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1.
Classification and regression techniques are among the most used tools by chemometricians.Withclassification,the two classic methods are discriminant analysis and SIMCA.In this paper we discuss theconnection between these two methods and introduce two new ones of the same family:DASCO(discriminantanalysis with shrunken covariances)and RDA(regularized discriminant analysis).We demonstrate on bothsimulated and real data sets that their performance is superior to the old favorites.This is especially truein small-sample/high-dimension settings typical in chemistry. 相似文献
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DOMINIQUE BERTRAND PHILIPPE COURCOUX JEAN-CLAUDE AUTRAN REGIS MERITAN PAUL ROBERT 《地理学报(英文版)》1990,(6)
Continuous digitalized signals such as spectra,electrophoregrams or chromatograms generally have alarge number of data points and contain redundant information.It is therefore troublesome performingdiscriminant analysis without any preliminary selection of variables.A procedure for the application ofcanonical discriminant analysis(CDA)on this kind of data is studied.CDA can be presented as asuccession of two principal component analyses(PCAs).The first is performed directly on the raw dataand gives PC scores.The second is applied on the gravity centres of each qualitative group assessed onthe normalized PC scores.A stepwise procedure for selection of the relevant PC scores is presented.Themethod has been tested on an illustrative collection of 165 size-exclusion high-performance(SE-HPLC)chromatograms of proteins of wheat belonging to 55 genotypes and grown in three locations.Thediscrimination of the growing locations was performed using seven to nine PC scores and gave more than86% accurate classifications of the samples both in the training sets and the verification sets.Thegenotypes were also rather well identified,with more than 85% of the samples correctly classified.Thestudied method gives a way of assessing relevant mathematical distances between digitalized signalsaccording to qualitative knowledge of the samples. 相似文献
3.
It is possible to reconstruct the past variation of an environmental variable from measured historical indicators when the
modern values of the variable and the indicators are known. In a Bayesian statistical approach, the selection of a prior probability
distribution for the past values of the environmental variable can then be crucial and the selection therefore should be made
carefully. This is particularly the case when the data are noisy and the statistical model used is complex since the influence
of the prior on the results can then be especially strong. It can be difficult to elicit the prior probability distribution
from the available information, since usually there are no measured data on the past values of the variable one wants to reconstruct
and different reconstructions are typically consistent with each other only at a coarse level. To overcome these difficulties
we propose to use a non-informative smoothing prior, possibly in combination with an informative prior, that simply penalizes
for roughness of the reconstruction as measured by the variability of its values. We believe that it can sometimes be easier
to set an overall prior distribution on the roughness than to agree on a prior for the actual values of the reconstructed
variable. Note that by using a smoothing prior one incorporates into the model itself the smoothing step usually done before
or after the actual numerical reconstruction. Another idea proposed in this paper is to integrate the reconstruction model
with a multiscale feature analysis technique known as SiZer. Multiscale analysis of the posterior distribution of the reconstructed
variable makes it possible to infer its statistically significant features such as trends, maxima and minima at several different
time scales. While only temperature is considered in this paper, the technique can be applied to other environmental variables. 相似文献
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Jung-Hong Hong Min-Lang Huang 《International journal of geographical information science》2017,31(6):1178-1197
Geographic information system (GIS) users rely heavily on the versatile operations of GIS software and the abundant variety of geospatial data from different resources to satisfy their application requirements. However, the convenient use of GIS software has resulted in users easily ignoring the threat of data misuse because of the lack of understanding of data quality. Here we argue that data quality considerations must be coherently assimilated into the GIS operation design to visually present helpful information and ensure the accuracy of data for decision making. Data completeness is selected in this paper to demonstrate how the use of data quality information opens a new dimension to the design of future GIS software. We propose a new model for the representation, analysis, and visualization of data completeness information. With the brand new quantitative measures and informative visual approach, understanding of the data completeness of the illustrated contents in the map interface is enhanced, and inappropriate dataset selection can be effectively prevented. Thus, this paper presents an innovative, integrated and geospatial concept of future GIS operation design, where users are constantly aware of the continuously changing status of data quality based on formalized and quantitative data quality theories. 相似文献
6.
