Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping

In this paper, we describe new fuzzy models for predictive mineral potential mapping: (1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on quantified spatial associations between a set of evidential evidence features and a set of known mineral deposits for deriving fuzzy membership values of input evidential maps. We also describe a graphical defuzzification procedure for the interpretation of output fuzzy favorability maps. The models are demonstrated for mapping base metal deposit potential in an area in the south-central part of the Aravalli metallogenic province in the state of Rajasthan, western India. The data-driven and knowledge-driven models described in this paper predict potentially mineralized zones, which occupy less than 10% of the study area and contain at least 83% of the model and validation base metal deposits. A cross-validation of the favorability map derived from using one of the models with the favorability map derived from using the other model indicates a remarkable similarity in their results. Both models therefore are useful for predicting favorable zones to guide further exploration work.     

Effects of variable attribute weights on landform classification

This paper focuses on the attribute weight issue and advocates use of modi?able attribute weights in terrain‐based environmental analysis and classi?cation. A question was asked: ‘How much will the result of a terrain‐based environmental analysis be affected if the weights of used terrain attributes are changed?’ The literature on landform classi?cation and the fuzzy k‐means method was reviewed in particular to help clarify the background and importance of this weight assignment issue. As an example, the effects of modifying attribute weights were evaluated for fuzzy k‐means landform classi?cation in a case study area. A total of 102 classi?cations were compared with each other and with a soil map, and comparison methods were speci?cally designed to evaluate the differences between these classi?cations. The results show that fuzzy k‐means landform classi?cation is sensitive to weight adjustments of adopted terrain attributes. The sensitivity is particularly high when the attribute weights started to be tuned away from the standard (i.e. uniform) weight of one. Better matching between landform classi?cation and a soil map may be produced when attribute weights are tuned. In all, we advocate the widespread adoption of an exploratory attitude in assigning attribute weights for environmental analysis and classi?cation. Copyright © 2006 John Wiley & Sons, Ltd.     

基于可持续发展的区域水资源多目标优化配置研究

以区域经济发展与水环境保护相协调为目标,考虑社会各产业经济部门的污水处理和节水调节的控制作用,建立水资源多目标优化配置模型,并利用模糊理论构建评价函数。通过应用于盐城市水资源的优化配置,计算分析结果表明该方法具有良好的可行性和合理性。     

湖南洛塔屋檐洞水库生态安全指标体系及综合评判

本文以DSR模型为框架建立了湖南洛塔屋檐洞水库生态安全评价指标体系,并引入缀块丰富度密度、聚集度、景观均匀性指数等景观生态学指数,采用层次分析和模糊评判有机结合的综合方法,从生态安全状态、压力、响应三个指标体系角度出发,具体分析了屋檐洞库区自然、社会、经济三方面的生态安全问题,对库区生态安全进行综合评价,评判出屋檐洞水库库区系统生态安全属于安全级别,并根据评价中间结果找出生态安全响应是洛塔中寨水电站建设的潜在生态危险因素,提出建立合理科学的生态补偿机制以及库区生态安全预警系统等对策.     

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automati...     

Modelling dispersion in complex open channel flows: Fuzzy calibration (2)

Part 1 of this study assessed the effectiveness of dispersion models based around random particle tracking (RPT) applied an overbank flow in the Flood Channel Facility at HR Wallingford. Several of the RPT models that were used predicted the mixing behaviour of the tracer in the complex channel flow to within an acceptable accuracy. If there is no uniqueness in the model structure which can be used to represent the true system to within the limitations of the available observations, then this implies an inherent degree of ambiguity in our knowledge of the physically based model structure. This suggests that we should be less forthright in the optimisation of each individual model structure, and perhaps investigate more of the parameter combinations for each model which yield feasible simulations of the system. An alternative fuzzy calibration technique is introduced which avoids the optimisation process and takes account of uncertainties in the model structure, parameter sets and observed data in prediction.     

钻井参数评价和优选的模糊综合评判方法

根据模糊综合评判理论,结合钻井资料的分析,建立了一套对钻井参数进行评价和优选的方法。整个过程简单易行,可对实际钻井中钻进参数的合理组配和优化提供有价值的信息。     

高产高效矿井地质条件的定量预测与检验模型

提出地质等性块段法与模糊综合评判法相结合评价煤层开采地质条件的方法对评价指标系统、验证指标系统、指标值赋值及合成,权系数和算子选定,评价方法及评价结果的验证,评价工作流程作了阐述,通过实例证明该方法客观可靠,有推广价值。     

Non-Darcian groundwater flow in leaky aquifers

Abstract

A simplified method has been developed for solving leaky aquifer non-Darcian flow hydraulics. The principle of volumetric approach is combined with the confined-aquifer, time-dependent drawdown equation in an observation well. The groundwater flow in the leaky aquifer is assumed to obey a non-Darcian flow law of exponential type. The results are obtained in the form of type-curve expressions from which the necessary bundles of curves are drawn for a set of selective non-Darcian flow aquifer parameters. Although application of the methodology appears as rather limited but it provides a scientific contribution and extension of leaky aquifer theory towards nonlinear flow conditions. The methodology developed herein is applied to some actual field data from the eastern sedimentary basin in the Kingdom of Saudi Arabia.     

A fuzzy dynamic flood routing model for natural channels

A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S_f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub‐reaches. Training set required for development of the fuzzy rule based model for each sub‐reach is obtained from discharge‐area relationship at its mean section. For highly heterogeneous sub‐reaches, optimized fuzzy rule based models are obtained by means of a neuro‐fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub‐reaches and also in a natural channel with a number of approximately uniform sub‐reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM outputs are comparable to those of the HEC‐RAS model. Copyright © 2009 John Wiley & Sons, Ltd.