基于Fuzzy模型的职业病危害综合风险评估方法研究

为有效评估作业场所职业病危害的风险大小,研究职业病危害综合风险评估方法。在综合考虑作业场所职业病危害的固有危害特征、接触特征、防护特征和健康影响特征等风险影响因素的基础上,采用层次分析和专家咨询法筛选和建立了职业病危害综合风险评价指标体系,研究制定了各评价指标的分级评价准则,利用模糊数学理论,构建了基于Fuzzy模型的职业病危害综合风险评价模型。该方法可以对职业病危害的综合风险进行评估,并能够确定风险控制的优先权,避免了传统单一指标评价的局限性,对职业病危害评价工作具有一定借鉴意义。     

Exploring price effects on the residential water conservation technology diffusion process: a case study of Tianjin city

Reforms of the water pricing management system and the establishment of a flexible water pricing system are significant for cities in northern China to tackle their critical water issues. The WATAP (Water conservation Technology Adoption Processes) model is developed in order to capture the water conservation technology adoption process under different price scenarios with disaggregate water demands down to the end use level. This model is explicitly characterized by the technological selection process under maximum marginal benefit assumption by different categories of households. In particular, when households need to purchase water devices in the provision market with the consideration of complex factors such as the life span, investment and operating costs of the device, as well as the regulated water price by the government. Applied to Tianjin city, four scenarios of water price evolutions for a long-term perspective (from year 2011 to 2030) are considered, including BAU (Business As Usual), SP1 (Scenario of Price increase with constant annual rate), SP2 (Scenario of Price increase every four years) and SP3 (Scenario of Price increase with affordable constraint), considering many factors such as historic trends, affordability and incentives for conservation. Results show that on aggregate 2.3%, 11.0% and 18.2% of fresh water can be saved in the residential sector in scenario SP1, SP2 and SP3, respectively, compared with the BAU scenario in the year 2030. The water price signals can change the market shares of different water appliances, as well as the water end use structure of households, and ultimately improve water use efficiency. TheWATAP model may potentially be a helpful tool to provide insights for policy makers on water conservation technology policy analysis and assessment.     

On equilibrium in resource markets with scale economies and stochastic prices

In this paper, I show the existence and the characteristics of equilibrium in a non-renewable resource market where extraction costs are non-convex and market price is subject to stochastic shocks, an empirically relevant setting. In my model firms may be motivated to hold inventories to facilitate production smoothing, which allows them to continue producing at a smooth pace at any instant when extraction ceases, e.g. when reserves are exhausted. This aspect of the model then supports a competitive equilibrium in the presence of non-convex costs. Casual empirical evidence is provided that supports the central features of my model for a variety of non-renewable resources, lending credence to the explanation for equilibrium I propose.     

一株花生根际促生菌的筛选鉴定及其特性研究

从种植于红壤的健康花生根际,筛选出7株产吲哚乙酸(IAA)菌株,以菌株L4合成IAA的能力最强,培养24 h时IAA产生量达135.67μg.mL-1,且菌株L4具有解磷能力。通过菌株形态、生理生化特征测定及16SrRNA的保守序列鉴定,初步确定菌株L4为氯酚节杆菌(Arthrobacter chlorophenolicus),其GenBank登录号为JQ277449。菌株生长和发酵条件试验结果表明,菌株L4生长和分泌IAA的最佳培养条件并不完全一致,既能促进菌株生长又能合成较多IAA的最佳培养条件是初始pH值为5～6,装液量为50 mL.(250 mL)-1,30℃摇床培养24 h;促进菌株生长的最佳碳、氮源分别是麦芽糖和酵母粉,而提高IAA产生量的最佳碳源是木糖,最佳氮源是KNO3。     

Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines

Rockburst possibility prediction is an important activity in many underground openings design and construction as well as mining production. Due to the complex features of rockburst hazard assessment systems, such as multivariables, strong coupling and strong interference, this study employs support vector machines (SVMs) for the determination of classification of long-term rockburst for underground openings. SVMs is firmly based on the theory of statistical learning algorithms, uses classification technique by introducing radial basis function (RBF) kernel function. The inputs of models are buried depth H, rocks’ maximum tangential stress σ_θ, rocks’ uniaxial compressive strength σ_c, rocks’ uniaxial tensile strength σ_t, stress coefficient σ_θ/σ_c, rock brittleness coefficient σ_c/σ_t and elastic energy index W_et. In order to improve predictive accuracy and generalization ability, the heuristic algorithms of genetic algorithm (GA) and particle swarm optimization algorithm (PSO) are adopted to automatically determine the optimal hyper-parameters for SVMs. The performance of hybrid models (GA + SVMs = GA-SVMs) and (PSO + SVMs = PSO-SVMs) have been compared with the grid search method of support vector machines (GSM-SVMs) model and the experimental values. It also gives variance of predicted data. A rockburst dataset, which consists of 132 samples, was employed to evaluate the current method for predicting rockburst grade, and the good results of overall success rate were obtained. The results indicated that the heuristic algorithms of GA and PSO can speed up SVMs parameter optimization search, the proposed method is robust model and might hold a high potential to become a useful tool in rockburst prediction research.     

Research on flood risk analysis and evaluation method based on variable fuzzy sets and information diffusion

Floods have become increasingly alarming worldwide. Flood risk management in terms of assessing disaster risk properly is a great challenge that society faces today. Natural disaster risk analysis is typically beset with issues such as imprecision, uncertainty, and partial truth. There are two basic forms of uncertainty related to natural disaster risk assessment, namely, randomness caused by inherent stochastic variability and fuzziness due to macroscopic grad and incomplete knowledge sample. However, the traditional probability statistical method ignores the fuzziness of risk assessment with incomplete data sets and requires a large sample size of data. The fuzzy set methodology is introduced in the area of disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The present paper puts forward a composite method based on variable fuzzy sets and information diffusion method for disaster risk assessment. The results indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management. We hope that by conducting such risk analysis, the impact of flood disasters can be mitigated in the future.     

教练直升机训练系统安全评价研究

为保证教练直升机的使用安全,预防事故发生,针对当前教练直升机安全风险决策数据量少、存在模糊的特点,提出基于模糊D-S证据理论的教练直升机训练系统安全评价模型。从人-机-环-管4个系统出发,建立教练直升机训练系统安全评价指标体系,运用模糊评价技术评估教练直升机系统安全影响因素,利用D-S证据理论的层次递归算法对不同层次影响因素的评估等级进行合成,并以某型教练直升机为例,给出评价步骤。结果表明:该方案适用于研究教练直升机训练系统安全评价;根据安全性量化值,能够实现按安全性能优劣对系统的快速排序。     

基于机会约束规划的航班应急调度问题研究

为应对民航突发情况,保障民航运行安全,提出应急调度这一概念。阐述常规情况下航班调度基本模型,分析其在应急情况下的弊端。引入机会约束,构建应对突发状况的应急调度模型。研究兼顾航空公司成本、航班运行安全及旅客随机需求的机型分配问题(FAP)模型和机组排班问题(CSP)模型。比较混合智能算法、隐枚举法、等价转化法的优缺点及适用度。根据案例数据,使用Matlab软件编程,并采用随机模拟与粒子群(PSO)算法相结合的智能算法对模型求解。结果表明,机会约束规划模型在考虑随机因素的情况下,比基本模型更符合实际动态环境。     

建筑施工事故非线性灰色伯努利模型预测

为提高建筑施工事故灰色预测模型精度,在传统GM(1,1)模型基础上,建立非线性灰色伯努利模型(NGBM),并采用粒子群优化(PSO)算法对参数进行优选。以2001—2011年全国建筑事故死亡人数统计数据为基础,运用该模型对2012—2013年的相应人数进行预测,并与GM(1,1)模型和灰色Verhulst模型的结果相对比。结果表明,NGBM拟合精度最好,平均相对误差仅为2.65%,验证了模型的可行性和准确性。     

带混合时间窗的多目标危险化学品运输路径优化

为降低危险化学品运输风险,使路径选择更加科学、切合实际,从责任主体、社会影响等方面综合考虑危险化学品运输相关主体,根据各主体目标对影响运输路径选择的指标进行重新识别和细分,提出5大指标体系。应用熵权法计算出各指标权重,建立混合时间窗条件下的多目标危化品运输路径优化模型,通过改进的多目标遗传算法求出Pareto最优解。结果表明,不同时间点出发会产生不同的Pareto最优解,并且可得到每条最优路径的出发时间窗,每个最优解代表了某项指标达到相对最优时的路径。混合时间窗较符合实际情况,基于出发时间窗及生成的多条最优路径,决策者可根据决策偏好及关注重点以较高效率选出最合适的路径。