Peter Foley 《International journal of geographical information science》2013,27(4):633-661
Geographically weighted spatial statistical methods are a family of spatial statistical methods developed to address the presence of non-stationarity in geographical processes, the so-called spatial heterogeneity. While these methods have recently become popular for analysis of spatial data, one of their characteristics is that they produce outputs that in themselves form complex multi-dimensional spatial data sets. Interpretation of these outputs is therefore not easy, but is of high importance, since spatial and non-spatial patterns in the results of these methods contain clues to causes of underlying non-stationarity. In this article, we focus on one of the geographically weighted methods, the geographically weighted discriminant analysis (GWDA), which is a method for prediction and analysis of categorical spatial data. It is an extension of linear discriminant analysis (LDA) that allows the relationship between the predictor variables and the categories to vary spatially. This produces a very complex data set of GWDA results, which include on top of the already complex discriminant analysis outputs (e.g. classifications and posterior probabilities) also spatially varying outputs (e.g. classification function parameters). In this article, we suggest using geovisual analytics to visualise results from LDA and GWDA to facilitate comparison between the global and local method results. For this, we develop a bespoke visual methodology that allows us to examine the performance of global and local classification method in terms of quality of classification. Furthermore, we are also interested in identifying the presence (or absence) of non-stationarity through comparison of the outputs of both methods. We do this in two ways. First, we visually explore spatial autocorrelation in both LDA and GWDA misclassifications. Second, we focus on relationships between the classification result and the independent variables and how they vary over space. We describe our visual analytic system for exploration of LDA and GWDA outputs and demonstrate our approach on a case study using a data set linking election results with a selection of socio-economic variables. 相似文献
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基于免疫进化算法的逻辑斯谛曲线水环境质量综合评价模型 总被引：2，自引：0，他引：2
在对现有水环境质量评价方法进行分析的基础上,提出用一种新型的优化算法———免疫进化算法应用于非线形的水环境质量综合评价模型,即逻辑斯谛曲线的参数优化问题,其结果优于目前广泛应用的遗传算法,从而建立了一种新的数学模型。实例研究表明,该算法易于操作、快速收敛于全局最优解,可用于解决复杂的优化问题,具有较为广阔的应用前景。 相似文献
9.
Probabilistic landslide hazard assessment at the basin scale 总被引：32，自引：9，他引：32
Fausto Guzzetti Paola Reichenbach Mauro Cardinali Mirco Galli Francesca Ardizzone 《Geomorphology》2005,72(1-4):272-299
We propose a probabilistic model to determine landslide hazard at the basin scale. The model predicts where landslides will occur, how frequently they will occur, and how large they will be. We test the model in the Staffora River basin, in the northern Apennines, Italy. For the study area, we prepare a multi-temporal inventory map through the interpretation of multiple sets of aerial photographs taken between 1955 and 1999. We partition the basin into 2243 geo-morpho-hydrological units, and obtain the probability of spatial occurrence of landslides by discriminant analysis of thematic variables, including morphological, lithological, structural and land use. For each mapping unit, we obtain the landslide recurrence by dividing the total number of landslide events inventoried in the unit by the time span of the investigated period. Assuming that landslide recurrence will remain the same in the future, and adopting a Poisson probability model, we determine the exceedance probability of having one or more landslides in each mapping unit, for different periods. We obtain the probability of landslide size by analysing the frequency–area statistics of landslides, obtained from the multi-temporal inventory map. Assuming independence, we obtain a quantitative estimate of landslide hazard for each mapping unit as the joint probability of landslide size, of landslide temporal occurrence and of landslide spatial occurrence. 相似文献
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TRIZ:研究人地关系问题的一种新的理论与方法 总被引：1，自引：0，他引：1
我国地理学家认为应该加强人地关系问题的综合集成研究。目前我国人地关系问题研究, 在技术设计解决问题上尚属空白, 为此, 引入TRIZ.TRIZ解决问题的基本观点有技术系统、技术矛盾、创新等级、理想状态;解决系统中矛盾问题的理论基础是技术系统演变的8个法则。TRIZ解决问题的方法主要是使用分析工具和知识库, 分析工具主要包括矛盾矩阵、物-场模型与标准解法、ARIZ、需求功能分析;知识库主要包括40个创新原理、解决矛盾问题的原则、76个标准解、效应数据库。TRIZ解决问题的程序主要是识别问题、选择工具和方法、解决矛盾问题的方案评估。以武汉市青山区为案例, 探讨了TRIZ解决区域人地关系矛盾问题的思路、理论、方法和强大功能, 构建了TRIZ理论解决区域人地关系问题的逻辑范式。结论指出, TRIZ不仅适用于技术领域, 也适用于非技术领域, 将为今后人地关系问题研究提供一种新视野、新理论、新方法。 相似文献
11.
