FCM聚类算法协同Canny算子的遥感影像边缘检测方法

提出一种FCM聚类算法协同Canny算子的遥感影像边缘检测方法,算法采用中值滤波消除原始遥感影像中的非高斯噪声;采用FCM(Fuzzy C-mean)聚类算法将滤波处理后的遥感影像中的像素分为两类:边缘类像素和非边缘类像素,并得到聚类影像;最后采用Canny算子对聚类影像进行边缘检测得到遥感影像地物边缘信息。实验结果表明,文中提出的方法能有效消除遥感影像中的混合噪声并准确地检测出地物目标的边缘,是一种有效的遥感影像边缘检测方法。     

Stage‐discharge uncertainty derived with a non‐stationary rating curve in the Choluteca River,Honduras

Uncertainty in discharge data must be critically assessed before data can be used in, e.g. water resources estimation or hydrological modelling. In the alluvial Choluteca River in Honduras, the river‐bed characteristics change over time as fill, scour and other processes occur in the channel, leading to a non‐stationary stage‐discharge relationship and difficulties in deriving consistent rating curves. Few studies have investigated the uncertainties related to non‐stationarity in the stage‐discharge relationship. We calculated discharge and the associated uncertainty with a weighted fuzzy regression of rating curves applied within a moving time window, based on estimated uncertainties in the observed rating data. An 18‐year‐long dataset with unusually frequent ratings (1268 in total) was the basis of this study. A large temporal variability in the stage‐discharge relationship was found especially for low flows. The time‐variable rating curve resulted in discharge estimate differences of ? 60 to + 90% for low flows and ± 20% for medium to high flows when compared to a constant rating curve. The final estimated uncertainty in discharge was substantial and the uncertainty limits varied between ? 43 to + 73% of the best discharge estimate. Copyright © 2010 John Wiley & Sons, Ltd.     

Fuzzy logic model approaches to daily pan evaporation estimation in western Turkey / Estimation de l’évaporation journalière du bac dans l’Ouest de la Turquie par des modèles à base de logique floue

Abstract

Abstract Evaporation is one of the fundamental elements in the hydrological cycle, which affects the yield of river basins, the capacity of reservoirs, the consumptive use of water by crops and the yield of underground supplies. In general, there are two approaches in the evaporation estimation, namely, direct and indirect. The indirect methods such as the Penman and Priestley-Taylor methods are based on meteorological variables, whereas the direct methods include the class A pan evaporation measurement as well as others such as class GGI-3000 pan and class U pan. The major difficulty in using a class A pan for the direct measurements arises because of the subsequent application of coefficients based on the measurements from a small tank to large bodies of open water. Such difficulties can be accommodated by fuzzy logic reasoning and models as alternative approaches to classical evaporation estimation formulations were applied to Lake Egirdir in the western part of Turkey. This study has three objectives: to develop fuzzy models for daily pan evaporation estimation from measured meteorological data, to compare the fuzzy models with the widely-used Penman method, and finally to evaluate the potential of fuzzy models in such applications. Among the measured meteorological variables used to implement the models of daily pan evaporation prediction are the daily observations of air and water temperatures, sunshine hours, solar radiation, air pressure, relative humidity and wind speed. Comparison of the classical and fuzzy logic models shows a better agreement between the fuzzy model estimations and measurements of daily pan evaporation than the Penman method.     

GRA——FAHP模型的煤层底板突水危险性评价

矿井水害一直是制约我国煤炭安全生产的重要隐患之一,对其进行准确的预测评价具有十分重要的理论意义和实用价值。本文根据煤层底板突水各影响因素之间的关系是灰色关系并且具有非线性特征的特点,建立了定量与定性指标为一体的煤层底板突水评价指标体系及等级划分标准。同时将灰色关联分析法(GRA)和模糊层次分析法(FAHP)相结合。构建了能真实反映影响因素与底板突水之间灰色关系和非线性关系的底板突水危险性评价模型,并应用模型对某典型工作面突水危险性等级进行了评价,可为今后煤层底板突水预测评价的研究提供一定的借鉴和依据。     

