Risk assessment for the Yucca Mountain high-level nuclear waste repository site: Estimation of volcanic disruption     

Chih-Hsiang Ho 《Mathematical Geology》1992,24(4):347-364

In this article, we model the volcanism near the proposed nuclear waste repository at Yucca Mountain, Nevada, U.S.A. by estimating the instantaneous recurrence rate using a nonhomogeneous Poisson process with Weibull intensity and by using a homogeneous Poisson process to predict future eruptions. We then quantify the probability that any single eruption is disruptive in terms of a (prior) probability distribution, since not every eruption would result in disruption of the repository. Bayesian analysis is performed to evaluate the volcanic risk. Based on the Quaternary data, a 90% confidence interval for the instantaneous recurrence rate near the Yucca Mountain site is (1.85×10^–6/yr, 1.26×10^–5/yr). Also, using-these confidence bounds, the corresponding 90% confidence interval for the risk (probability of at least one disruptive eruption) for an isolation time of 10⁴ years is (1.0×10^–3, 6.7×10^–3), if it is assumed that the intensity remains constant during the projected time frame.  相似文献   

Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series     

Babak Mohammadi  Nguyen Thi Thuy Linh  Ali Najah Ahmed  Jana Vojteková  Yiqing Guan 《水文科学杂志》2020,65(10):1738-1751

ABSTRACT

Accurate runoff forecasting plays a key role in catchment water management and water resources system planning. To improve the prediction accuracy, one needs to strive to develop a reliable and accurate forecasting model for streamflow. In this study, the novel combination of the adaptive neuro-fuzzy inference system (ANFIS) model with the shuffled frog-leaping algorithm (SFLA) is proposed. Historical streamflow data of two different rivers were collected to examine the performance of the proposed model. To evaluate the performance of the proposed ANFIS-SFLA model, six different scenarios for the model input–output architecture were investigated. The results show that the proposed ANFIS-SFLA model (R² = 0.88; NS = 0.88; RMSE = 142.30 (m³/s); MAE = 88.94 (m³/s); MAPE = 35.19%) significantly improved the forecasting accuracy and outperformed the classic ANFIS model (R² = 0.83; NS = 0.83; RMSE = 167.81; MAE = 115.83 (m³/s); MAPE = 45.97%). The proposed model could be generalized and applied in different rivers worldwide.  相似文献   

Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping   总被引：5，自引：0，他引：5  

Porwal  Alok  Carranza  E. J. M.  Hale  M. 《Natural Resources Research》2003,12(1):1-25

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.  相似文献   

Multiobjective analysis of chaotic dynamic systems with sparse learning machines     

Abedalrazq F. Khalil  Mac McKeeMariush Kemblowski  Tirusew AsefaLuis Bastidas 《Advances in water resources》2006

Sparse learning machines provide a viable framework for modeling chaotic time-series systems. A powerful state-space reconstruction methodology using both support vector machines (SVM) and relevance vector machines (RVM) within a multiobjective optimization framework is presented in this paper. The utility and practicality of the proposed approaches have been demonstrated on the time series of the Great Salt Lake (GSL) biweekly volumes from 1848 to 2004. A comparison of the two methods is made based on their predictive power and robustness. The reconstruction of the dynamics of the Great Salt Lake volume time series is attained using the most relevant feature subset of the training data. In this paper, efforts are also made to assess the uncertainty and robustness of the machines in learning and forecasting as a function of model structure, model parameters, and bootstrapping samples. The resulting model will normally have a structure, including parameterization, that suits the information content of the available data, and can be used to develop time series forecasts for multiple lead times ranging from two weeks to several months.  相似文献   

基于主成分分析和贝叶斯正则化方法的神经网络年最大洪峰流量预测模型探讨     

李红霞  许士国  范垂仁 《水文》2006,26(6):30-32

针时水文预测建模中输入因子过多而导致神经网络结构规模过大,泛化能力差的问题,利用主成分分析和贝叶斯正则化方法对神经网络进行改进,优化网络结构,从而提高泛化能力。以洮儿河流域镇西站年最大洪峰流量预测为例,研究结果表明,改进的神经网络预测方法与传统的神经网络方法相比,泛化能力有显著提高,而且网络的收敛也比较稳定,实际预测中效果良好。  相似文献   

