高阶非线性系统自适应模糊有限时间状态约束控制

针对一类具有状态约束的非严格反馈高阶非线性系统,研究一种自适应模糊有限时间跟踪控制问题.首先,利用模糊逻辑系统逼近不确定性非线性函数,在此基础上,采用障碍Lyapunov函数,解决状态约束问题,通过障碍加幂积分方法和反步递推技术,提出了一种有限时间控制设计方法.在有限时间Lyapunov稳定意义下,严格证明闭环系统半全局实际有限时间稳定且系统的状态不超出给定的约束边界,并实现了有限时间跟踪控制目标.最后,仿真研究进一步验证了所提出控制方法的有效性.     

矿井水源判别的模糊数学方法

通过对邢台矿务局五个矿214个水样化学分析资料的统计,给出了利用频数统计法和正态分布型函数形成各因素隶属度的方法,求标准参数值和权重值数学模型及水源快速判别模糊综合评判的数学方法。验证结果证明了这种方法的可行性和可靠性。      

航空影像的模糊增强方法

根据航空影像的灰度特性,选用像素的相对灰度等级作为模糊特征,采用模糊算法实现航空影像的模糊增强处理。实验表明,模糊算法较传统方法可取得更好的增强效果。     

Using computational intelligence techniques to model subglacial water systems

Measurements of water pressure beneath Trapridge Glacier, Yukon Territory, Canada show that the basal water system is highly heterogeneous. Three types of behaviour were recorded: pressure records which are strongly correlated, records which are strongly anticorrelated, and records which alternate between strong correlation and strong anticorrelation. We take the pressure in bore-holes that are connected to the evacuation route for basal water as the forcing, and the other pressures as the response to this forcing. Previous work (Murray and Clarke 1995) has shown that these relationships can be modelled using low-order nonlinear differential equations optimized by inversion. However, despite optimizing the model parameters we cannot be sure that the final model forms are themselves optimal. Computational intelligence techniques provide alternative methods for fitting models and are robust to missing or noisy data, applicable to non-smooth models, and attempt to derive optimal model forms as well as optimal model parameters. Four computational intelligence techniques have been used and the results compared with the more conventional mathematical model. These methods were genetic programming, artificial neural networks, fuzzy logic and self-organizing maps. We compare each technique and offer an evaluation of their suitability for modelling the pressure data. The evaluation criteria are threefold: (1) goodness of fit and an ability to predict subsequent data under different surface weather conditions; (2) interpretability, and the extent and significance of any new insights offered into the physics of the glacier; (3) computation time. The results suggest that the suitability of the computational intelligence techniques to model these data increases with the complexity of the system to be modelled.     

位置不确定性与属性不确定性的场模型

不确定性是自地理信息系统发展与应用以来一个引起关注的课题。位置不确定性与属性不确定常常不加区分地被看作是可以单个讨论的问题。本文将借助场的概念和模型使二者得以统一的描述和分析;对于明确定义的离散目标,二者虽然可分别讨论,但却在数学上有着联合的基础;对于非明确定义的地理现象,二者以连续体的形式而存在,位置不确定性可以作为属性不确定性的空间映射而提取出来。     

Analysis of reservoir water quality using fuzzy synthetic evaluation

A general methodology for fuzzy synthetic evaluation is developed and illustrated with a case study of trophic status assessment for Fei-Tsui Reservoir in Taiwan. The historical data base was collected from the management agency of Fei-Tsui Reservoir from 1987 to 1996. In fuzzy synthetic evaluation, the classification is determined by a matrix operation of the weighted vector with the fuzzy evaluation matrix. After all individual membership functions of evaluated factors have been determined, the fuzzy evaluation matrix can be established. The weighted vector is determined by the analytic hierarchy process method (AHP). The results of this investigation show that the long-term change of water quality and the overturn phenomena cannot be observed with the Carlson index from 1987 to 1992 but is expressed by fuzzy synthetic evaluation. Fuzzy synthetic evaluation is better suited than the Carlson index to rating the trophic status of self-sustaining lakes. Interpretation of the results can provide valuable information to decision makers and aid reservoir management.     

近海多功能混凝土平台选型与优化

提出了一种适合近海边际油田开发的多功能混凝土平台型式,并对其进行了优化设计.分析了各约束对平台造价的影响,确定了平台的应用范围.优化分析中采用了约束单调性分析、初始点自动给定等方法,加快了优化的迭代收敛速度,并对初稳性高度GM值采用了模糊优化方法,考虑了影响GM值的主观因素.     

湖泊水环境模糊数学评价模型及其在富营养化排序中的应用

本文根据模糊水文学关于水体“清洁”与“污染”之间无明确界面,在识别过程中具有模糊性的论点,提出湖泊水环境评价的模糊数学模型。应用此模型对我国12个湖泊富营养化污染状况进行排序,结果与实际相符,文中提出的评价模型,原则上也适用于其他环境领域的评价工作。     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

考虑时间约束的地震救灾数学模型设计与实现

在地震救灾方面,针对信息实时更新的地震救灾数学模型,为了满足不同受灾点的物资需求,增加了出救点数量以及配送时间,以此来保证地震救援物资需求的满足度,提高了应急响应水平。结合地震救灾特点,设计了一种考虑时间约束的地震救灾数学模型。该模型在地震救灾物资需求预测部分,分析影响地震救灾物资需求量的主要因素,构建地震救灾物资需求量计算模型,对影响地震救灾物资需求量的主要因素构建隶属度函数,给出基于模糊综合评判的地震救灾物资需求分级模型。其次,考虑时间约束以及需求不确定等方面,构建考虑时间约束的地震救灾多目标优化数学模型,并给出求解模型。实验结果表明,该模型减少了救灾物资到达受灾点的延迟时间,可在满足时间约束的条件下提高物资需求满足率。