空间集聚与外商直接投资的区位选择——基于珠江三角洲地区的实证分析 总被引：7，自引：0，他引：7
在揭示改革开放以来外商直接投资在珠江三角洲空间分布呈现向珠江三角洲集聚的基础上,采用动态局部调整模型对1992～2003年外商直接投资在珠江三角洲9个地级城市中的区位选择影响因素进行了实证分析,结果表明外商直接投资在广东省的区位选择,除受到城市区位特性因素的影响外,更为主要的影响因素是外商直接投资的集聚效应,即与城市已有的外商直接投资数量呈正相关,存在外商直接投资的空间集聚效应,进一步的提出了通过产业集群培育和升级促进珠江三角洲城市外商直接投资持续集聚的策略. 相似文献
12.
XIN M.TU 《地理学报(英文版)》1991,(4)
Rank estimation by canonical correlation analysis in multivariate statistics has been proposed as analternative approach for estimating the number of components in a multicomponent mixture.Amethodological turning point of this new approach is that it focuses on the difference in structure ratherthan in magnitude in characterizing the difference between the signal and the noise.This structuraldifference is quantified through the analysis of canonical correlation,which is a well-established datareduction technique in multivariate statistics.Unfortunately,there is a price to be paid for having thisstructural difference:at least two replicate data matrices are needed to carry out the analysis.In this paper we continue to explore the potential and to extend the scope of the canonical correlationtechnique.In particular,we propose a bootstrap resampling method which makes it possible to performthe canonical correlation analysis on a single data matrix.Since a robust estimator is introduced to makeinference about the rank,the procedure may be applied to a wide range of data without any restrictionon the noise distribution.Results from real as well as simulated mixture samples indicate that when usedin conjunction with this resampling method,canonical correlation analysis of a single data matrix isequally efficient as of replicate data matrices. 相似文献
13.
Michael Batty Jake Desyllas Elspeth Duxbury 《International journal of geographical information science》2013,27(7):673-697
Small-scale spatial events are situations in which elements or objects vary in such a way that temporal dynamics are intrinsic to their representation and explanation. Some of the clearest examples involve local movement, from conventional traffic modeling to disaster evacuation where congestion, crowding, panic, and related safety issues are key features. We propose that such events can be simulated using new variants of pedestrian model, which embody ideas about how behavior emerges from the accumulated interactions between small-scale objects. We present a model in which the event space is first explored by agents using ‘swarm intelligence’. Armed with information about the space, agents then move in unobstructed fashion to the event. Congestion and problems over safety are then resolved through introducing controls in an iterative fashion, rerunning the model until a ‘safe solution’ is reached. The model has been developed to simulate the effect of changing the route of the Notting Hill Carnival, an annual event held in west central London over 2 days in August each year. One of the key issues in using such simulation is how the process of modeling interacts with those who manage and control the event. As such, this changes the nature of the modeling problem from one where control and optimization is external to the model to one where it is intrinsic to the simulation. 相似文献
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Michele Crosetto Stefano Tarantola 《International journal of geographical information science》2013,27(5):415-437
A novel procedure to analyse the uncertainty associated to the output of GIS-based models is presented. The procedure can handle models of any degree of complexity that accept any kind of input data. Two important aspects of spatial modelling are addressed: the propagation of uncertainty from model inputs and model parameters up to the model output (uncertainty analysis); and the assessment of the relative importance of the sources of uncertainty in the output uncertainty (sensitivity analysis). Two main applications are proposed. The procedure allows implementation of a GIS-based model whose output can reliably support the decision process with an optimized allocation of resources for spatial data acquisition. This is possible in low cost strategy, based on numerical simulations on a small prototype of the GIS-based model. Furthermore, the procedure provides an effective model building tool to choose, from a group of alternative models, the best one in terms of cost-benefit analysis. A comprehensive case study is described. It concerns the implementation of a new GIS-based hydrologic model, whose goal is providing near real-time flood forecasting. 相似文献
17.