基于标点随机过程的遥感影像道路提取   总被引：1，自引：1，他引：1  

余长慧  孟令奎  秦昆 《武汉大学学报(信息科学版)》2006,31(1):59-62

在分析贝叶斯方法用于遥感影像目标提取技术的基础上．基于标点随机过程方法，利用线状地物的整体几何约束和地物之间的空间结构及相关关系对目标构建数学模型．提取线状地物．并以道路网的自动提取为例，详细阐述了此算法。  相似文献   

An Aggregate Constraint Method for Inequality-constrained Least Squares Problems   总被引：3，自引：0，他引：3  

Junhuan Peng  Hongping Zhang  Suli Shong  Chunxi Guo 《Journal of Geodesy》2006,79(12):705-713

The inequality-constrained least squares (ICLS) problem can be solved by the simplex algorithm of quadratic programming. The ICLS problem may also be reformulated as a Bayesian problem and solved by using the Bayesian principle. This paper proposes using the aggregate constraint method of non-linear programming to solve the ICLS problem by converting many inequality constraints into one equality constraint, which is a basic augmented Lagrangean algorithm for deriving the solution to equality-constrained non-linear programming problems. Since the new approach finds the active constraints, we can derive the approximate algorithm-dependent statistical properties of the solution. As a result, some conclusions about the superiority of the estimator can be approximately made. Two simulated examples are given to show how to compute the approximate statistical properties and to show that the reasonable inequality constraints can improve the results of geodetic network with an ill-conditioned normal matrix.  相似文献   

A case for a reassessment of the risks of extreme hydrological hazards in the Caribbean   总被引：2，自引：3，他引：2  

S. A. Sisson  L. R. Pericchi  S. G. Coles 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(4):296-306

There is an urgent need for the development and implementation of modern statistical methodology for long-term risk assessment of extreme hydrological hazards in the Caribbean. Notwithstanding the inevitable scarcity of data relating to extreme events, recent results and approaches call into question standard methods of estimation of the risks of environmental catastrophes that are currently adopted. Estimation of extreme hazards is often based on the Gumbel model and on crude methods for estimating predictive probabilities. In both cases the result is often a remarkable underestimation of the predicted probabilities for disasters of large magnitude. Simplifications do not stop here: assumptions of data homogeneity and temporal independence are usually made regardless of potential inconsistencies with genuine process behaviour and the fact that results may be sensitive to such mis-specifications. These issues are of particular relevance for the Caribbean, given its exposure to diverse meteorological climate conditions.In this article we present an examination of predictive methodologies for the assessment of long-term risks of hydrological hazards, with particular focus on applications to rainfall and flooding, motivated by three data sets from the Caribbean region. Consideration is given to classical and Bayesian methods of inference for annual maxima and daily peaks-over-threshold models. We also examine situations where data non-homogeneity is compromised by an unknown seasonal structure, and the situation in which the process under examination has a physical upper limit. We highlight the fact that standard Gumbel analyses routinely assign near-zero probability to subsequently observed disasters, and that for San Juan, Puerto Rico, standard 100-year predicted rainfall estimates may be routinely underestimated by a factor of two.  相似文献   

重磁异常解释中的一些复杂因素与对策 ——在海口区域物探成果交流会上的发言提纲     

刘士毅 《物探与化探》2007,31(5):386-390,398

列出了不重视推断解释可靠性问题而导致的严重后果;论述了复杂情况下重、磁异常解释的思路和对策,即如何正确、合理使用方法技术;提出了推断成果可靠性划分方案的建议和新的成果表达方式的建议.  相似文献   

边坡稳定性优势面分析与专家系统推理策略     

璩继立 《南方国土资源》1998,(2)

文章对边坡稳定性优势面分析与评价的专家系统及其推理策略和实现过程进行了阐述;并对在实现过程及实际应用中的技术问题进行了探讨。  相似文献