道路交通安全知识提取方法及其递进式模型的研究

道路交通数据资源日益膨胀和复杂化 ,已经远远超出了人脑的记忆和分析能力。面对道路交通的海量数据 ,传统运用的DBMS和OLTP技术 ,已无法发现隐藏在数据背后的关系、规则和发展趋势等新的内容、知识和信息。因此 ,建立基于DMKD的智能道路交通安全决策支持系统是相关部门急需解决的重大课题。笔者重点介绍了数据挖掘、知识发现的概念 ,提出了基于DW +OLAP +DMKD的道路交通安全决策支持系统 ,通过道路交通系统的要素分析 ,介绍了一种面向属性的粗糙集方法提取规则 ,并阐述了一种递进式规则评价提炼过程。     

生物多样性保护规制工具更新——规范层面的分析

生物多样性保护法律的有效执行,应立足于具体规制工具的设计。生物多样性保护立法涉及三个主要法律领域——物种保育法、自然保护地法和生物安全法,从法律规范层面分析,这三个法律领域对规制工具的偏好与选择呈现出"硬者极硬,刑罚优先,软者无力"的整体格局。本文以生物多样性保护原理对现行规制工具进行检验,物种保育法和自然保护地法应以规制领域的去极端化为导向进行规制工具更新,一方面要软化甚至去除极硬规制,与此同时应建立完善行政合同、行政指导、行政奖励等柔性规制工具,赋予其可操作性,使之柔而有力。     

Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives

Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (Spectrum) to optimize timber harvest schedules, then a simulation model (HARVEST) to project those schedules in a spatially explicit way and produce maps from which the spatial pattern of habitat could be calculated. We demonstrated the power of this approach by evaluating alternative plans developed for a national forest plan revision in Wisconsin, USA. The amount of forest interior habitat was inversely related to the amount of timber cut, and increased under the alternatives compared to the current plan. The amount of edge habitat was positively related to the amount of timber cut, and increased under all alternatives. The amount of mature northern hardwood interior and edge habitat increased for all alternatives, but mature pine habitat area varied. Mature age classes of all forest types increased, and young classes decreased under all alternatives. The average size of patches (defined by age class) generally decreased. These results are consistent with the design goals of each of the alternatives, but reveal that the spatial differences among the alternatives are modest. These complementary models are valuable for quantifying and comparing the spatial effects of alternative management strategies.     

Non-powered hand tool improvement research for prevention of work-related problems: a review

Purpose. In lower-middle-income countries, most of the work is performed manually using non-ergonomic hand tools which results in work-related health problems. Using hand tools designed in line with ergonomic principles may play an important role in reducing work-related health concerns significantly. Methods. Scientific databases (PubMed, EBSCOhost) and e-publishers were searched for articles from 1985 to 2015 using the following keywords: ‘hand tool’, ‘ergonomics’, ‘usability’ and ‘design’. After applying selection criteria to 614 articles, 58 articles related to the physical design of hand tools were selected. Results. Seventeen articles were related to hand tool improvement in the manufacturing sector. Musculoskeletal disorders were found to be the most frequently occurring work-related health problems. Most of the articles focused on product and qualitative variables for improvement in hand tools, while few articles considered human and task variables. Conclusions. Literature shows that hand tool improvement studies have been given less importance in low-income and lower-middle-income countries. However, some work of significance is reported in the agriculture sectors of these countries. Hence, it is concluded that ergonomic intervention in hand tools is much needed for those industries which employ traditional methods of working.     

PDE accident model from a safety information perspective and its application to Zhangjiakou fire and explosion accident

Accident models can provide theoretical frameworks for determining the causes and mechanisms of accidents, and thus are theoretical bases for accident analysis and prevention. The role of safety information in accident causation is profound. Thus, safety information is an important and essential perspective for developing accident models. This study presents a new accident model developed from a safety information perspective, called the Prediction—Decision—Execution (PDE) accident model. Because the PDE accident model is an emerging accident model that was proposed in 2018, its analysis logic and viability remain to be discussed. Thus, the main contributions of this study include two aspects: (i) detailed explanation of the analysis logic of the PDE accident model, and (ii) case-study examination of the Zhangjiakou fire and explosion accident, a serious accident that occurred in China in 2018, to demonstrate the viability of the PDE accident model. Results show that this is a safety-information-driven accident model that can provide a new and effective methodology for accident analysis and prevention, and safety management.     

Can level of safety climate predict level of orientation toward safety in a decision making task?

Establishing the relationship between level of safety climate and safety performance is a current challenge. This work examines the relationship between level of safety climate and orientation toward safety in the decision making process and choice. Alternatively, this work seeks to answer the question of whether level of safety climate can predict safety-oriented decision making. A generalized safety climate questionnaire and a decision making simulation are utilized to examine this relationship. The results indicate that level of safety climate is not a significant predictor of the decision process; however, it was found to be a significant predictor of the selection of safer choices.     

Recursive Operability Analysis as a decision support tool for Risk-Based Maintenance

This work was developed with the support of MEMC, one of the most important producers of ultra-pure silicon wafers for electronic applications throughout the world. The availability of ultra-pure water is of prime importance in the silicon production process. In order to maximize the availability of UP water, MEMC has developed a preventive maintenance program and a detailed record of each maintenance intervention is recorded. This has allowed a complete failure rate data bank to be developed. In order to optimize the maintenance intervention, a Recursive Operability Analysis (ROA) has been used as a decision support tool. The results of the ROA, coupled with the failure rates, have made it possible to calculate the expected number of events (ENE) of various top events (TEs). The magnitude of each TE has been estimated on the basis of the monetary losses provoked by each event. The risk then has been calculated and the events ranked on this basis. Maintenance policies have been optimized with the aim of reducing the risk of the top ranked events.     

Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine1

Abstract: With the popularity of complex, physically based hydrologic models, the time consumed for running these models is increasing substantially. Using surrogate models to approximate the computationally intensive models is a promising method to save huge amounts of time for parameter estimation. In this study, two learning machines [Artificial Neural Network (ANN) and support vector machine (SVM)] were evaluated and compared for approximating the Soil and Water Assessment Tool (SWAT) model. These two learning machines were tested in two watersheds (Little River Experimental Watershed in Georgia and Mahatango Creek Experimental Watershed in Pennsylvania). The results show that SVM in general exhibited better generalization ability than ANN. In order to effectively and efficiently apply SVM to approximate SWAT, the effect of cross‐validation schemes, parameter dimensions, and training sample sizes on the performance of SVM was evaluated and discussed. It is suggested that 3‐fold cross‐validation is adequate for training the SVM model, and reducing the parameter dimension through determining the parameter values from field data and the sensitivity analysis is an effective means of improving the performance of SVM. As far as the training sample size, it is difficult to determine the appropriate number of samples for training SVM based on the test results obtained in this study. Simple examples were used to illustrate the potential applicability of combining the SVM model with uncertainty analysis algorithm to save efforts for parameter uncertainty of SWAT. In the future, evaluating the applicability of SVM for approximating SWAT in other watersheds and combining SVM with different parameter uncertainty analysis algorithms and evolutionary optimization algorithms deserve further research.     

Impact Assessment and Recommendation of Alternative Conjunctive Water Use Strategies for Salt Affected Agricultural Lands through a Field Scale Decision Support System – A Case Study

Conjunctive use of saline/non-saline irrigation waters is generally aimed at minimizing yield losses and enhancing flexibility of cropping, without much alteration in farming operations. Recommendation of location-specific suitable conjunctive water use plans requires assessment of their long-term impacts on soil salinization/sodification and crop yield reductions. This is conventionally achieved through long-term field experiments. However such impact evaluations are site specific, expensive and time consuming. Appropriate decision support systems (DSS) can be time-efficient and cost-effective means for such long-term impact evaluations. This study demonstrates the application of one such (indigenously developed) DSS for recommending best conjunctive water use plans for a, rice-wheat growing, salt affected farmer’s field in Gurgaon district of Haryana (India). Before application, the DSS was extensively validated on several farmers and controlled experimental fields in Gurgaon and Karnal districts of Haryana (India). Validation of DSS showed its potential to give realistic estimates of root zone soil salinity (with R = 0.76–0.94; AMRE = 0.03–0.06; RMSPD = 0.51–0.90); sodicity (with R = 0.99; AMRE = 0.02; RMSPD = 0.84) and relative crop yield reductions (AMRE = 0.24), under existing (local) resource management practices. Long term (10 years) root zone salt build ups and associated rice/wheat crop yield reductions, in a salt affected farmer’s field, under varied conjunctive water use scenarios were evaluated with the validated DSS. It was observed that long-term applications of canal (CW) and tube well (TW) waters in a cycle and in 1:1 mixed mode, during Kharif season, predicted higher average root zone salt reductions (2–9%) and lower rice crop yield reductions (4–5%) than the existing practice of 3-CW, 3-TW, 3-CW. Besides this, long-term application of 75% CW mixed with 25% TW, during Rabi season, predicted about 17% lower average root-zone salt reductions than the cyclic applications of (1-CW, 1-TW, 2-CW) and (2-CW, 1-TW, 1-CW, i.e., existing irrigation strategy). However, average wheat crop yield reductions (16–17%) simulated under all these strategies were almost at par. In general, cyclic-conjunctive water use strategies emerged as better options than the blending modes. These results were in complete confirmation with actual long-term conjunctive water use experiments on similar soils. It was thus observed that such pre-validated tools could be efficient means for designing, local resource and target crop yield-specific, appropriate conjunctive water use plans for irrigated agricultural lands.     

Interval-parameter Fuzzy-stochastic Semi-infinite Mixed-integer Linear Programming for Waste Management under Uncertainty

An interval-parameter fuzzy-stochastic semi-infinite mixed-integer linear programming (IFSSIP) method is developed for waste management under uncertainties. The IFSSIP method integrates the fuzzy programming, chance-constrained programming, integer programming and interval semi-infinite programming within a general optimization framework. The model is applied to a waste management system with three disposal facilities, three municipalities, and three periods. Compared with the previous methods, IFSSIP have two major advantages. One is that it can help generate solutions for the stable ranges of the decision variables and objective function value under fuzzy satisfaction degree and different levels of probability of violating constraints, which are informative and flexible for solution users to interpret/justify. The other is that IFSSIP can not only handle uncertainties through constructing fuzzy and random parameter, but also reflect dynamic features of the system conditions through interval function of time over the planning horizon. By comparing IFSSIP with interval-parameter mixed-integer linear semi-infinite programming and parametric programming, the IFSSIP method is more reasonable than others.