利用多手段异常项次预报我国大震的模糊聚类方法

选用我国大陆１９６９－１９９１年发生的１１次Ｍｓ≥６．９地震作为样本，取地球物理、地球化学、地形变和地震活动性方面共计１２项手段的资料为判定指标，编制了模糊聚类计算机程序用以预报未来３个月、６个月和１２个月内发生大震的概率，并给出一个预报实例。     

模糊综合评判在震害评估中的应用

本文介绍了模糊综合评判的基本原理和方法。通过对震后灾害经济损失的综合评判，获得了较为满意的判识结果，证实了该方法应用于震害评估的合理性和可行性。     

黄河三角洲海岸稳定性特征的模糊分类

本文首次将模糊分类方法引入海滩动态性特征分类的研究中。     

Estimation of pile group scour using adaptive neuro-fuzzy approach

An accurate estimation of scour depth around piles is important for coastal and ocean engineers involved in the design of marine structures. Owing to the complexity of the problem, most conventional approaches are often unable to provide sufficiently accurate results. In this paper, an alternative attempt is made herein to develop adaptive neuro-fuzzy inference system (ANFIS) models for predicting scour depth as well as scour width for a group of piles supporting a pier. The ANFIS model provides the system identification and interpretability of the fuzzy models and the learning capability of neural networks in a single system. Two combinations of input data were used in the analyses to predict scour depth: the first input combination involves dimensional parameters such as wave height, wave period, and water depth, while the second combination contains nondimensional numbers including the Reynolds number, the Keulegan–Carpenter number, the Shields parameter and the sediment number. The test results show that ANFIS performs better than the existing empirical formulae. The ANFIS predicts scour depth better when it is trained with the original (dimensional) rather than the nondimensional data. The depth of scour was predicted more accurately than its width. A sensitivity analysis showed that scour depth is governed mainly by the Keulegan–Carpenter number, and wave height has a greater influence on scour depth than the other independent parameters.     

Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya

Landslides in Himalaya cause widespread damage in terms of property and human lives. It the present study, an attempt is made to derive information on causative parameters and preparation of landslide-susceptible map using fuzzy data integration in one of the seismically active region of Garhwal Himalaya that was recently devastated by a huge landslide. High-resolution remotely sensed data products acquired from Indian Remote Sensing Satellite before and after the landslide event were processed to improve interpretability and derivation of causative parameters. Spatial data sets such as lithology, rock weathering, geomorphology, lineaments, drainage, land use, anthropogenic factor, soil type and depth, slope gradient, and slope aspect were integrated using fuzzy gamma operator. The final map was reclassified in to five classes such as highly to lowly susceptible classes based on cumulative cutoff. The result shows around 72% of known landslide areas including the large Uttarkashi landslide in the high and very high susceptibility classes comprising of only 37% of the total area. The precipitation data from ground- and satellite-based observations were compared; the precipitation threshold and the role of seismic activity were analyzed for initiation of landslide.     

Fuzzified kinematic analysis of discontinuity-controlled rock slope instabilities

In this study, it is aimed to bring a different approach to kinematic analyses of discontinuity-controlled rock slope instabilities. For this purpose, the data of a detailed discontinuity survey carried out in Ankara, the capital city of Turkey, were updated and reevaluated. Serious discontinuity-controlled instability events were observed in the andesites covering large areas with dense population in the city. Instead of analyzing the effects of the planes belonging only to the major discontinuity sets on the stereographic projection net, all discontinuities were taken into consideration, and kinematic analyses were carried out for planar, wedge, and toppling type failures on pixel basis of the Digital Elevation Model (DEM) of the study area. By doing so, it could be possible to compensate for the deficiency created by neglecting the planes in the lower concentration zones of the stereographic projection. A computer program named FUDIKA (Fuzzified Digital Kinematic Analyses) was written to perform modular kinematic analyses and fuzzy operations, having four modules and operating in three stages. First, Potential Instability Index (PII) was introduced to define instability potential of the rock slopes based on the number of possible instability events for each failure type. Next, the PII values were normalized and fuzzified to obtain PII map of the area. It was seen that when tested on previously occurred instabilities in the area, the PII values obtained through the methodology proposed in the study showed quite a high performance.     

Pattern based map comparisons

Map comparison techniques based on a pixel-by-pixel comparison are useful for many purposes, but fail to reveal important aspects of map similarities and differences. In contrast, pattern based map comparison techniques address the question of structural similarity, although with these approaches the comparison problem becomes open ended, since there is an unlimited number of ways to characterise a pattern. Two types of pattern based technique are used here to analyse the test sets of maps. The first, a fuzzy polygon based matching technique, focuses on the meso-scale aspects of pattern. It is based on the areal intersection of land use polygons on the two maps being compared. The areal intersection, areal complement, and polygon size values are fuzzified into an appropriate set of categories, a set of fuzzy inference rules is applied to derive memberships in local matching categories, and finally the local matching category memberships are defuzzified to yield local matching values for each land use polygon on the reference map. The second approach, fractal analysis, captures macro-scale or global qualities of the maps. Two measures are calculated here: the radial dimension and the cluster size—frequency dimension. The polygon matching approach provides only limited insight when applied to the case of the map set representing differences in classification. It proves much more effective when applied to the problem of change detection, revealing areas where the pattern has changed and giving local measures of the degree of change. The approach is particularly useful in the case where there is a considerable degree of random change at the pixel level, as changes in the underlying pattern are extracted from the noise, while pixel based approaches largely detect the noise.     

Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP)

Environmental risk management is an integral part of risk analyses. The selection of different mitigating or preventive alternatives often involve competing and conflicting criteria, which requires sophisticated multi-criteria decision-making (MCDM) methods. Analytic hierarchy process (AHP) is one of the most commonly used MCDM methods, which integrates subjective and personal preferences in performing analyses. AHP works on a premise that decision-making of complex problems can be handled by structuring the complex problem into a simple and comprehensible hierarchical structure. However, AHP involves human subjectivity, which introduces vagueness type uncertainty and necessitates the use of decision-making under uncertainty. In this paper, vagueness type uncertainty is considered using fuzzy-based techniques. The traditional AHP is modified to fuzzy AHP using fuzzy arithmetic operations. The concept of risk attitude and associated confidence of a decision maker on the estimates of pairwise comparisons are also discussed. The methodology of the proposed technique is built on a hypothetical example and its efficacy is demonstrated through an application dealing with the selection of drilling fluid/mud for offshore oil and gas operations.