A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint‐Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Tuning of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms. Copyright © 2009 John Wiley & Sons, Ltd.     

Delineation of hydrologically similar units in a watershed based on fuzzy classification of soil hydraulic properties

Evaluation of flow and transport processes in a watershed‐scale requires that the watershed be divided into homogenous spatial units referred to as hydrologically similar units (HSUs). Although a few discretization schemes are already in use, a universally acceptable method of obtaining HSUs is yet to emerge. In this study, we developed a fuzzy inference system (FIS) to classify the saturated hydraulic conductivity (K_s) and two water‐retention parameters α and n into fuzzy logic‐based soil hydrologic classes (FSHCs). Analysis of these classes showed that soil properties within an FSHC have less variability and those between two FSHCs have large variability. This result suggested that soils belonging to a specific FSHC may be more similar than those across different FSHCs and may be grouped together to represent an HSU. Soils within a specific hydrologic class were aggregated to delineate HSUs within the watershed. For the Dengei Pahad micro‐watershed (DPW), this approach showed five distinct regions representing a discretized zone having similar soil hydraulic properties. Application of this approach on a larger international database of soil hydraulic properties revealed that the developed hydrologic classes are quite comparable across different databases. The delineated HSUs based on these FSHCs were also better than the soil series map of the watershed in maintaining the soil heterogeneity of the watershed. Moreover, this new discretization scheme using the SWAT modelling environment showed better performance than the soil series‐based discretization approach. Copyright © 2010 John Wiley & Sons, Ltd.     

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for scientific evaluation of a public meteorological service. This paper aims to explore a technical method for determining and screening evaluation indicators. Based on public satisfaction survey data obtained in Wafangdian (China) in 2010, this study investigates the suitability of the fuzzy clustering analysis method in establishing an evaluation index. Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators, correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer, then one indicator could be removed, or the two indicators merged. For evaluation indicators in different sub-evaluation layers, although clustering reveals attribute correlations, these indicators may not be substituted for one another. Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.     

模糊聚类分析法在油气评价中的应用

文章介绍了模糊聚类分析在石油勘探决策中的应用,选用了烃源岩9个评价参数,利用模糊聚类方法对烃源岩进行分类评价,并对评价过程进行了详细的论述.通过对评价结果与实际地质情况进行比较,评价结果与实际情况完全符合,证明模糊聚类方法用于油气资源评价是完全可靠的.     

贺庄橡胶坝工程建设综合后评价

构建了橡胶坝工程建设综合后评价的指标体系,建立了合理的后评价数学模型,并以贺庄橡胶坝工程建设为实例,应用多目标模糊层次分析法对其进行了综合后评价.该方法将定性指标数量化及各项指标的无量纲化,使定性指标和定量指标有机的结合起来,从而更准确、直观地反映橡胶坝建设项目的成功度,对实际的橡胶坝工程后评价有一定实用价值.     

英超球员能力的定量评估和预测

为了对足球运动员的运动能力进行系统且量化的评估,并进一步根据已知资料预测特定球员的能力走向,运用统计学方法进行研究。基于2006—2009这4个赛季英超联赛的统计数据和现场评论,运用定量评估方法,首先综合分析已有数据和球评关键词,建立基于赛季末统计数据的球员能力评估模型1;然后单独考虑球评中球员名出现次数,建立基于球评中球员名出现次数的球员能力评估模型2;定量评估上场球员能力,并将结果与历届获得世界足球先生提名的英超球员进行比较,发现模型1更接近于奖项的评奖标准。最后在二模型的基础上,建立对正在进行的2010赛季内球员能力的预测模型。模型结果具有实际效应,值得在足球球员能力评估与预测中加以运用。     

具有Bernoulli反馈的M/M/1/N工作休假排队系统

研究了带Bernoulli反馈的M/M/1/N工作休假排队模型。工作休假策略为空竭服务多重工作休假。完成服务的顾客以概率p(0相似文献   

模糊线性优化在厦门湾水体总磷环境容量计算中的应用

在应用POM模型进行厦门湾水动力、污染物扩散和各排污口响应系数场模拟研究的基础上,采用最优化法对厦门湾水体总磷环境容量进行计算.根据厦门湾海区特征和使用功能,将厦门湾划分成5个海区,分别在5个海区选取水质控制点.分别以各海区水质控制点总磷浓度作为约束条件,运用普通优化和模糊优化对厦门湾内22个排污口源强进行优化设计.分析结果表明,基于模糊线性优化方法进行排污口源强优化设计和环境容量计算可以实现排污口源强再分配,且能够更充分地利用厦门湾的纳污能力.     

区域气候变化适应度评价——以咸阳市为例

选取经济、农业、社会和资源环境系统作为区域气候变化适应度的评价子系统,运用AHP分析法,确定各评价因子的权重,运用模糊综合评判分析法,确定对气候变化适应的隶属度并判断适应度。结果表明,咸阳市1998-2007年对气候变化适应的隶属度呈逐年增加趋势,适应度处于由"较弱"向"一般"过渡状态,区域整体及各子系统对气候变化的适应处于低水平状态。其中经济系统适应度由"弱"到"强",受不利因素影响程度小;农业系统适应度由"弱"到"一般",受不利因素影响程度较大;社会系统适应度由"较弱"到"较强";资源环境系统适应度由"弱"到"一般",受不利因素的影响程度较大,稳定性差。