star might be produced is the merger of a helium white dwarf with a Hertzsprung gap (HG) star. We use a stellar evolution program to calculate the models of the merger remnants, and find that the models can reproduce the observed distribution of these CEMP single RR Lyrae stars in terms of surface temperature, gravity, and carbon abundance. Hence, it is extremely possible that the helium white dwarf and HG star merger model is one of the formation channels of the metal-poor carbon-rich RR Lyrae stars.     

遗传算法优化的BP神经网络卫星钟差预报

针对BP (Back Propagation)神经网络模型预测卫星钟差中权值和阈值的最优化问题, 提出了基于遗传算法优化的BP神经网络卫星钟差短期预报模型, 给出了遗传算法优化BP神经网络的基本思想、具体方法和实施步骤. 为验证该优化模型的有效性和可行性, 利用北斗卫星导航系统(BeiDou navigation satellite system, BDS)卫星钟差数据进行钟差预报精度分析, 并将其与灰色模型(GM(1,1))和BP神经网络模型预报的结果比较分析. 结果表明: 该模型在短期钟差预报中具有较好的精度, 优于GM(1,1)模型和BP神经网络模型.     

基于斩波轮技术的K波段接收机噪声校准研究

接收机是射电天文中用于探测微弱射电信号的重要接收设备.接收机的强度校准就是将接收机对射电源的响应转换为天文意义上的流量密度.常规方法就是使用经典的冷热负载法,将接收机自身的强度响应转换为一个等效的温度值,之后再据此对射电源做进一步标定.通过搭建基于斩波轮技术的K波段接收机强度校准平台,使用斩波轮法测试K波段常温接收机的噪声温度,并与传统冷热负载法的测试结果进行比对.结果显示,在晴好天气条件下,斩波轮法在30°、90°仰角下噪声温度的最大测试误差为7.5%和8.4%,可以很好地应用于实际噪声温度测试中;但在5°仰角测试中,由于过低仰角引入了地面噪声,使得斩波轮法的测试误差上升至20%–30%之间而无法使用.希望在此基础上进一步开展K波段天空亮温度的理论计算与实测,从而完善斩波轮技术的应用,使之可以满足在不同气象条件下的噪声校准测试需求.     

城镇化与生态环境耦合的动态模拟——研究进展与展望

Urbanization and eco-environment coupling is a research hotspot.Dynamic simulation of urbanization and eco-environment coupling needs to be improved because the processes of coupling are complex and statistical methods are limited.Systems science and cross-scale coupling allow us to define the coupled urbanization and eco-environment system as an open complex giant system with multiple feedback loops.We review the current state of dynamic simulation of urbanization and eco-environment coupling and find that:(1)The use of dynamic simulation is an increasing trend,the relevant theory is being developed,and modeling processes are being improved;(2)Dynamic simulation technology has become diversified,refined,intelligent and integrated;(3)Simulation is mainly performed for three aspects of the coupling,multiple regions and multiple elements,local coupling and telecoupling,and regional synergy.However,we also found some shortcomings:(1)Basic theories are inadequately developed and insufficiently integrated;(2)The methods of unifying systems and sharing data are behind the times;(3)Coupling relations and the dynamic characteristics of the main driving elements are not fully understood or completely identified.Additionally,simulation of telecoupling does not quantify parameters and is not systemically unified,and therefore cannot be used to represent spatial synergy.In the future,we must promote communication between research networks,technology integration and data sharing to identify the processes governing change in coupled relations and in the main driving elements in urban agglomerations.Finally,we must build decision support systems to plan and ensure regional sustainable urbanization.     

鱼类摄食生态研究的理论及方法

综合分析了鱼类摄食生态研究的理论，方法及其应用中的诸多问题：胃含物分析法，营养生境及食物重叠，食物链与食物网，营养结构与营养级，摄食器官的形态特征与摄食行为的关系，食物选择以及生理生太因子对鱼类摄食的影响；提出了食物排序的概念、优势度指数Ｄ及其判定公式，并以此比较客观地建立了摄食生态相似的鱼类群落主次食物的划分标准。     

海洋中铁的来源、形态和对初级生产力的限制作用

在海洋中,铁和Ｎ、Ｐ等主营养盐一样,也是一种限制浮游植物初级生产力的重要因素。由于铁是一种化学活性较高的元素,所以海水中铁的存在形态、来源及沉降会直接影响其生物可利用性。目前人们一般采用预富集／原子吸收法（ＡＡＳ）或是借助于电分析技术（如催化极谱）来测定海水中的铁。     

河口海岸环境沉积速率研究方法

沉积速率是河口海岸沉积环境的重要参数，对于河口海岸地质历史时期沉积速率的研究，大多采用^14C年龄值计算；现代河口海岸沉积速率的研究方法较多，常见的有河流输沙法，海图对比法，GIS法，放射性同位素测年法等。^14C法结合考古，孢粉等方法，能比较真实地反映河口海岸地质历史时期的沉积速率，对于现代河口海岸沉积，由于GIS和DEM方法的发展和计算机功能的支持，使海图对比的方法克服了手工带来的误差，目前仍然是一种可以使用的方法。放射性同位素^210Pb,^137Cs,^239,240Pu法使沉积速率的计算趋于定量化，在一定时间区域范围内，多种同位素测年同时运用，相互印证，从而使河口现代沉积速率更加准确。