模块化模糊神经网络训练策略研究

为分析模块化模糊神经网络的训练机制,进一步降低其训练复杂度,增强模型的泛化性能,尝试采用部分训练样本对模型进行相对粗训练,并以广西全省1957-2003年连续47 a 5月平均降水量作为实验数据,统计各种参数条件下模型的逐步预测误差情况.结果表明:由部分训练样本参与训练的模型所得测试误差普遍低于由全部训练样本参与训练的模型所得测试误差,证明该方法可行.     

基于标识的遥感影像部分监督模糊聚类

根据遥感影像的特点引入了部分监督模糊聚类的方法,并对其进行改进,加入了标识参数flagk,使其在训练过程中对参与计算的数据进行筛选,使得训练的速度加快,去除了非样本类数据对类心数据的影响,获得了较高精度的分类结果。     

Reservoir operation using grey fuzzy stochastic dynamic programming

This paper presents an optimal regulation programme, grey fuzzy stochastic dynamic programming (GFSDP), for reservoir operation. It is composed of a grey system, fuzzy theory and dynamic programming. The grey system represents data by covering the whole range without loss of generality, and the fuzzy arithmetic takes charge of the rules of reservoir operation. The GFSDP deals with the multipurpose decision‐making problem by fuzzy optimization theorem. The practicability and effectiveness of the proposed approach is tested on the operation of the Shiman reservoir in Taiwan. The current M5 operating rule curves of this reservoir also are evaluated. The simulation results demonstrate that this new approach, in comparison with the M5 rule curves, has superior performance with regard to the total water deficit and number of monthly deficits. Copyright © 2002 John Wiley & Sons, Ltd.     

A Short-Term Climate Prediction Model Based on a Modular Fuzzy Neural Network

In terms of the modular fuzzy neural network (MFNN) combining fuzzy c-mean (FCM) cluster and single-layer neural network, a short-term climate prediction model is developed. It is found from modeling results that the MFNN model for short-term climate prediction has advantages of simple structure, no hidden layer and stable network parameters because of the assembling of sound functions of the selfadaptive learning, association and fuzzy information processing of fuzzy mathematics and neural network methods. The case computational results of Guangxi flood season (JJA) rainfall show that the mean absolute error (MAE) and mean relative error (MRE) of the prediction during 1998 2002 are 68.8 mm and 9.78%, and in comparison with the regression method, under the conditions of the same predictors and period they are 97.8 mm and 12.28% respectively. Furthermore, it is also found from the stability analysis of the modular model that the change of the prediction results of independent samples with training times in the stably convergent interval of the model is less than 1.3 mm. The obvious oscillation phenomenon of prediction results with training times, such as in the common back-propagation neural network (BPNN) model, does not occur, indicating a better practical application potential of the MFNN model.     

An improved algorithm for supervised fuzzyC-means clustering of remotely sensed data

This paper describes an improved algorithm for fuzzyc-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is decreased as comparing with that by a conventional algorithm: that is, the classification accuracy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzyc-means clustering, in particular when fuzziness is also accommodated in the assumed reference data.     

A FUZZY MATHEMATICS EVALUATION OF THE DISASTER BY TROPICAL CYCLONES

In this paper, data from disaster reduction in China have been used to statistically analy ze the disaster by tropical cyclones that occurred from 1979 to 1996 within the area of Guangdong province. By the method of fuzzy subset theory, the conditions of the disaster have been discussed and the evaluation model of the disaster B set up. The index of the disaster of every tropical cyclone have been obtained and divided into five parts. The result shows that the index is almost proportional to the direct economic losses, so this model is reasonable.     

结构振动的模糊状态控制法

本文介绍了一种模糊状态控制法,将结构的状态（即反应）进行模糊化,按照某种经验法则对结构反应进行控制。使用这种方法使得振动控制计算简便、控制直接和控制效果显著。     

路基下岩溶稳定性评价的模糊多层次多属性决策方法研究

影响高速公路路基下岩溶稳定性的因素很多,影响程度各不相同且包含各种模糊信息。基于实际工程资料,综合运用层次分析方法和模糊多属性决策方法,建立路基下岩溶顶板稳定性评价的模糊多层次多属性决策模型;采用Laagoven和Buckley关于层次分析方法中权重比矩阵元素模糊化的建议,推导出权重比矩阵元素为三角模糊数的模糊权值向量计算公式,再按照模糊平均加权方法（F-SAW）得到每个评语的模糊效应值;最后以此结果进行模糊集排序,得到岩溶顶板稳定性的评语。实际工程的应用结果表明了方法的可行性和有效性,为岩溶区路基稳定性评价提供了新的思路和方法。     

荒漠绿洲防风固沙林体系的模糊综合评判——以高台县为例

运用模糊数学方法,以植物生长状况及固沙效果、土壤机械组成和土壤含水量3类指标对高台沙区现存的、定植20 a后的7种防风固沙林配置类型综合评判后,认为花棒+柠条锦鸡儿+梭梭（6 m×3 m）的隔带混交类型、梭梭+花棒（4.5 m×3 m）的隔带混交类型及柠条锦鸡儿(6 m×5 m)为生态健康,综合效益好,可以在高台沙区推广应用。     

可控阵的图论特征

文中提出了模糊矩阵有向图的强链的概念 ,并利用它对可控阵的图进行了研究 ,揭示可控阵的有向图中无强圈的特征 ;着重讨论可控阵的可控度 ,给出可控度的强链刻画。在此基础上 ,通过可控度的性质及其与可控阵、可控阵的标准型的关系研究 ,得出可控度为图中最长强链的长度加 1和可控阵的周期≤ 2的结果。