基于指标规范值的室内空气客观评价的概率神经网络模型

为了建立简单、普适、通用的概率神经网络的室内空气评价模型,在适当设定室内空气各项指标的参照值及指标值的规范变换式基础上,使室内空气同级标准不同指标的规范值差异尽可能小,从而用规范值表示的各指标都可用同一个规范指标"等效"替代。因此,概率神经网络隐层各类模式的基函数中心矢量的各指标分量值与同级标准所有15项指标规范值的均值等同。将基于指标规范值的概率神经网络模型用于室内空气的评价实例进行检验,验证了该模型的普适性、通用性和简便性。     

An Analysis of Water Data Systems to Inform the Open Water Data Initiative

Improving access to data and fostering open exchange of water information is foundational to solving water resources issues. In this vein, the Department of the Interior's Assistant Secretary for Water and Science put forward the charge to undertake an Open Water Data Initiative (OWDI) that would prioritize and accelerate work toward better water data infrastructure. The goal of the OWDI is to build out the Open Water Web (OWW). We therefore considered the OWW in terms of four conceptual functions: water data cataloging, water data as a service, enriching water data, and community for water data. To describe the current state of the OWW and identify areas needing improvement, we conducted an analysis of existing systems using a standard model for describing distributed systems and their business requirements. Our analysis considered three OWDI‐focused use cases—flooding, drought, and contaminant transport—and then examined the landscape of other existing applications that support the Open Water Web. The analysis, which includes a discussion of observed successful practices of cataloging, serving, enriching, and building community around water resources data, demonstrates that we have made significant progress toward the needed infrastructure, although challenges remain. The further development of the OWW can be greatly informed by the interpretation and findings of our analysis.     

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

This article presents a two-stage maximum power point tracking (MPPT) controller using artificial neural network (ANN) for photovoltaic (PV) standalone system, under varying weather conditions of solar irradiation and module temperature. At the first-stage, the ANN algorithm locates the maximum power point (MPP) associated to solar irradiation and module temperature. Then, a simple controller at the second-step, by changing the duty cycle of a DC–DC boost converter, tracks the MPP. In this method, in addition to experimental data collection for training the ANN, a circuit is designed in MATLAB-Simulink to acquire data for whole ranges of weather condition. The whole system is simulated in Simulink. Simulation results show small transient response time, and low power oscillation in steady-state. Furthermore, dynamic response verifies that this method is very fast and precise at tracking the MPP under rapidly changing irradiation, and has very low power oscillation under slowly changing irradiation. Experimental results are provided to verify the simulation results as well.     

Dynamics of Policy Networks. The Case of Organic Farming Policy in the Czech Republic

To better understand the potential for successful and long-term establishment of environmental policy, the aim of this paper is to explore the network dynamics of a policy field that has become well established in the EU: organic farming. We look at the dynamics of the organic farming policy network in the Czech Republic over a period of 10 years by applying a comparative formal network analysis. We focused in particular on the distribution of power between actors and how capacities of policy actors have evolved between 2004 (its year of accession to the EU) and 2014. We conclude that the organic farming policy network in the Czech Republic has been highly dynamic and has changed from one that was decidedly influenced by organic sector organizations to a network centralized around the Ministry of Agriculture. However, the organic farming organization managed to maintain its good reputation for competence in organic farming policy, which creates opportunities for the organization to remain active in the policy debate.     

Understanding communicational behavior among rangelands’ stakeholders: application of social network analysis

Understanding communicational behavior of rangelands’ stakeholders is fundamental for effective development of rangeland management plans. This study aimed to understand differences between stakeholders’ relations among various actors involved in rangeland management using social network analysis (SNA). A survey was conducted on 334 stakeholders (89 extension agents, 110 researchers and 135 executive agents) in the Tehran province, Iran. Results showed that all the three groups of stakeholders are interested in making contact mainly within their own group. Furthermore, while the executive agents have shared the strongest technical and friendship relations with the two other groups, the extension agents established the strongest administrative interactions. The researchers, however, made a poor link especially with the extension agents. The study concluded that SNA could be an efficient tool to assess communicational behavior in rangeland management.     

