Fuzzy optimization of multi-period carbon capture and storage systems with parametric uncertainties

Carbon capture and storage (CCS) is an important technology option for reducing industrial greenhouse gas emissions. In practice, CO₂ sources are easy to characterize, while the estimation of relevant properties of storage sites, such as capacity and injection rate limit (i.e., injectivity), is subject to considerable uncertainty. Such uncertainties need to be accounted for in planning CCS deployment on a large scale for effective use of available storage sites. In particular, the uncertainty introduces technical risks that may result from overestimating the limits of given storage sites. In this work, a fuzzy mixed integer linear program (FMILP) is developed for multi-period CCS systems, accounting for the technical risk arising from uncertainties in estimates of sink parameters, while still attaining satisfactory CO₂ emissions reduction. In the model, sources are assumed to have precisely known CO₂ flow rates and operating lives, while geological sinks are characterized with imprecise fuzzy capacity and injectivity data. Three case studies are then presented to illustrate the model. Results of these examples illustrate the tradeoff inherent in planning CCS systems under parametric uncertainty.     

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.     

Modelling spatial distribution of hard bottom benthic communities and their functional response to environmental parameters

In this study we analyzed and modelled spatial distribution of hard bottom benthic communities in the Lagoon of Venice, and used the model to derive functional response of these communities to changing environmental conditions.     

Spatio-temporal dissolved oxygen dynamics in the Orbetello lagoon by fuzzy pattern recognition

This paper models the dissolved oxygen (DO) dynamics in the Orbetello lagoon as a function of the physico-chemical and ecological system variables, including the submerged vegetation, nutrients, and hydrodynamics. It should be viewed as the concluding sequel to a previous paper describing the dynamics of the lagoon ecosystem [Giusti, E., Marsili-Libelli, S., 2006. An integrated model for the Orbetello lagoon ecosystem, Ecol. Model. 196, 379–394] by introducing the missing DO dynamics. The model considers the oxygen demand originating from the decay of carbonaceous and nitrogenous compounds, as well as photosynthesis and natural reaeration by winds and currents as the oxygen producing processes. With a fixed-parameter set the model could accurately reproduce each single circadian DO cycle, but in the long run it failed to extend this fit and could not accommodate the large DO fluctuations induced by the seasonal variability. In order to enhance the model flexibility, a fuzzy pattern recognition algorithm was designed to classify the circadian DO patterns into four typical behaviours, related to the season, and estimate the corresponding parameters, with the overall model output being a fuzzy combination of these sets. The paper discusses several methods to patch the parameter sets and compares their performance in tracking long-term DO variations. A final assessment of the model validity is obtained by incorporating the whole DO dynamics (model, fuzzy pattern recognition and parameter combination) into the general lagoon model and producing a consistently correct series of DO daily distributions over a yearly cycle. Thus the paper contains both a practical and a methodological aspect. The practical one is the linking of all the lagoon dynamics to the dissolved oxygen kinetics in order to clarify to what extent macroalgae and macrophytes influence the oxygen balance. The methodological aspect consists of extending the validity of short-term models to long time-horizons through a patching technique supported by fuzzy pattern recognition.     

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process.     

工业设备的震害预测研究

综合考虑地震作用和结构材料的随机性 ,运用概率论的知识建立了地震作用下钢铁工业设备各种破坏形式的极限状态方程 ,并求出了对应于某种地震烈度 ,设备出现各种破坏状态的概率。在此基础上 ,通过模糊综合评判的手段提出了工业设备的震害预测方法 ,并编制了相应的软件。此种方法的建立使设备抗震预测变得方便、可行。     

A model of Cellular Automata for the spatial and temporal analysis of Citrus Sudden Death with the fuzzy parameter

Citrus Sudden Death (CSD) is a disease that has affected sweet orange trees grafted on Rangpur lime in the south of Minas Gerais state and in the north of São Paulo state (Brazil). This is a worrying characteristic because the Rangpur lime responds to 85% of the Brazilian citrus rootstocks. This disease is believed to be caused by a virus transmitted by aphids (vector) of the citrus. In this work, we have adopted the Cellular Automata model (CA) to study the temporal evolution of the disease. We take into account the effect of the wind in the space covered by the aphid. To establish the relationship between the space covered by the aphid and the intensity of the wind, we have adopted the rule-based fuzzy system. Simulations were performed and compared to real data. Through the use of the mean absolute error (MAE) method, it was possible to verify a 70% of similarity between our model of data and the real one.     

模糊综合评价法在疏散时间影响因素研究中的应用

人员疏散是一个复杂的运动过程,人员疏散时间受众多因素影响,具有一定的模糊性和随机性。该文将人员安全疏散作为一个系统进行分析,从疏散场所、疏散人员以及疏散环境三个角度分析影响人员疏散时间的因素,构建出人员疏散时间的评价指标体系。结合模糊综合评价法的基本原理和步骤,建立人员疏散时间影响因素的三级模糊综合评价模型,并应用该模型对某高层建筑火灾中影响人员疏散时间的因素进行模糊综合评价。     

太湖流域水资源可持续利用评价研究

为了全面了解太湖流域水资源开发利用状况,加强流域水资源综合管理,根据水资源可持续利用的涵义和太湖流域的实际情况,构建太湖流域水资源可持续利用评价指标体系,利用模糊综合评判法和灰色关联分析法分别对太湖流域2008年水资源可持续利用状况进行评价,两种模型计算结果均表明,2008年太湖流域水资源可持续利用处于中上水平,其主要制约因素主要表现在水环境状况和水生态状况问题较为严重。     

模糊识别在水质综合评价中的应用

应用模糊数学方法对水质进行综合评价,其关键问题是如何合理地确定各评价指标的权重．将最优权法引入模糊评价以确定各评价指标的权系数．通过求解权向量的最优解来确定各指标权重,可避免确定评价指标权重的主观任意性,增加评价结果的分辨性．实例计算与结果对比表明,该方法克服了各指标的权系数随实测样本的不同而变化和评价结果分辨性差的缺点,提高了模型的通用性和评价结果的可比性,同时也简化了多次重复确定权系数的工作量．