共查询到19条相似文献，搜索用时 203 毫秒
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为了探讨新的加权系数估计方法对于消除或减弱证据层不满足条件独立性假设时对预测结果的影响, 对加权证据权模型的加权系数估计方法进行了新的探讨,尝试用顺序估计法估计加权系数.加权系数的顺序估计法是将加权证据权模型与基于模糊预测对象的证据权模型相结合,将证据层按照一定顺序逐步加入到加权证据权模型中,在加入到模型的过程中依次用已经获得的后验概率作为模糊训练层对证据层加入到模型的顺序进行修正,并通过条件相关系数的方法估计加权系数.分别以1组多元正态分布模拟数据和个旧锡铜多金属矿产资源预测为例,比较了多种模型的后验概率,结果表明加权证据权模型对减弱证据层不满足条件独立性假设所产生的影响是有效的. 相似文献
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模糊证据权方法在镇沅(老王寨)地区金矿资源评价中的应用 总被引：11，自引：0，他引：11
采用模糊证据权方法和GeoDASGIS技术开展了镇沅(老王寨)及其邻区的金矿资源潜力评价.分别采用GeoDASGIS软件提供的局部奇异性分析技术、S-A异常分解技术、主成分分析技术、证据权、模糊证据权等技术对相关地球化学元素进行了系统的处理和分析.应用主成分分析方法确定了可能的2种不同成矿类型,并采用主成分得分确定了组合异常点,在此基础上分别采用普通证据权和模糊证据权方法编制了成矿后验概率图,圈定了有利成矿地段.对比普通证据权方法与模糊证据权方法所得结果表明,模糊证据权方法可减小图层离散化造成的有用信息损失,提高预测结果精度. 相似文献
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证据权方法是目前最常用的信息综合方法之一,广泛应用于矿产资源定量预测与评价.然而,它要求变量间相互独立,地质上很难满足这一条件.如何削弱条件不独立对证据权预测结果的影响,已成为当前数学地球科学研究的热点.解决该问题的途径之一是对传统证据权模型进行校正,比如采取加权的方法对原证据权模型计算的证据权重进行修正,以便消除非条件独立性的影响.对近期提出的多种加权证据权模型进行了系统的对比研究,基于同样的应用实例和实验方案,对不同方法的应用效果进行了比较,结果表明,各种加权证据权模型均可不同程度地削弱证据图层条件不独立性的影响,其中,基于逻辑回归的加权证据权模型优于其他加权方法. 相似文献
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本文选择博格达-哈尔里克一带作为研究区,从区域成矿地质背景入手,鉴于该地区已知成型铜矿床较少,成矿规律研究薄弱,故作者采用ArcGIS平台下的证据权模型(WofE),以数据驱动方式为主,从断裂构造、沉积岩相与建造、火山岩建造、侵入岩岩性等方面,以学生化反差S(C)作为有利因子衡量指标,对各控矿因素进行影响程度分类,利用加权逻辑斯回归模型计算成矿后验概率,根据后验概率值的大小进行成矿远景区的圈定和分级,在博格达-哈尔里克成矿带内共圈定7个成矿远景区。最后结合区域化探资料进行了验证,结果显示所圈定的铜矿成矿远景区内化探异常明显,与Cu元素异常套合较好,说明ArcGIS证据权模型能很好地为区域矿产预测提供良好的技术支撑,为研究区铜矿找矿方向提供理论依据,文中所总结的基于ArcGIS平台的证据权计算方法流程也为区域矿产预测提供了方法借鉴。 相似文献
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加权证据权模型和逐步证据权模型及其在个旧锡铜矿产资源预测中的应用 总被引：7，自引：2，他引：5
为了消除和减弱当证据层不满足条件独立性假设时对预测结果产生的影响, 提出了逐步证据权模型和加权证据权模型.加权证据权模型通过对logit模型进行修改, 对各个证据层给予一定的权重, 以调整由于证据层与其他证据层的条件相关性对模型的影响; 逐步证据权模型是将证据层按照一定的顺序逐步加入到模型中, 在加入到模型的过程中依次用已经获得的后验概率作为模糊训练层的方法.以个旧锡铜多金属矿产资源预测为例, 应用4种证据权模型的后验概率进行异常圈定, 结果表明两种新的模型对减弱证据层不满足条件独立性假设所产生的影响是有效的. 相似文献
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模糊逻辑空间决策模型在变量取值上不是采用二态法将研究区分为成矿有利区和成矿不利区两部分,而是根据地质数据的规律取连续变化的隶属度赋值,有效避免了有用地质信息的丢失。笔者在GIS平台上利用Arc-SDM模块对冀西北地区的地质、地球化学、地球物理等资料进行了处理,利用证据权法进行了线缓冲形成的证据层与矿床（点）之间的亲近度分析,在此基础上采用列表法对原始地质变量进行了直观模糊隶属度赋值。模糊逻辑的预测结果表明,在圈出的仅占研究区面积13.2%的靶区范围内有85%的已知矿床（点）出现,与已知矿床（点）吻合程度高,预测效果理想,其结果可用于指导下一步找矿工作。 相似文献
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基于模糊预测对象的证据权方法及其在土地沙漠化评价中的应用 总被引：3，自引：3，他引：0
为了使在地理信息系统中被广泛用于点事件预测的证据权方法能对面事件进行评价和预测, 提出了一种新的基于模糊训练层的证据权方法.它是一种更广泛的证据权方法, 与普通证据权方法所不同的是, 它的训练层是模糊集合, 其取值是它的隶属度.通过适当的变换也可以把点训练层转换为模糊集合.因此, 该方法可以对面事件、点事件和线事件进行评价和预测.该方法可以处理训练层和证据层均为模糊集合的情况, 被称为双重模糊证据权方法.作为该方法的一个应用实例, 本文介绍毛乌素沙漠边缘的晋陕蒙地区土地沙漠化评价的应用实例. 相似文献
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中国江西省的九瑞地区是长江中下游成矿带中最重要的铜矿产地之一,其中花岗闪长斑岩与铜成矿关系密切。基于水系沉积物与矿化相关的信息,采用因子分析（FA）、浓度–面积分形法（C–A）和模糊证据权方法 （FWofE）相结合建立成矿潜力预测模型。使用因子分析处理包含32个元素的255份水系沉积物样本数据,找到能够指示铜矿化的组合元素（即主因子）。采用多重分形反距离加权插值法（MIDW）创建主因子得分栅格图并用C–A分形模型提取与铜矿化相关的地化异常。将得到和铜矿化相关的地球化学异常图与地质、遥感解译数据相结合,应用模糊证据权方法建立预测模型。结果表明：已知铜矿床位于圈定预测概率高值区,且受花岗闪长斑岩和断裂的分布共同控制;除已知铜矿床区域外,圈定的3个一级远景区域内也具有较高的概率,值得进一步铜勘查找矿工作的进行。 相似文献
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山西五台地区位于华北陆台中部,是山西省内重要的金矿成矿区域,地质条件复杂,近年来找矿突破较小。在矿产预测中,可以结合证据权快速筛选地质变量,求取权重,计算地质奇异性指数,提取局部地质弱异常;利用灰色理论只需少量信息进行预测的特点,圈定找矿靶区,寻找突破。应用证据权-奇异性-灰色理论方法圈定了研究区预测靶区,靶区内通过已知矿床的验证,提取了4个一级靶区,1个二级靶区,确定了该区域金矿找矿突破口,明确了证据权-奇异性-灰色理论关联分析预测法在矿产预测评价中的重要应用价值和独特的应用效果。 相似文献
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Mineral exploration programs commonly use a combination of geological, geophysical and remotely sensed data to detect sets of optimal conditions for potential ore deposits. Prospectivity mapping techniques can integrate and analyse these digital geological data sets to produce maps that identify where optimal conditions converge. Three prospectivity mapping techniques – weights of evidence, fuzzy logic and a combination of these two methods – were applied to a 32,000 km2 study area within the southeastern Arizona porphyry Cu district and then assessed based on their ability to identify new and existing areas of high mineral prospectivity. Validity testing revealed that the fuzzy logic method using membership values based on an exploration model identified known Cu deposits considerably better than those that relied solely on weights of evidence, and slightly better than those that