强化环境监测管理提高环境监测地位

总结和回顾了我国环境监测工作开展近三十年来所取得的非凡成绩,阐述了目前环境监测工作同整个环境保护事业相比较,同国外环境监测相比较存在的不足,并进一步提出了以"强化环境监测管理,提高环境监测地位"为核心的几点建议,旨在使我国的环境监测工作能更好地为环境保护和经济建设服务.     

Monitoring Forest Carbon Sequestration with Remote Sensing and Carbon Cycle Modeling

Sources and sinks of carbon associated with forests depend strongly on the management regime and spatial patterns in potential productivity. Satellite remote sensing can provide spatially explicit information on land cover, stand-age class, and harvesting. Carbon-cycle process models coupled to regional climate databases can provide information on potential rates of production and related rates of decomposition. The integration of remote sensing and modeling thus produces spatially explicit information on carbon storage and flux. This integrated approach was employed to compare carbon flux for the period 1992–1997 over two 165-km² areas in western Oregon. The Coast Range study area was predominately private land managed for timber production, whereas the West Cascades study area was predominantly public land that was less productive but experienced little harvesting in the 1990s. In the Coast Range area, 17% of the land base was harvested between 1991 and 2000. Much of the area was in relatively young, productive-age classes that simulations indicate are a carbon sink. Mean annual harvest removals from the Coast Range were greater than mean annual net ecosystem production. On the West Cascades study area, a relatively small proportion (< 1%) of the land was harvested and the area as a whole was accumulating carbon. The spatially and temporally explicit nature of this approach permits identification of mechanisms underlying land base carbon flux. Published online     

改进BP算法在煤与瓦斯突出预测中的应用

为了正确预测煤与瓦斯突出的趋势与危险性 ,基于反向BP神经网络 ,笔者提出了一种改进的BP网络模型 :为了加快BP网络的收敛速度 ,增强其跳出局部极小点的能力 ,采用了自适应变步长法和改进模拟退火法 (SA法 )相结合的方法。实际应用表明 ,该模型收敛速度快 ,准确性高 ,具有较高的可靠性和实用性 ,是一种十分有效的煤与瓦斯突出危险性预测方法。     

Evaluation of leachate composition by multivariate data analysis (MVDA)

Landfills generate emissions in the form of gas and leachate. The emissions are often measured within monitoring programmes. It is likely that the requirements of such monitoring programmes can be extended in the future, particularly in light of the increased interest in specific organic substances. Multivariate data analyses (MVDA) have been used to evaluate the possibility of predicting the content of specific organic substances from more common analyses. The results indicate that this is possible for a specific leachate. MVDA can also be used to reduce the number of analyses performed within existing monitoring programmes while retaining information about all the variables formerly included in the programmes.     

Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.     

Detecting Changes in Natural Resources Using Land Condition Trend Analysis Data

The Land Condition Trend Analysis (LCTA) program is the US Army's standard for land inventory and monitoring, employing standardized methods of natural resources data collection, analyses, and reporting designed to meet multiple goals and objectives. Critical to using LCTA data in natural resources management decisions is the ability of the LCTA protocols to detect changes in natural resources. To quantify the ability of LCTA protocols to detect resource changes, power analysis techniques were used to estimate minimum detectable effect sizes (MDES) for selected primary and secondary management variables for three Army installations. MDES for a subset of primary variables were estimated using data from 27 installation LCTA programs. MDES for primary and secondary variables varied widely. However, LCTA programs implemented at larger installations with lower sampling intensities detected changes in installation resources as well as programs implemented at smaller more intensively sampled installations. As a national monitoring program that is implemented at individual installations, LCTA protocols provide relatively consistent monitoring data to detect changes in resources despite diverse resource characteristics and implementation constraints.     

The Information Cycle as a Framework for Defining Information Goals for Water-Quality Monitoring

/ The necessity to tailor information becomes increasingly urgent as the information revolution continues to generate ever-increasing flows of data and so-called information. From European experiences, a new approach for monitoring system design is suggested in this paper. In this approach, careful and detailed specification of information needs is a major contributing factor to the effectiveness of information products. To develop better specifications for information products, the process of collecting and transforming data into useful information requires careful thought and guidance. A dialogue between information users on one hand and information producers on the other is essential. This dialogue can be based on the information cycle, describing the continuous process from specifying information needs for water management and a strategy to collect information through data collection and data analysis up to utilization of information by water management. By following the respective steps in the information cycle, the process of information gathering can be completed. The cyclic character provides a quantitative means of connecting monitoring system design and operations with the information expectations and/or products required by management.     

组合优化的能源消费量预测模型

针对非等间距灰色系统预测中存在误差较大的问题，结合序列本身的特点，利用世界能源消费的历史数据，采用3种灰色预测模型与神经网络进行组合优化，建立了灰色神经网络的能源消费量组合预测模型。实证分析结果表明，提高了模型的拟合和预测精度，拓宽了应用范围。该模型可对能源的消费趋势进行预测，为科学分析能源结构提供依据。     

网络安全中的蜜罐技术和蜜网技术

当前，网络安全正在受到严重的威胁，传统的防御技术存在其固有的被动防御的缺陷，而蜜罐技术正以其主动防御的特性受到越来越多的关注。本文说明了其在网络安全中所起到的防御作用和通过收集信息而起到的研究作用，讨论了涉及到的诱骗机制、数据控制、数据捕获和数据分析等关键技术以及实际应用中的部署方案。     

深水平台施工过程自然风险定量评估

在分析现有风险理论的基础上,结合海洋施工实际,提出了一种对海洋施工自然风险进行定量评估的模型。根据目标系统各风险事件与影响因素之间存在高度非线性复杂映射的特点,提出了利用BP神经网络拟合方法,对主要风险事件发生概率进行量化的模型。针对传统的梯度下降优化算法收敛速度慢的特点,采用可避免计算Hesse矩阵的Levenberg-Marquardt算法来训练神经网络。这一模型可以模拟专家评价,并准确地按照专家的评定法则进行估算,具有一定的通用性。