基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

Coma Morphology of Three Non-periodic Comets

The coma morphology and short-term evolution was investigated of three non-periodic comets in retrograde orbits, C/2001 Q4 (NEAT), C/2002 T7 (LINEAR), and C/2003 K4 (LINEAR). All three comets display distinct coma features, which were very different from one comet to the next and remained rather constant in shape during the observational period. A single, broad feature perpendicular to the sun-tail direction dominated the coma of C/2003 K4 in all used filters (B,V,R,I), whereas the coma of Comet C/2002 T7 exhibited different features in blue and red filters. C/2001 Q4 showed rather complex coma morphology with clear short-term variability in coma brightness. Therefore, these non-periodic comets neither show a featureless coma nor any similarities of the features detected. The overall distribution of coma material was investigated from the shape of radial coma profiles averaged around the comet nucleus. For C/2001 Q4 and C/2002 T7, the slopes fitted to the linear part of these profiles are flatter in the blue than in the red, which can be explained by the presence of coma gas. For C/2003 K4 no such difference is indicated in the May observations (r = 2.3 AU), while in July (r = 1.7 AU) the profiles in the B-filter are flatter than in V, R, and I, hence gas contamination was relevant at least in the B filter. The R and I filter images were used to determine approximate Afρ values of each comet as a function of time.     

含有集约束向量极值问题的最优性条件

在序线性拓扑空间里研究了含有集约束向量极值问题的最优性条件,并建立了充分性和必要性条件.     

Geometric Derivation of the Delaunay Variables and Geometric Phases

We derive the classical Delaunay variables by finding a suitable symmetry action of the three torus T³ on the phase space of the Kepler problem, computing its associated momentum map and using the geometry associated with this structure. A central feature in this derivation is the identification of the mean anomaly as the angle variable for a symplectic S ¹ action on the union of the non-degenerate elliptic Kepler orbits. This approach is geometrically more natural than traditional ones such as directly solving Hamilton–Jacobi equations, or employing the Lagrange bracket. As an application of the new derivation, we give a singularity free treatment of the averaged J ₂-dynamics (the effect of the bulge of the Earth) in the Cartesian coordinates by making use of the fact that the averaged J ₂-Hamiltonian is a collective Hamiltonian of the T³ momentum map. We also use this geometric structure to identify the drifts in satellite orbits due to the J ₂ effect as geometric phases.     

用遗传算法解算病态方程

对应用遗传算法解决病态方程问题进行了探讨。利用拟合法而不是通过法方程求解参数，从而避免了法方程系数求逆，使病态方程的解答有了较好的结果。通过模拟计算并和其他方法进行比较，证明该方法是可行的和有效的。     

Magnetotelluric investigations for imaging electrical structure of Garhwal Himalayan corridor,Uttarakhand, India

Magnetotelluric investigations have been carried out in the Garhwal Himalayan corridor to delineate the electrical structure of the crust along a profile extending from Indo-Gangetic Plain to Higher Himalayan region in Uttarakhand, India. The profile passing through major Himalayan thrusts: Himalayan Frontal Thrust (HFF), Main Boundary Thrust (MBT) and Main Central Thrust (MCT), is nearly perpendicular to the regional geological strike. Data processing and impedance analysis indicate that out of 44 stations MT data recorded, only 27 stations data show in general, the validity of 2D assumption. The average geoelectric strike, N70°W, was estimated for the profile using tensor decomposition. 2D smooth geoelectrical model has been presented, which provides the electrical image of the shallow and deeper crustal structure. The major features of the model are (i) a low resistivity (<50Ωm), shallow feature interpreted as sediments of Siwalik and Indo-Gangetic Plain, (ii) highly resistive (> 1000Ωm) zone below the sediments at a depth of 6 km, interpreted as the top surface of the Indian plate, (iii) a low resistivity (< 10Ωm) below the depth of 6 km near MCT zone coincides with the intense micro-seismic activity in the region. The zone is interpreted as the partial melting or fluid phase at mid crustal depth. Sensitivity test indicates that the major features of the geoelectrical model are relevant and desired by the MT data.     

Mapping ambivalence: Exploring the geographies of community change and rails-to-trails development using photo-based Q method and PPGIS

As the literature on trail development suggests, recreational trail projects can generate conflicts and controversies, particularly when built on abandoned rail corridors through developed areas. These conflicts are often understood as “not in my back yard” (NIMBY) reactions, suggesting a spatial proximity to conflict which increases as one draws closer to the proposed trail. This research seeks to understand local residents’ perceptions and reactions to recreational trail development in the City of Delaware (Ohio, USA). It addresses two spatially infused questions: Does the potential for conflict related to trail development increase as people live closer to a potential trail (the NIMBY factor)? Can important qualitative factors about favorable and unfavorable land uses including potential recreational trail sites be defined using a participatory methodology and then represented in GIS? The study used a mixed-method approach to collect and analyze qualitative data from a group of local residents. Each participant was interviewed and asked to sort 19 pictures related to trail development. After each of the sorts, participants were asked to explain why they ranked the pictures the way they did. Results of the picture sorts were then analyzed using Q method and mapped with GIS. The results show that spatial proximity matters in the context of trail development and potential NIMBY reactions to trails. Significant differences were found in the picture sorts that reveal the importance of proximity and location, although in a manner contrary to the assumptions in the writings on rails-to-trails. Through combining qualitative methods, Q analysis and PPGIS analysis, the research shows that qualitative place-based studies are capable of generating insights about the complexities of situated geographic change such as recreational trail development.     

GPS变形监测平差计算及不确定度分析

全球定位系统（GPS）是一种全天候、高精度的连续定位系统,它以速度快、方法灵活多样、操作简便等优势被广泛应用于工程测量和变形监测中。结合水厂铁矿GPS边坡变形监测实例,对GPS监测网的星历预报、基线向量平差计算、网平差计算、结果及残差不确定度进行了细致分析研究,以验证GPS技术在边坡变形监测中的可靠性和精度。     

基于AGA的SVM需水预测模型研究

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.