Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.     

基于多元对应分析的国家地质公园综合价值及分类

目前地质公园的分类难以针对具有多重价值属性的各类地质公园提出行之有效的分类管理模式。提出基于综合价值的国家地质公园分类模式,建立了国家地质公园综合价值评价指标,通过问卷调查与小组讨论获取了35个国家地质公园的量化综合价值评价指标数据,应用多元对应分析对量化数据进行统计处理,最后将35个国家地质公园分为禀赋型地质公园、生态型地质公园、成熟型地质公园、均衡型地质公园和发展型地质公园五大类,为国家地质公园分类管理提供依据。     

长春地区粉质黏土导热系数与其物性参数相关性研究

为研究导热系数与影响因素之间的相关关系,建立导热系数的推算公式,以长春地区粉质黏土为研究对象,对原状土样的导热系数与其物理参数之间的相关性进行回归分析。制作9个重塑土样,测其相关的参数值,以验证回归方程的适用性。结果表明,回归分析建立导热系数与2个物理参数之间的关系式不成立;考虑天然密度、含水率和孔隙度为自变量,其分别对应的相关性系数T检验显著值(Sig)都0. 05,复决定系数为0. 886,建立的回归方程成立,自变量能准确解释因变量的变化,且含水率与导热系数呈负相关,天然密度和孔隙度呈正相关。重塑土样相关参数代入回归方程得到的导热系数值与实验实测值之间相对误差低于4%,验证了该回归方程的普遍性和适用性。     

逻辑回归模型在边坡稳定性分析中的应用

采用逻辑回归模型和确定性系数CF建立概率模型,使用收集到的22个边坡实例,将重度、内聚力、坡角、坡高、内摩擦角和孔隙压力比六个影响因子作为自变量,边坡状态作为因变量,应用SPSS取不同的滑坡概率P与不滑坡概率1-P的比值的自然对数Z进行回归分析。将获得的滑坡概率拟合模型反馈到样本参数上,对比其误差,选取Z=±10时的函数模型对另外8组边坡进行验证,证明预测模型的合理性。     

Application of Geochemistry and VNIR Spectroscopy in Mapping Heavy Metal Pollution of Stream Sediments in the Takab Mining Area, NW of Iran

This study considered the possibility of using visible and near infrared (VNIR) spectral absorption feature parameters (SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of the Takab area. In total, 60 sediment samples were collected along main streams draining from the mining districts and tailing sites, in order to measure the concentration of As, Co, V, Cu, Cr, Ni, Hg, Ti, Pb and Zn and the reflectance spectra (350–2500 nm). The quantitative relationship between SAFPs (Depth500nm, R610/500nm, R1344/778nm, Area500nm, Depth2200nm, Area2200nm, Asym2200nm) and geochemical data were assessed using stepwise multiple linear regression (SMLR) and enter multiple linear regression (EMLR) methods. The results showed a strong negative correlation between Ni and Cr with Area2200nm, a significant positive correlation between As and Asym2200nm, Ni and Co with Depth2200nm, as well as Co, V and total values with Depth500nm. The EMLR method eventuated in a significant prediction result for Ni, Cr, Co and As concentrations based on spectral parameters, whereas the prediction for Zn, V and total value was relatively weak. The spatial distribution pattern of geochemical data showed that mining activities, along with the natural weathering of base metal occurrences and rock units, has caused high concentrations of heavy metals in sediments of the Sarough River tributaries.     

Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules

The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.     

基于逻辑回归的四川青川县区域滑坡灾害预警模型

四川省青川县滑坡灾害群发,点多面广,区域滑坡灾害预警是有效防灾减灾的重要手段,预警模型是成功预警的核心。由于研究区滑坡诱发机理复杂、调查监测大数据及分析方法不足等原因,传统区域地质灾害预警模型存在预警精度有限、精细化不足等问题。文章在青川县地质灾害调查监测和降水监测成果集成整理与数据清洗基础上,构建了青川县区域滑坡灾害训练样本集,样本集包括地质环境、降雨等27个输入特征属性和1个输出特征属性,涵盖了青川县近9年（2010—2018年）全部样本,数量达1 826个（其中,正样本613个,负样本1 213个）。基于逻辑回归算法,对样本集进行5折交叉验证学习训练,采用贝叶斯优化算法进行模型优化,采用精确度、ROC曲线和AUC值等指标校验模型准确度和模型泛化能力。其中,ROC曲线也称为“受试者工作特征”曲线;AUC值表示ROC曲线下的面积。校验结果显示,基于逻辑回归算法的模型训练结果准确率和泛化能力均较好（准确率94.3%,AUC为0.980）。开展区域滑坡实际预警时,按训练样本特征属性格式,输入研究区各预警单元27个特征属性,调用预先学习训练好的模型,输出滑坡灾害发生概率,根据输出概率分段确定滑坡灾害预警等级。当输出概率P≥40%且P<60%时,发布黄色预警;当输出概率P≥60%且P<80%时,发布橙色预警;当输出概率P≥80%时,发布红色预警。     

矿石体重回归分析在新疆乌宗布拉克矿区的应用研究

在资源储量估算的过程中,矿石小体重的准确与否将直接影响到资源储量估算的客观程度。对矿石小体重的准确预测将需要通过大量的统计分析工作,传统的方法是利用矿石小体重的算术平均值进行估算矿床资源储量,并没有考虑到多矿种对矿石小体重的影响程度。本文利用Excel软件"数据分析"的"回归"功能模块,对实验室所测定的矿石小体重值与其对应品位进行二元线性回归分析,快速、准确地构建矿石体重与其品位的数学模型,从而为资源储量估算提供了更客观、更科学的矿石体重模型。     

中国东部夏季降水与气温的联合EOF分析

采用JEOF等方法分析中国东部夏季降水和气温的协同变化时空分布特征,结果表明:当时间系数为正时,第1典型场降水型态从北向南(下同)呈"++-"分布,气温表现为冷异常,500 hPa回归场在中纬度地区呈显著低压异常,SST回归场表现为太平洋海域呈西北-东南的分布;第2典型场降水呈"+-"分布,气温则呈"-+"分布;第3典型场降水分布呈中间型,气温场呈"-+"分布。     

基于偏最小二乘回归的区域换式风速预报订正技术研究

利用偏最小二乘回归技术,将预报产品作为自变量,相应的自动气象站观测资料作为因变量,对2013-2016年冬季浙江省中尺度区域模式预报近地面风速进行订正和评估。所选956站中多数站点风速订正后有所改善,通过定量分析可知浙江西部地区整体改善效果最好,其中效果明显站点占91.7%;中部地区改善效果明显站点占86.5%;东部沿海地区改善效果略差,明显改善的站点占67%。各地级市整体表现均不错,除舟山地区为49.9%外,其他地区风速改善比例均超过50%。选取2017年1月20日浙江东北地区沿海大风过程分析发现订正后的风速与观测风速更为接近,在定海大岛站点(靠里)中表现尤为明显,订正后的结果具有显著参考价值。