A. M. García I. Santé M. Boullón R. Crecente 《International journal of geographical information science》2013,27(8):1593-1611
Cellular automata (CA) stand out among the most commonly used urban models for the simulation and analysis of urban growth because of their ability to reproduce complex dynamics, similar to those found in real cities, from simple rules. However, CA models still have to overcome some shortcomings related to their flexibility and difficult calibration. This study combines various techniques to calibrate an urban CA that is based on one of the most widely used urban CA models. First, the number of calibration parameters is reduced by using various statistical techniques, and, second, the calibration procedure is automated through a genetic algorithm. The resulting model has been assessed by simulating the urban growth of Ribadeo, a small village of NW Spain, characterized by low, slow urban growth, which makes the identification of urban dynamics and consequently the calibration of the model more difficult. Simulation results have shown that, by automating the calibration procedure, the model can be more easily applied and adapted to urban areas with different characteristics and dynamics. In addition, the simulations obtained with the proposed model show better values of cell-to-cell correspondence between simulated and real maps, and the values for most spatial metrics are closer to real ones. 相似文献
18.
H. Jesse Walker 《自然地理学》2013,34(4):373-375
The focus of this research is the development of a model which explains channel pattern variability in streams. Since channel pattern is commonly regarded as a qualitative phenomenon, the research employs a logistic regression model, which is advocated as an alternative to traditional graphic/discriminant analysis, since the concepts of threshold and instability have very natural expressions in the logistic regression framework. The results demonstrate that channel gradient and mean discharge can effectively explain channel pattern (i.e., whether the channel is single or multithreaded) in an environment where there is a small range of bed material size. Sediment sorting is also shown to be related to channel pattern in the study environment. Models using valley gradient rather than channel gradient are shown to be distinctly inferior, and no advantage is found in using a stream power measure as opposed to separate gradient and discharge measures. [Key Words: fluvial geomorphology, stream channels, channel patterns, models.] 相似文献
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Tarek Rashed John Weeks 《International journal of geographical information science》2013,27(6):547-576
Assessing urban vulnerability to natural hazards such as earthquakes can be regarded as an ill-structured problem (i.e. a problem for which there is no unique, identifiable, objectively optimal solution). A review of the literature indicates a number of contrasting definitions of what vulnerability means, as well as numerous conflicting perspectives on what should or should not be included within the broad assessment of vulnerability in cities. This paper reports on the findings from a project in which a GIS methodology has been developed to assess urban vulnerability through a spatial analytical procedure. First, we highlight the deficiencies of current GIS approaches to urban vulnerability analysis and discuss the ill-structured nature of the vulnerability problem. We then propose a working definition for vulnerability assessment in which vulnerability is thought of as a spatial decision problem under the conditions of uncertainty. Next, we present a methodology to incorporate this definition into a GIS framework that combines elements from the techniques of spatial multicriteria analysis and fuzzy logic. The application of this methodology is then illustrated with a case study from Los Angeles County. The results suggest that the proposed methodology may provide a new approach for analyzing vulnerability that can add to our understanding of human/hazards interaction. 相似文献
20.
Hexiang Bai Feng Cao M. Peter Atkinson Qian Chen Jinfeng Wang 《International journal of geographical information science》2020,34(10):2077-2114
ABSTRACT This paper proposes a new classification method for spatial data by adjusting prior class probabilities according to local spatial patterns. First, the proposed method uses a classical statistical classifier to model training data. Second, the prior class probabilities are estimated according to the local spatial pattern and the classifier for each unseen object is adapted using the estimated prior probability. Finally, each unseen object is classified using its adapted classifier. Because the new method can be coupled with both generative and discriminant statistical classifiers, it performs generally more accurately than other methods for a variety of different spatial datasets. Experimental results show that this method has a lower prediction error than statistical classifiers that take no spatial information into account. Moreover, in the experiments, the new method also outperforms spatial auto-logistic regression and Markov random field-based methods when an appropriate estimate of local prior class distribution is used. 相似文献