Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

公民对全球环境变化的响应——以上海、香港地区为例

工业革命以来，全球环境发生了前所未有的变化，将可能给地球系统带来灾难性后果，究其原因主要是由于人类活动造成的。人的行为深受意识的影响和制约,环境意识对于环境问题的产生和解决至关重要。本文选取上海、香港两个地区来分析公民对环境的关注度、公民的环保意识、环保行为以及公民对政府环境工作的看法和评价，研究公民对全球环境变化反应的区域差异，为政府制定相关环境保护政策提供理论依据。调查结果显示，上海、香港两地公民在很多环境闷题上具有共识。但是。在对手环境状况好转的期待值、参与环境保护活动的积极性、对人为因素主导力量的认识、环境保护与日常生活的切实关系、为环境保护的支付意愿、对于环境教育内容的认可度等方面存在着一定的差异。     

Dynamics of growth and seed production in the Siberian stone pine: The level and pattern of variation in characters

A statistical analysis of interannual variation in a set of vegetative and generative characters over 13 years has been performed to characterize the growth and seed production dynamics of the Siberian stone pine (Pinus sibirica Du Tour) in the southeast of the forest zone in western Siberia. The results have shown that the range of fluctuations in most of vegetative characters is ordinary and their distribution is close to normal. The range of fluctuations in many generative characters is enormous (from 0 to +∞), and the distribution of their values is usually skewed, with low values being recorded several times more frequently than high values. Most variable are the proportion of abortive cones and other characters that are determined mainly in the spring of the pollination year. These characters account for a very high level of variation in the total seed production.     

Preliminary assessment of polybrominated diphenyl ethers (PBDEs) in the Scottish aquatic environment, including the Firth of Clyde

This paper presents preliminary data on polybrominated diphenyl ethers (PBDEs) in the Scottish aquatic environment. Sediment and biota (fish liver, fish muscle and mussels) from a number of locations around Scotland were analysed for PBDEs with samples being from both remote and from potentially contaminated areas such as the former sewage sludge dump site at Garroch Head in the Clyde. PBDEs were measured in both cultivated, rope grown mussels and wild mussels collected from 5 sites around Scotland in 2006. Total PBDE concentrations (sum of tri- to hepta-BDEs) ranged from 相似文献   

Estimating waste transfer station delays using GPS

This paper examines the use of on-board global positioning system (GPS) data recorders as a method to collect field data on the movements of solid waste collection vehicles at transfer stations. The movements of five waste collection vehicles using four different transfer facilities were compared over a period of 1 year. The spatial data were analyzed using geofences to determine the amount of time each truck spent on each of four activities: queuing for access to the weigh scale, sitting on the weigh scale, queuing for access to the tipping floor, and unloading waste. The study found that queuing delays can be identified and measured using GPS data. The average time at a facility for all trucks was 16.4min per visit, with a standard deviation of 14.3min. Time at the facility ranged between 2 and 111min per visit and the distribution of time at the facility was positively skewed. Multi-compartment vehicles (co-collection and recycling trucks) spent significantly more time at unloading facilities. There were also significant differences in the length and the location of the queues at different facilities. At one facility, the longest delays were encountered while waiting for the weigh scale, at two facilities trucks experienced delays in obtaining access to the tipping floor, while at the fourth facility no significant delays developed.