Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.     

An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

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.     

Toward quantifying the effectiveness of water trading under uncertainty

This paper presents a methodology for quantifying the effectiveness of water-trading under uncertainty, by developing an optimization model based on the interval-parameter two-stage stochastic program (TSP) technique. In the study, the effectiveness of a water-trading program is measured by the water volume that can be released through trading from a statistical point of view. The methodology can also deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle uncertainties expressed as intervals in the trading system. The developed methodology was tested with a hypothetical water-trading program in an agricultural system in the Swift Current Creek watershed, Canada. Study results indicate that the methodology can effectively measure the effectiveness of a trading program through estimating the water volume being released through trading in a long-term view. A sensitivity analysis was also conducted to analyze the effects of different trading costs on the trading program. It shows that the trading efforts would become ineffective when the trading costs are too high. The case study also demonstrates that the trading program is more effective in a dry season when total water availability is in shortage.     

应用区间层次分析法(IAHP)研究高层建筑火灾安全因素

高层建筑物的火灾安全影响因素繁多,其对建筑物火灾安全性的影响不容易确定,采用传统的层次分析法对某些因子的影响权重进行确定时难度较大.本文采用区间层次分析法来解决这一问题.首先建立影响高层建筑火灾安全的层次分析模型,然后用区间层次分析法确定影响因子,采用区间数特征根法求出各个火灾安全因子的权重值,并进行一致性检验.研究表明,影响高层建筑火灾安全的因子从大到小依次为:安全疏散措施、管理与维护、消防设施、报警与灭火系统、阻燃与防火结构,得到了每个因子的权重.采用同样的方法确定了每个影响因子的子因子的权重及重要性排序.其结果与实际情况基本相符.表明在进行高层建筑火灾安全性评估时,区间层次分析法是一种较好的方法.     

用区间估计法控制环境监测质量的初探

用投放质控标准样的方法来选择若干校准曲线，对这些标准曲线的截距ａ、斜率ｂ的进行总体参数进行区间估计。在实际工作中根据估计出的置信区间便可控制和检验监测所做校准曲线的质量，从而间接推断同期环境监测的质量。     

Heat illness among high school athletes--United States, 2005-2009

Introduction

Heat illness is a leading cause of death and disability among U.S. high school athletes.

Methods

To examine the incidence and characteristics of heat illness among high school athletes, CDC analyzed data from the National High School Sports-Related Injury Surveillance Study for the period 2005–2009.

Results

During 2005–2009, the 100 schools sampled reported a total of 118 heat illnesses among high school athletes resulting in ≥ 1 day of time lost from athletic activity, a rate of 1.6 per 100,000 athlete-exposures, and an average of 29.5 time-loss heat illnesses per school year. The average corresponds to a weighted average annual estimate of 9,237 illnesses nationwide. The highest rate of time-loss heat illness was among football players, 4.5 per 100,000 athlete-exposures, a rate 10 times higher than the average rate (0.4) for the eight other sports. Time-loss heat illnesses occurred most frequently during August (66.3%) and while practicing or playing football (70.7%). No deaths were reported.

Conclusions

Consistent with guidelines from the National Athletic Trainers’ Association, to reduce the risk for heat illness, high school athletic programs should implement heat-acclimatization guidelines (e.g., set limits on summer practice duration and intensity). All athletes, coaches, athletic trainers, and parents/guardians should be aware of the risk factors for heat illness, follow recommended strategies, and be prepared to respond quickly to symptoms of illness. Coaches also should continue to stress to their athletes the importance of maintaining proper hydration before, during, and after sports activities.

Impact of industry

By implementing preventive recommendations and quickly recognizing and responding to heat illness, coaches, athletic trainers, and the sporting community can prevent future deaths.     

ICCLP: An Inexact Chance-Constrained Linear Programming Model for Land-Use Management of Lake Areas in Urban Fringes

Lake areas in urban fringes are under increasing urbanization pressure. Consequently, the conflict between rapid urban development and the maintenance of water bodies in such areas urgently needs to be addressed. An inexact chance-constrained linear programming (ICCLP) model for optimal land-use management of lake areas in urban fringes was developed. The ICCLP model was based on land-use suitability assessment and land evaluation. The maximum net economic benefit (NEB) was selected as the objective of land-use allocation. The total environmental capacity (TEC) of water systems and the public financial investment (PFI) at different probability levels were considered key constraints. Other constraints included in the model were land-use suitability, governmental requirements on the ratios of various land-use types, and technical constraints. A case study implementing the system was performed for the lake area of Hanyang at the urban fringe of Wuhan, central China, based on our previous study on land-use suitability assessment. The Hanyang lake area is under significant urbanization pressure. A 15-year optimal model for land-use allocation is proposed during 2006 to 2020 to better protect the water system and to gain the maximum benefits of development. Sixteen constraints were set for the optimal model. The model results indicated that NEB was between $1.48 × 10⁹ and $8.76 × 10⁹ or between $3.98 × 10⁹ and $16.7 × 10⁹, depending on the different urban-expansion patterns and land demands. The changes in total developed area and the land-use structure were analyzed under different probabilities (q _i ) of TEC. Changes in q _i resulted in different urban expansion patterns and demands on land, which were the direct result of the constraints imposed by TEC and PFI. The ICCLP model might help local authorities better understand and address complex land-use systems and develop optimal land-use management strategies that better balance urban expansion and grassland conservation.