Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.     

Optimizing artificial neural network-based indoor positioning system using genetic algorithm

Abstract

The Global Positioning System (GPS) is expected to play an integral role in the development of digital earth; however, the GPS cannot provide positioning information in regions where a majority of the population spends their time, that is, in urban and indoor environments. Hence, alternate positioning systems that work in indoor and urban environments should be developed to achieve the vision of digital earth. Wi-Fi-based positioning systems (WPS) stand out because of the near-ubiquitous presence of the associated infrastructure and signals in indoor environments. The WPS-based fingerprinting is the most widely adopted technique for position determination, but its accuracy is lower than that of techniques such as time of arrival and angle of arrival. Improving the accuracy is still a challenging task because of the complex nature of the propagation of Wi-Fi signals. Here, a novel server-based, genetic-algorithm-optimized, cascading artificial neural network-based positioning model is presented. The model is tested in 2D and 3D indoor environments under varying conditions. The model is thoroughly investigated on a real Wi-Fi network, and its accuracy is found to be better than that of other well-known techniques. A mean accuracy of 1.9 m is achieved with 87% of the distance error within the range of 0–3 m.     

QTPV data model and algorithm and its application to geological exploration engineering

3D spatial data model and simulating are the core of 3D GIS can be adopted in different domains. A data model based on Quasi Tri-Prism Volume (QTPV) has been proposed. QTPV definition and its special cases have been discussed. Using QTPV and its special cases, irregular natural geological bodies and regular subsurface engineering can be described efficiently. The proposed model is composed of five primitives and six objects. Data structures and topological relationship of the fives primitives and three objects describing stratigraphy are designed in detail. Some schemes are designed for the QTPV modelling of stratigraphy and subsurface engineering according to modelling data. The model manipulation method of QTPV cutting by an arbitrary plane is discussed. Using VC++ 6.0 programming language integrated with SQL database and OpenGL graphic library under windows environment, a system prototype 3DGeoMV has been developed. The experiment result shows that the QTPV model is feasible and efficient in modelling subsurface engineering.     

Jacques Bertin’s legacy in information visualization and the reorderable matrix

ABSTRACT

Jacques Bertin’s legacy extends beyond the domain of cartography, and in particular to the field of information visualization where he continues to inspire researchers and practitioners. Although in the late twentieth century his books were out of print, their reedition around 2010 has steered a renewed interest and inspired new generations of researchers to reinterpret the principles of Semiology of Graphics and La Graphique in a time of interactive computers. In particular, the work of Jacques Bertin on the reorderable matrix has been very challenging in his time, and the quest to its automation has not been satisfactory to him. This article summarizes Bertin’s approach to the reorderable matrix, underlines the limitations of fully automated reordering methods, and introduces Bertifier, a hybrid system to reorder matrices using a combination of machine assistance and human control.     

基于CA模型的西安城市空间扩展模拟及误差分析

元胞自动机(CA)是城市发展动态模拟的重要工具。本文以西安市为例,利用基于遗传算法的CA模型对西安市1990-2007年的城市发展进行模拟,得到了较好的效果。结果表明,运用遗传算法建立的CA模型能够较好地模拟城市发展状态;对模拟误差分析表明,影响城市土地利用变化机制的尺度特征,城市规划调整、重大事件、重大建设项目和行政区划调整等过程,城市不同发展阶段和不同区位的扩展类型等都将影响确定转换规则、寻找最佳参数和模拟精度的结果。     

密度聚类算法在连续分布点云去噪中的应用

在原始测量获取的点云数据中,除了目标数据外,还有大量的噪声数据。噪声往往无规律地分布在目标物体周围,难以用统一数学模型区分。基于密度的聚类算法将簇定义为密度相连的点的最大集合,能发现任意形状、大小的类簇,将该算法应用在点云去噪中,能将密度分布连续点进行聚类,从中提取出目标点云。     

Onboard GRB trigger algorithms of SVOM-GRM

The Gamma-Ray Monitor （GRM） is a high energy detector onboard the future Chinese-French satellite named the Space-based multi-band astronomical Variable Object Monitor which is dedicated to studies of gamma-ray bursts （GRBs）. This paper presents an investigation of the algorithms that look for GRBs by searching for a significant increase in the photon count rate for the computer onboard GRM. The trigger threshold and trigger efficiency, which are based on a given sample of GRBs, are calculated with the algorithms. The trigger characteristics of onboard instruments GRM and ECLAIRs are also analyzed. In addition, the impact of solar flares on GRM is estimated, and a method to distinguish solar flares from GRBs is investigated.     

