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81.
基于Wavelet-ANFIS和MODIS地表温度产品的青藏高原0 cm土壤温度估算方法 总被引:1,自引:1,他引:0
0 cm土壤温度是冻土模型的上边界条件, 连续的、 高质量的青藏高原0 cm土壤温度数据是进行准确冻土模拟的必要条件. 然而受复杂下垫面的影响, 遥感手段无法获取可靠的0 cm土壤温度. 利用自适应网络模糊推理系统(ANFIS)结合青藏高原实测资料建立遥感地表温度产品(LST)与0 cm土壤温度的关系, 以实现通过LST估算青藏高原逐日0 cm土壤温度. 研究了ANFIS的各种参数组合, 发现筛选合适的小波函数、 小波窗口、 小波层数建立起来的Wavelet-ANFIS模型能较准确实现估算0 cm土壤温度的目的. 验证表明, 估算结果与气象站点实测0 cm土壤温度绝对误差在2 K以下, 相关系数0.98以上. 考虑到原始MODIS LST误差在0~2 K之间, 该方法可以获取较为理想的0 cm土壤温度, 为冻土模型提供准确的上边界输入. 相似文献
82.
Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques 总被引:3,自引:0,他引:3
Evaporation, as a major component of the hydrologic cycle, plays a key role in water resources development and management in arid and semi-arid climatic regions. Although there are empirical formulas available, their performances are not all satisfactory due to the complicated nature of the evaporation process and the data availability. This paper explores evaporation estimation methods based on artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques. It has been found that ANN and ANFIS techniques have much better performances than the empirical formulas (for the test data set, ANN R2 = 0.97, ANFIS R2 = 0.92 and Marciano R2 = 0.54). Between ANN and ANFIS, ANN model is slightly better albeit the difference is small. Although ANN and ANFIS techniques seem to be powerful, their data input selection process is quite complicated. In this research, the Gamma test (GT) has been used to tackle the problem of the best input data combination and how many data points should be used in the model calibration. More studies are needed to gain wider experience about this data selection tool and how it could be used in assessing the validation data. 相似文献
83.
Seismic safety of high concrete dams 总被引:2,自引:1,他引:1
Peak ground acceleration(PGA) estimation is an important task in earthquake engineering practice.One of the most well-known models is the Boore-Joyner-Fumal formula,which estimates the PGA using the moment magnitude,the site-to-fault distance and the site foundation properties.In the present study,the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an effi ciency-robustness balanced formula is proposed.For this purpose,a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship.In this approach,each model class(a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data.The one with the highest plausibility is robust since it possesses the optimal balance between the data fi tting capability and the sensitivity to noise.A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis.The optimal predictive formula is proposed based on this database.It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore,Joyner and Fumal(1993). 相似文献
84.
为了实现基于多源WFS服务要素层次的语义检索,提出了一个要素本体的五元模型。在此框架下,研究了要素本体的自动构建方法,形式化定义了要素的空间关系,并扩展了逻辑关系以及空间关系的推理规则来实现要素层次的联合推理检索,并给出了联合规则推理的要素语义检索算法。实例证明,本文方法对多源WFS的语义查询具有实际的可行性,为多源WFS服务要素的语义检索提供了一个新的方法。 相似文献
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87.
Sediment source apportionment in Laurel Hill Creek,PA, using Bayesian chemical mass balance and isotope fingerprinting 总被引:2,自引:0,他引:2
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A Bayesian chemical mass balance (CMB) approach was used to assess the contribution of potential sources for fluvial samples from Laurel Hill Creek in southwest Pennsylvania. The Bayesian approach provides joint probability density functions of the sources' contributions considering the uncertainties due to source and fluvial sample heterogeneity and measurement error. Both elemental profiles of sources and fluvial samples and 13C and 15N isotopes were used for source apportionment. The sources considered include stream bank erosion, forest, roads and agriculture (pasture and cropland). Agriculture was found to have the largest contribution, followed by stream bank erosion. Also, road erosion was found to have a significant contribution in three of the samples collected during lower‐intensity rain events. The source apportionment was performed with and without isotopes. The results were largely consistent; however, the use of isotopes was found to slightly increase the uncertainty in most of the cases. The correlation analysis between the contributions of sources shows strong correlations between stream bank and agriculture, whereas roads and forest seem to be less correlated to other sources. Thus, the method was better able to estimate road and forest contributions independently. The hypothesis that the contributions of sources are not seasonally changing was tested by assuming that all ten fluvial samples had the same source contributions. This hypothesis was rejected, demonstrating a significant seasonal variation in the sources of sediments in the stream. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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本文采用模糊逻辑推理方法对地下水位进行预测,收到较好的效果,该方法与其它方法相比提高了预测精度,简化了计算方法。 相似文献
90.
The Uncertainty in the True End Point of a Fossil's Stratigraphic Range When Stratigraphic Sections Are Sampled Discretely 总被引:1,自引:0,他引:1
Stratigraphic sections are often sampled at well-defined discrete points. Because of the incompleteness of the fossil record, a particular species may not be observed even when it is extant at a sampling point. We introduce a model and Bayesian analysis for estimating the true time of disappearance of a lineage from a section in the face of the possibility that failure to find the species beyond its observed stratigraphic range may represent false negatives. We incorporate proper prior information, including an estimated longevity of the species and the probability that it will be observed if extant. Our analysis produces a posterior density for the true extinction time of the species. Summaries of this probability distribution provide a point estimate of the extinction time, a standard deviation for the uncertainty in the estimate, and confidence intervals for the time of extinction. We apply our model to stratigraphic ranges of benthic foraminifera collected from the early Late Cretaceous (Cenomanian and Turonian) from Eastbourne, England. 相似文献