used a combination of weights of evidence and fuzzy logic. This led to the selection of the prospectivity map created using the fuzzy logic method with membership values based on an exploration model. Three case study areas were identified that comprise many critical geological and geophysical characteristics favourable to hosting porphyry Cu mineralisation, but not associated with known mining or exploration activity. Detailed analysis of each case study has been performed to promote these areas as potential targets and to demonstrate the ability of prospectivity modelling techniques as useful tools in mineral exploration programs. 相似文献
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Daojun Zhang Frits Agterberg Qiuming Cheng Renguang Zuo 《Mathematical Geosciences》2014,46(7):869-885
Weights of evidence and logistic regression are two of the most popular methods for mapping mineral prospectivity. The logistic regression model always produces unbiased estimates, whether or not the evidence variables are conditionally independent with respect to the target variable, while the weights of evidence model features an easy to explain and implement modeling process. It has been shown that there exists a model combining weights of evidence and logistic regression that has both of these advantages. In this study, three models consisting of modified fuzzy weights of evidence, fuzzy weights of evidence, and logistic regression are compared with each other for mapping mineral prospectivity. The modified fuzzy weights of the evidence model retains the advantages of both the fuzzy weights of the evidence model and the logistic regression model; the advantages being (1) the predicted number of deposits estimated by the modified fuzzy weights of evidence model is nearly equal to that of the logistic regression model, and (2) it can deal with missing data. This method is shown to be an effective tool for mapping iron prospectivity in Fujian Province, China. 相似文献
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Weights of evidence (WofE) is an artificial intelligent method for integration of information from diverse sources for predictive purpose in supporting decision making. This method has been commonly used to predict point events by integrating point training layer and binary or ternary evidential layers (multiclass evidence less commonly used). Omnibus weights of evidence integrates fuzzy training layer and diverse evidential layers. This method provides new features in comparison with the ordinary WofE method. This new method has been implemented in a geographic information system-geophysical data analysis system and the method includes the following contents: (1) dual fuzzy weights of evidence (DFWofE), in which training layer and evidential layers can be treated as fuzzy sets. DFWofE can be used to predict not only point events but also area or line events. In this model a fuzzy training layer can be defined based on point, line, and areas using fuzzy membership function; and (2) degree-of-exploration model for WofE is implemented through building a degree of exploration map. This method can be used to assess possible spatial correlations between the degree of exploration and potential evidential layers. Importantly, it would also make it possible to estimate undiscovered resources, if the degree of exploration map is combined with other models that predict where such resources are most likely to occur. These methods and relevant systems were validated using a case study of mineral potential prediction in Gejiu (个旧) mineral district, Yunnan (云南), China. 相似文献
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基于GIS的证据权法在三江北段铜多金属成矿预测中的应用 总被引：4，自引：0，他引：4
在建立三江北段地质矿产空间数据库的基础上,运用GIS技术,分析提取矿产地质、地球物理、地球化学等综合信息中的成矿异常信息,运用多学科信息综合研究地质异常与成矿之间的相互关系,运用证据权重法建立该区的证据权重成矿预测模型,圈定出7个找矿远景区。 相似文献