改进的模糊聚类遥感影像分割

聚类是数据挖掘的重要分支之一,引入模糊理论的模糊聚类分析为显示数据提供了模糊处理能力,在许多领域被广泛应用。本文应用考虑邻域关系的约束模糊C均值(Fuzzy C-Means with Constrains,FCM_S)算法,将邻域像素引入到目标函数中,进而有效地利用邻域像素信息,提高分割精度。本文应用FCM_S算法对模拟彩色纹理图像进行分割,计算其混淆矩阵,定性定量地与FCM算法进行对比分析,证明了该算法的鲁棒性。     

中国典型旅游城市人居环境适宜度空间分异研究

运用模糊层次分析法,在中国101个拥有5个3A及以上旅游景区的城市中选取30个城市为研究对象。通过建立人居环境适宜度指标体系,运用熵值法计算得出30个典型旅游城市经济环境适宜度、生态环境适宜度、气候环境适宜度、服务环境适宜度和人居环境适宜度综合得分,并对典型旅游城市的人居环境适宜度进行排序和分析。结果显示:北京和上海在人居环境适宜度得分排名前两位且优势明显;长三角地区城市(苏州、杭州、南京等)人居环境适宜度综合排名与典型旅游城市综合排名差距不大且大部分排名前15,是城市人居环境与旅游资源协调发展的典范;沿海城市(大连、青岛、厦门等)和传统旅游城市(桂林、昆明、黄山)由于旅游季节单一等原因造成城市旅游综合指数得分的排名不高,但人居环境适宜度得分较高,优势主要体现在气候环境适宜度、生态环境适宜度和服务环境适宜度;以人文景观为主的旅游城市(西安、洛阳等)人居环境适宜度排名普遍不高;重庆、广州在典型旅游城市中排名靠前,但城市人居环境适宜度得分较低,此类城市在做好旅游发展的同时应注重城市生态、服务等方面的发展。     

基于模糊关联规则的NCRE数据分析

在对NCRE数据进行预处理的基础上,通过定义模糊事物数据库,将模糊集与经典关联规则算法结合起来,提出了一种模糊关联规则的数据挖掘算法,将其应用于NCRE数据分析,收到了较好的效果。     

Adapted Fuzzy Controller for Astronomical Telescope Tracking

This paper presents a novel application of fuzzy logic (FL) controller driven by an adaptive fuzzy set (AFS) for position tracking of the telescope driven by electric motor. Also, the proposed FL controller, driven by AFS, is compared with a classical FL control, driven by a static fuzzy set (SFS). Both FL controllers algorithm use the position error and its rate of change as an input vector. The mathematical model of the telescope driven by electric motor is highly nonlinear differential equations. Therefore the use of the artificial intelligent controller, such as FL is much better than the conventional controller, to cover a wide range of operating conditions. So, the output of FL control is utilized to force the electric drives, of the telescope, to satisfy a perfect matching of the predefined desired position of the telescope arms. Both of FL controllers, using AFS and SFS, are simulated and tested when the system is subjected to a step change in reference value. In addition, these simulation results are compared with the conventional Proportional-Derivative (PD) controller, driven by fixed gain. The proposed FL, using an adaptive fuzzy set, improve the dynamic response of the overall system by improving the damping coefficient and decreasing the rise time and settling time compared with other two controllers.     

The Potential of Fuzzy Multi-objective Model for Rainfall Forecasting from Typhoons

This study applies the fuzzy multi-objective approach to forecast short-term (around 24 h) typhoon rainfall, which can be implemented without much background meteorological knowledge. The physical characteristics of 40 typhoons, including route, central pressure, central velocity and cyclonic radius, were used as the data set. The fuzzy multi-objective method mined information from the database to forecast both the depth and pattern of rainfall, which were then combined to estimate a cumulative rainfall curve. The results of calibration with reference to 40 historical typhoon events and the results of validation using another five typhoon events indicate that the proposed model has the potential to forecast short-term cumulative rainfall curves if more variables can be included and more historical typhoon events can be collected to enlarge the database.