融合地形和土壤特征的流域蓄水容量模型

以van Genuchten模型表述的土壤水分特征曲线为基础,推导出流域单点缺水量,并结合TOPMODEL模型中地形指数与地下水位关系,建立了反映地形和土壤特征共同影响的蓄水容量模型,通过统计方法从栅格尺度蓄水容量获得流域尺度蓄水容量曲线,取代传统新安江模型中率定的蓄水容量曲线。以淮河流域紫罗山子流域为例,分析地形特征与土壤类型对蓄水容量的影响;并与实测流量过程以及原新安江模型模拟的流量过程对比,表明模型能较好地模拟场次洪水过程。模型将蓄水容量曲线显式表述,减少了新安江模型参数,为无资料地区的水文模拟提供了分析方法。     

3D Gravity Inversion by Growing Bodies and Shaping Layers at Mt. Vesuvius (Southern Italy)

To improve our knowledge of the structural pattern of Mt. Vesuvius and its magmatic system, which represents one of the three volcanoes located in the Neapolitan area (together with Campi Flegrei and Ischia; southern Italy), we analyze here the Bouguer gravity map that is already available through its interpretation by means of 2.5-dimensional modelling. We have carried out a three-dimensional interpretation using a new and original algorithm, known as ‘Layers’, that has been especially processed for this purpose. Layers works in an automatic and non-subjective way, and allows the definition of the structural settings in terms of several layers, each representing a specific geological formation. The same data are also interpreted in terms of isolated and shallow anomalous density bodies using a well tested algorithm known as ‘Growth’. We focus our inversions on the Mt. Vesuvius volcano, while globally analyzing the entire Neapolitan area, in order to investigate the deep structures, and in particular the deep extended ‘sill’ that has been revealed by seismic tomography. The final models generally confirm the global setting of the area as outlined by previous investigations, mainly for the shape and depth of the carbonate basement below Mt. Vesuvius. The presence of lateral density contrasts inside the volcano edifice is also shown, which was only hypothesized in the 2.5-dimensional inversion. Moreover, the models allow us to note a high density body that rises from the top of the carbonate basement and further elongates above sea level. This probably represents an uprising of the same basement, which is just below the volcano and which coincides with the V_P and V_P/V_S anomalies detected under the crater. The three-dimensional results also reveal that the two inversion methods provide very similar models, where the high density isolated body in the Growth model can be associated with the rising high density anomaly in the Layers model. Taking into account the density of these modelled bodies, we would also suggest that they represent solidified magma bodies, as suggested by other studies. Finally, we did not clearly detect any deep anomalous body that can be associated with the sill that was suggested by seismic tomography.     

A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems

Groundwater characterization involves the resolution of unknown system characteristics from observation data, and is often classified as an inverse problem. Inverse problems are difficult to solve due to natural ill-posedness and computational intractability. Here we adopt the use of a simulation–optimization approach that couples a numerical pollutant-transport simulation model with evolutionary search algorithms for solution of the inverse problem. In this approach, the numerical transport model is solved iteratively during the evolutionary search. This process can be computationally intensive since several hundreds to thousands of forward model evaluations are typically required for solution. Given the potential computational intractability of such a simulation–optimization approach, parallel computation is employed to ease and enable the solution of such problems. In this paper, several variations of a groundwater source identification problem is examined in terms of solution quality and computational performance. The computational experiments were performed on the TeraGrid cluster available at the National Center for Supercomputing Applications. The results demonstrate the performance of the parallel simulation–optimization approach in terms of solution quality and computational performance.