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A 2D prospectivity model of epithermal gold mineralisation has been completed over the Taupo Volcanic Zone (TVZ), using the weights of evidence modelling technique. This study was used to restrict a 3D geological interpretation and prospectivity model for the Ohakuri region. The TVZ is commonly thought of as a present-day analogue of the environment in which many epithermal ore deposits, such as in the Hauraki Goldfield, Coromandel Volcanic Zone, are formed. The models utilise compiled digital data including historical exploration data, geological data from the Institute of Geological and Nuclear Sciences Ltd. Quarter Million Mapping Programme, recent Glass Earth geophysics data and historic exploration geochemical data, including rock-chip and stream sediment information. Spatial correlations between known deposits and predictive maps are determined from the available data, which represent each component of the currently accepted mineral system model for epithermal gold. The 2D prospectivity model confirms that the TVZ has potential for gold mineralisation. However, one of the weaknesses of this weights of evidence model is that the studies are carried out in 2D, with an approximation of 3D provided by geophysical and drilling data projected to a 2D plane. Consequently, a 3D prospectivity model was completed over the Ohakuri area, constrained by the results of the 2D model and predictive maps. The 3D model improved the results allowing more effective exploration targeting. However, the study also highlighted the main issues that need to be resolved before 3D prospectivity modelling becomes standard practise in the mineral exploration industry. The study also helped develop a work flow that incorporates preliminary 2D spatial data analysis from the weights of evidence technique to more effectively restrict and develop 3D predictive map interpretation and development. 相似文献
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Application of Weights of Evidence to Mineral Potential Mapping of Yujiacun Ore Field in Northwest Yunnan Province, China 总被引：1，自引：0，他引：1
ZHAO Pengda 《中国地质大学学报(英文版)》2003,14(3):269-273
The multivariate information conprehensive processing technique is especially important at present to the digital mineral prospecting. However, the GIS-based weights of evidence have provided us with powerful tool for the quantitative assessment of mineral resource potential. In this paper, the mineralization model is established, based on the achievements made by previous researchers, to mend such deficiencies ad few references on ore fields in Yujiacun, Yunnan Province and the shortage of quantitative prediction and assessment of mineral resources. In addition, the weights of evidence are used to make a systematic quantitative prediction and assessment of mineral resources there, so that 2 mineral prospecting target areas of grade Ⅰ and 8 mineral prospecting target areas of grade Ⅱ are delineated, providing the further mineral resource exploration with the basis for the selection of mineral deposits. 相似文献
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W. M. Brown T. D. Gedeon D. I. Groves R. G. Barnes 《Australian Journal of Earth Sciences》2013,60(4):757-770
A multilayer feed‐forward neural network, trained with a gradient descent, back‐propagation algorithm, is used to estimate the favourability for gold deposits using a raster GIS database for the Tenterfield 1:100 000 sheet area, New South Wales. The database consists of solid geology, regional faults, airborne magnetic and gamma‐ray survey data (U, Th, K and total count channels), and 63 deposit and occurrence locations. Input to the neural network consists of feature vectors formed by combining the values from co‐registered grid cells in each GIS thematic layer. The network was trained using binary target values to indicate the presence or absence of deposits. Although the neural network was trained as a binary classifier, output values for the trained network are in the range [0.1, 0.9] and are interpreted to indicate the degree of similarity of each input vector to a composite of all the deposit vectors used in training. These values are rescaled to produce a multiclass prospectivity map. To validate and assess the effectiveness of the neural‐network method, mineral‐prospectivity maps are also prepared using the empirical weights of evidence and the conceptual fuzzy‐logic methods. The neural‐network method produces a geologically plausible mineral‐prospectivity map similar, but superior, to the fuzzy logic and weights of evidence maps. The results of