基于灰色模型和模糊神经网络的综合水质预测模型研究

水质状态变化趋势预测研究对水资源管理和维护具有重要的现实意义。提出了一种将灰色模型和模糊神经网络相结合的水质预测模型。首先基于改进的灰色模型预测出水体中各理化因子在未来一段时间内的指标变化,然后采用T-S模糊神经网络对各单因子的预测值进行数据融合,构建水质变化综合趋势预测模型,预测出下一时间段的水质整体状态指标。实验表明,这种方式用来预测湖泊水质变化趋势具有可行性;与BP网络模型相比,基于T-S模糊神经网络系统的模型具有预测精度高、模型系统稳定等优越性。     

基于人工神经网络的半连续式混合厌氧消化产气量预测

研究采用BP神经网络和模糊神经网络(FNN)模型对逐步提高有机负荷的半连续式餐厨垃圾和猪粪混合厌氧消化试验进行日产气量预测.结果表明,BP神经网络模型的预测准确率为77.63％,FNN模型为82.33％,2种模型均可用于产气预测,但FNN模型在传统神经网络模型基础上加入了模糊控制,可提高其准确率,更适用于混合厌氧消化产气量预测.     

基于粗糙集和BP神经网络的流域水资源脆弱性预测研究——以淮河流域为例

水资源是一种重要的自然资源和经济资源,对其未来的脆弱性进行预测可以预估研究区未来的水安全状况,对其脆弱性问题做出预警,从而及时采取治理措施。因此,合理科学的水资源脆弱性预测研究是缓解水资源脆弱性的有效手段。目前,水资源脆弱性研究主要是针对水资源现状进行评价,对其未来状况的预测较少。集成了粗糙集和BP神经网络两种方法,首先采用改进了的盲目删除法对构建的流域水资源脆弱性评价指标体系进行约简,其次通过BP神经网络拟合约简后的指标数据与脆弱度之间的映射关系,构建流域水资源脆弱性评价预测模型。基于之前研究的样本数据和脆弱性结果,探讨淮河流域未来的水资源脆弱性状况。结果表明:淮河流域2015年、2020年和2025年的水资源脆弱度分别为0.305、0.359和0.390,处于轻度脆弱和中度脆弱的状况,除2015年脆弱性状况有所好转以外,2020年和2025年的水资源脆弱性程度与近几年相比有所加剧,根据指标数据可知该现象主要是受年降水量、人均用水量、万元GDP废水排放量、垦殖指数、有效灌溉面积比和干旱面积受灾比6个指标的影响,为避免水资源脆弱性的加剧,应当有针对性的加强这几个方面的管理和控制。     

Trophic structure of ecosystems and ecotoxicology of soil organisms

Studies on the ecotoxicology of soil organisms have led to the revision of views on the trophic structure of ecosystems. It was found that the microbial link is obligatory and controls the migration of toxicants and their effects in the food chain. Differences in effects are accounted for by both the physiological stability of organisms and their affliation with relatively independent and biogeochemically closed ecosystems differing in their spatiotemporal scales. The latter form a hierarchical three-level structure: ecosystems of unicellular organisms—ecosystems of small multicellular organisms—the ecosystem of large multicellular organisms, or of biogeocenosis. Trophic networks within the structure are united by ecosystemophagy as the type of feeding of large multicellular organisms, and this accounts for the importance of the latter as indicators of long-term changes in a biogeocenosis.     

生命线系统的震害耦联

在震害分析时,弧立地评价一个生命线系统的功能,不考虑与其它生命线系统间的耦联关系,可能会低估地震造成的损失。将地理信息系统（ＧＩＳ）与现有的震害预测方法结合起来,有利于推动新方法的研究。本文在ＧＩＳ环境下定义了网络失效率,提出了一种考虑不同生命线系统之间耦联关系的震害分析方法,给出了一个算例,并建议了相应的生产能力相关的震后应急抢修决策方案。