基于模糊理论的气象科研项目风险与绩效评估

通过对项目风险进行综合分析、审定,确立一种气象科研项目的立项风险评估指标及体系的准则;从风险角度出发,构建出一组多级指标的项目风险评估指标体系;采用定性和定量相结合的方法,提出一种基于模糊理论的风险评估体系和模型,对科研项目的立项进行综合评估,给出评估意见,给决策提供指导意见;同时,提出一种气象科研项目绩效考核及推广方法.     

Development and application of oil-spill risk assessment model for offshore pipeline

To the potential oil-spill risk caused by offshore pipeline more attention has been paid after the Dalian oil spill incident from oil-pipeline explosion. Since then an issue about how to prevent and control the sudden oil-spill from the offshore pipeline has been raised. In this paper, we proposed an optimized model to analyze the main causes （probability） of spill and the consequence with the fuzzy comprehensive assessment model. Considering the complicated assessment process for oil-spill, the assessment factor system involving the spill probability and consequence was established based on the operative manual and statistic leakage/damage data of offshore pipeline in order to estimate the integrated spill risk score automatically. The evaluated factors of spill probability could be grouped into five aspects：corrosion, fatigue, national damage, third party, and operational fault;the consequence evaluated factors of spill included hazard of oil and impact-controlling capability. With some modifications based on experts’ opinions, each of the evaluated factors in our work was developed with a relative weight and evaluation criterion. A test example for an offshore pipe-line in the Bohai waters was described to show how the model can be used for an actual case in more detail. By using the oil-spill risk assessment model, it is easy to determine the risk level associated with the ongoing activity and management level and hence to take the risk mitigation action immediately.     

模糊理论在临沂城区生态地质环境评价中的应用

近年来,随着经济的快速发展和城市的大规模建设,临沂市城区出现了一系列环境地质问题,比如水土体污染、地质灾害加剧、生态环境恶化等等,严重破坏了自然生态环境。为综合评价该区生态地质环境,加强该区的生态地质环境保护与管理,该文在目前国内外尚无生态地质环境评价规范和标准的情况下,运用模糊理论对临沂生态地质环境进行了综合评价。评价结果把工作区分为良好区、较好区、较差区和差区4个区。     

基于二级模糊综合评判的废弃采石场对景观的影响分析——以泰山风景区及周边采石场为例

以泰山为例,根据风景区内及周边废弃采石场分布现状,选取地理位置、规模、植被恢复程度作为评价因子,利用二级模糊综合评判模型,量化了各个采石场相关指标对景区景观影响程度,并最终得出综合评判结果,为进一步对废弃采石场进行处理提供依据。     

基于双层模糊计算的工程测量质量评价模型

科学的对工程测量的成果质量进行评价是测绘生产过程中的关键工作,本文在总结以往测绘成果质量评价方法的同时,给出了工程测量的质量评价模型,即双层模糊评价模型,以高程控制测量为例,详述了模型的计算步骤和最终质量评价等级。     

三种开发区土地集约利用评价方法比较分析

BP神经网络是近年来用于开发区土地集约利用评价的新方法,自学习能力强且精度较高。模糊综合评价法和多因素综合评价法是开发区土地集约利用评价的常用方法。本文拟采用上述三种方法对广东省某高新技术产业开发区土地集约利用程度进行评价。通过评价过程和结果的对比分析,探讨三种方法在评价中的优缺点。     

基于模糊贴近度和改进Prim算法的高光谱图像波段分组排序

传统的基于Prim算法的高光谱图像波段分组排序需要计算所有波段之间的相关系数,并采用满秩相关系数矩阵作为邻接矩阵进行比较,计算复杂度较高。结合模糊数学的相似度衡量理论和高光谱图像的特点,首先提出使用计算简单的最大最小贴近度(maximum and minimum closeness,MMC)作为衡量高光谱图像波段间相关性的参数;然后将MMC的满秩邻接矩阵稀疏化,提取有效波段进行排序,明显降低了排序的波段数目和比较次数。实验结果表明,与传统的Prim算法相比,所提出的算法在保持原有压缩效率的同时,大大降低了波段排序的复杂度,平均波段排序运行时间减少了27%。     

Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery

Urban areas consist of spectrally and spatially heterogeneous features. Advanced information extraction techniques are needed to handle high resolution imageries in providing detailed information for urban planning applications. This study was conducted to identify a technique that accurately maps impervious and pervious surfaces from WorldView-2 (WV-2) imagery. Supervised per-pixel classification algorithms including Maximum Likelihood and Support Vector Machine (SVM) were utilized to evaluate the capability of spectral-based classifiers to classify urban features. Object-oriented classification was performed using supervised SVM and fuzzy rule-based approach to add spatial and texture attributes to spectral information. Supervised object-oriented SVM achieved 82.80% overall accuracy which was the better accuracy compared to supervised per-pixel classifiers. Classification based on the proposed fuzzy rule-based system revealed satisfactory output compared to other classification techniques with an overall accuracy of 87.10% for pervious surfaces and an overall accuracy of 85.19% for impervious surfaces.     

A 24‐h Forecast of Oxidant Concentration in Tokyo Using Neural Network and Fuzzy Learning Approach

In this study, several types of adaptive network‐based fuzzy inference system (ANFIS) with different membership functions (MFs) and artificial neural network (ANN) were employed to predict hourly photochemical oxidants that were oxidizing substances such as ozone and peroxiacetyl nitrate produced by photochemical reactions. The results indicated that ANFIS statistically outperforms ANN in terms of hourly oxidant prediction. The minimum mean absolute percentage errors (MAPEs) of 4.99% could be achieved using ANFIS with bell shaped MFs. The maximum correlation coefficient, the minimum mean square errors, and the minimum root mean square errors were 0.99, 0.15, and 0.39, respectively. ANFIS's architecture consists of both ANN and fuzzy logic including linguistic expression of MFs and if‐then rules, so it can overcome the limitations of traditional neural network and increase the prediction performance.     

Metropolitan dynamics in Israel: an emerging “metropolitan island state”?

This study analyzes metropolitan dynamics in a small country with an “island state” context of closed boundaries, using commuting data and mobile phone tracking data. We examine whether the Israeli context encourages the formation of a monocentric “metropolitan state,” characterized by increasing links between localities throughout the country and its principal metropolitan node (Tel Aviv)—rather than with secondary metropolitan areas—and by fuzzy, overlapping metropolitan boundaries. Commuting data from the 1995 and 2008 censuses show that metropolitan expansion processes in Israel are gradual. Mobile phone tracking data for 2013 reveal similar patterns, confirming the urban structure’s stability and the reliability of tracking data as a means of assessing metropolitan processes. The “island state” context supports growing monocentricity, but, when it comes to commuting and travel for other purposes, Israel is not yet a metropolitan state; metropolitan boundaries are not as fuzzy and rapidly changing as expected.