this study indicate that the use of neural networks for the integration of large multisource datasets used in regional mineral exploration, and for prediction of mineral prospectivity, offers several advantages over existing methods. These include the ability of neural networks to: (i) respond to critical combinations of parameters rather than increase the estimated prospectivity in response to each individual favourable parameter; (ii) combine datasets without the loss of information inherent in existing methods; and (iii) produce results that are relatively unaffected by redundant data, spurious data and data containing multiple populations. Statistical measures of map quality indicate that the neural‐network method performs as well as, or better than, existing methods while using approximately one‐third less data than the weights of evidence method. 相似文献
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Fuzzy logic mineral prospectivity modelling was performed to identify camp-scale areas in western Victoria with an elevated potential for hydrothermal-remobilised nickel mineralisation. This prospectivity analysis was based on a conceptual mineral system model defined for a group of hydrothermal nickel deposits geologically similar to the Avebury deposit in Tasmania. The critical components of the conceptual model were translated into regional spatial predictor maps combined using a fuzzy inference system. Applying additional criteria of land use restrictions and depth of post-mineralisation cover, downgrading the exploration potential of the areas within national parks or with thick barren cover, allowed the identification of just a few potentially viable exploration targets, in the south of the Grampians-Stavely and Glenelg zones. Uncertainties of geological interpretations and parameters of the conceptual mineral system model were explicitly defined and propagated to the final prospectivity model by applying Monte Carlo simulations to the fuzzy inference system. Modelling uncertainty provides additional information which can assist in a further risk analysis for exploration decision making. 相似文献
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The main purpose of this study is to introduce a geographic information system (GIS)-based, multi-criteria decision analysis method for selection of favourable environments for Besshi-type volcanic-hosted massive sulphide (VHMS) deposits. The approach integrates two multi-criteria decision methods (analytical hierarchy process and ordered weighted averaging) and theory of fuzzy sets, within a GIS environment, to solve the problem of big suggested areas and missing known ore deposits in favourable environment maps for time and cost reduction. We doubled the fuzzy linguistic variables’ significance as a method to apply the arrange weights that the analytical hierarchy process (AHP)-ordered weighted averaging (OWA) hybrid procedure depends on. Another aim of this work is to assist mineral deposit exploration by modelling existing uncertainty in decision-making. Both AHP and fuzzy logic methods are knowledge-based, and they are affected by decision maker judgments. We used data-driven OWA approach in a hybrid method for solving this problem. We applied a new knowledge-guided OWA approach on data with changing linguistic variables according to the mineral system for VHMS deposits. Additionally, we used a vector-based method combination, which increased the precision of results. Results of knowledge-guided OWA showed that all of the mines and discovered deposits have been predicted with 100% accuracy in half of the size of the suggested area. To summarize, results improved the selection of possible target sites and increased the accuracy of results as well as reducing the time and cost, which will be used for field exploration. Finally, the hybrid methods with a knowledge-guided OWA approach have delivered more reliable results compared to exclusively knowledge-driven or data-driven methods. The study proved that expert knowledge and processed data (information) are critical important keys to exploration, and both of them should be applied in hybrid methods for reaching reliable results in mineral prospectivity mapping. 相似文献