业务性防雹作业实时决策指挥系统的设计

本文论述了西北地区人工防雹业务性决策指挥的现状和面对的重要问题;探讨了目前无法识别的20%左右雹云在业务性防雹中的处理思路;以三级判别思路提出了业务性决策指挥系统的设计.     

铁路行车事故救援智能辅助决策系统研究

介绍了铁路行车事故救援智能辅助决策系统的设计及实现。采用产生式规则与数据库技术相结合的铁路行车事故救援决策知识表示方法。推理过程为正向推理。决策树分层分类并嵌入数据库。该系统可在行车事故现场以人机交互方式提供一个或几个救援方案。为铁路行车事故救援决策提供了一种新的途径与范例。并为人工智能在新的工程领域的应用进行了有益的尝试     

多目标决策-理想点法综合评价淮北市环境空气质量

运用多目标决策-理想点法对淮北市环境空气质量进行评价,评价结果表明淮北市环境空气质量达到了2级标准以上,能够达到淮北市环境空气功能区划要求。     

Public Participation Mechanisms in Environmental Disasters

This paper examines the role of public participation mechanisms in certain major environmental disasters. It examines situations in which people’s lifestyles or their lives have been directly threatened, and thus elicited citizen participation. Threatening issues often seem morally, physically, socially, economically, religiously, and otherwise unacceptable to a group. As will be presented in this paper, citizens voluntarily participate in a community activity when they see that their way of life has been threatened. An introductory historical perspective, the legal framework upon which it is based, and background information on the participatory mechanisms, all emphasizing the importance and need for empowering citizens with participatory skills so as to bring changes in the existing educational, legal, and social systems are presented. The major environmental accidents/disasters of Minamata, Japan; Bhopal, India; Seveso, Italy; Chernobyl, Ukraine; and Exxon-Valdez, Alaska are discussed, mainly to indicate the reaction, and the participatory mechanisms used by the affected communities in each of the sudden disasters that occurred. If citizens worldwide had been active participants in the environmental issues, it is quite possible that we would have experienced fewer environmental accidents.     

县域土壤资源管理与施肥决策信息系统的建立——以北京市平谷区为例

以作物推荐施肥模型为智能决策支撑,建立了基于地块的县域土壤资源管理与施肥决策信息系统。该系统采用C/S和B/S混合结构,采用Delphi开发语言和GIS组件技术,对GIS、数据库和模型进行耦合与集成,实现了土壤资源和决策信息查询、更新;养分资源管理决策与咨询;耕地质量评价;耕地环境质量预警等四个主要功能。系统在北京市平谷区得到应用和验证,应用表明该系统对于区域土壤资源信息高效管理、决策和面向公众的土壤信息服务具有重要意义。     

Linking Ecological Science to Decision-Making: Delivering Environmental Monitoring Information as Societal Feedback

The paper describes the Ecological Monitoring and Assessment Network's (EMAN) operational and program response to certain challenges of environmental monitoring in Canada, in particular, efforts to improve the ability of the network to deliver relevant information to decision makers. In addition to its familiar roles, environmental monitoring should deliver feedback to society on environmental changes associated with development patterns, trends, processes and interventions. In order for such feedback to be effective, it must be relevant, timely, useful and accessible: all characteristics that are defined by the user, not the provider. Demand driven environmental monitoring is explored through EMAN's experiences with Canada's Biosphere Reserves, the NatureWatch Program and the Canadian Community Monitoring Network.     

Artificial Neural Networks for Risk Decision Support in Natural Hazards: A Case Study of Assessing the Probability of House Survival from Bushfires

Risk decision-making in natural hazards encompasses a plethora of environmental, socio-economic and management-related factors, and benefits greatly from exploring possible patterns and relations among these multivariate factors. Artificial neural networks, capable of general pattern classifications, are potentially well suited for risk decision support in natural hazards. This paper reports an example that assesses the risk patterns or probabilities of house survival from bushfires using artificial neural networks, with a simulation data set based on the empirical study by Wilson and Ferguson (Predicting the probability of house survival during bushfires, Journal of Environmental Management 23 (1986) 259–270). The aim of this study was to re-model and predict the relationship between risk patterns of house survival and a series of independent variables. Various configurations for input and output variables were tested using neural networks. An approach for converting linguistic terms into crisp numbers was used to incorporate linguistic variables into the quantitative neural network analysis. After a series of tests, results show that neural networks are capable of predicting risk patterns under all tested configurations of input and output variables, with a great deal of flexibility. Risk-based mathematical functions, be they linear or non-linear, can be re-modelled using neural networks. Finally, the paper concludes that the artificial neural networks serve as a promising risk decision support tool in natural hazards.     

Using triple bottom line metrics and multi-criteria methodology in corporate settings

With the growing importance of environmental sustainability in the corporate sector, businesses are compelled to progress from assessing and benchmarking their environmental impact to making decisions on how to prioritize impact reduction alternatives. Most often, business decisions are driven by financial metrics, but with sustainability improvements becoming a business goal, it is also important to assess metrics from environmental and social spheres; nevertheless, practically and systematically performing such an assessment is challenging. We present an application of a multi-criteria decision analysis (MCDA) method that addresses the aforementioned challenges in a corporate setting. Our case study company – one of the largest inland marine freight carriers in the United States – promotes a business culture focused on financially viable, yet socially and environmentally responsible solutions. Thus, we combine life cycle analysis (LCA), financial calculation methods, and corporate surveys to quantify environmental, economic, and social performance measures, respectively. Multiattribute utility theory is integrated with analytic hierarchy processes (AHPs) and fuzzy analysis to create a carefully designed framework for corporations with diverse groups of stakeholders. With company leadership, implementation is feasible and successful at prioritizing alternatives among diverse stakeholders. The process provides a platform for negotiation and promotes discussions on decision drivers. The use of MCDA methodologies promoted the inclusion of a suite of metrics that aligned with the company's sense of social and environmental responsibility, generating an in-depth analysis of the alternatives that factored in other things besides economics. Return-on-investments (ROI) calculations, the typical approach used in the corporate setting, would have required significantly less time and effort from the company, but the results of our MCDA application indicated that inclusion of triple bottom line metrics delve deeper into stakeholder preferences. Thus, our case study company gained a holistic view of the candidate alternatives, in addition to creating a platform for structured discussions about company goals and priorities.