基于AGA-BP神经网络的采空区危险性评价

针对采空区危险性评价的影响因素众多且关系复杂的特点,提出了基于AGA-BP神经网络算法评价采空区危险性。将岩体结构、地质构造、岩石抗压强度等13个影响因子作为神经网络输入,采空区危险性等级作为输出,建立一个采空区危险性评价的BP神经网络模型;采用自适应遗传算法(AGA)对BP网络的初始权值和阈值进行全局寻优,将寻优结果回代入网络中进行训练并预测得出采空区危险性等级;利用其它智能算法与该预测结果做出比较,以验证AGA-BP算法的有效性及优越性。结果表明:该算法的优化效果明显,同时在训练时间与预测精度上较其它智能算法有突出的优势,是一种在采空区危险性评价方面值得推广的新方法。     

公路路网建设项目声环境影响评价研究

以甘肃省某市新区基础设施建设中的路网建设为例,根据公路路网的交通参数、道路地形地貌条件、路面设施等,利用导则推荐模式预测路网噪声贡献值。该新区路网中道路距离多在500m以上,不论道路平行还是相交,噪声影响以主干道为主,以次干道为辅,相互影响;根据路网噪声环境影响的特点,提出切实可行的声环境影响减缓措施。     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

基于BP神经网络优化制备Cu-Ce/TiO_2及其光催化活性研究

采用Cu和Ce对TiO2进行改性,基于正交实验设计和BP神经网络研究了Cu-Ce/TiO2中Cu-Ce对TiO2的摩尔百分数、Cu-Ce/TiO2中CuCe摩尔比及Cu-Ce/TiO2烧结温度对Cu-Ce/TiO2光催化降解甲醛溶液性能的影响.同时,对Cu-Ce/TiO2制备方案进行了优化,并运用X射线衍射仪、扫描电子显微镜和紫外-可见分光光度计对最佳条件下制备的Cu-Ce/TiO2进行表征.结果表明,优化的制备条件为Cu-Ce/TiO2中Cu-Ce对TiO2的摩尔百分数为2.88%,Cu-Ce/TiO2中Cu-Ce的摩尔比为1∶1,Cu-Ce/TiO2的烧结温度为570℃.共掺杂Cu离子和Ce离子能有效避免掺杂TiO2晶格内部表层和近表层产生较多的位错,从而抑制晶格畸变增大;诱导TiO2中锐钛矿型晶体向金红石型晶体转变的能力增强,有效抑制电子-空穴对的复合,产生介电局域效应.     

Enhancing soil aggregation and acetamiprid adsorption by ecofriendly polysaccharides hydrogel based on Ca2+- amphiphilic sodium alginate

Soil aggregation plays an important role in agricultural production activities. However, the structure of soil aggregation is destroyed by the natural environment and unreasonable farming management, resulting in the loss of water, fertilizers and pesticides in soil. At present, hydrogels have been widely reported to promote the formation of soil aggregation. In this paper, amphiphilic calcium alginate (ASA/Ca²⁺) was applied to promote the formation of soil aggregation and enhance pesticide retention. Initially, an ASA was obtained through the one-pot Ugi condensation (a four-component green chemical reaction). Then, ASA/Ca²⁺ hydrogel is prepared by Ca²⁺ cross-linking. The formation of soil aggregation was determined through the Turbiscan Lab Expert stability analyzer, Confocal Laser Scanning Microscope (CLSM), and Transmission Electron Microscope (TEM). And the effect of soil aggregation on acetamiprid environmental behavior was investigated by adsorption kinetics, adsorption isotherms, and leaching. The results shown that the three-dimensional network structure of ASA/Ca²⁺ hydrogel can promote the formation of soil aggregation. Aggregate durability index (ADI) was 0.55 in the presence of ASA/Ca²⁺ hydrogel, indicating that amphiphilic hydrogel can enhance the stability of soil aggregation. The adsorbing capacity of acetamiprid was 1.58 times higher than pure soil, and the release of acetamiprid only about 20% in the presence of ASA/Ca²⁺ hydrogel. These results would be helpful for the formation of soil aggregation and pesticides adsorption on soil aggregation. Thus, ASA/Ca²⁺ hydrogel is likely to improve soil quality, simultaneously it can minimize the mobility of pesticides in the agricultural system.     

基于不变矩理论的腐蚀等级评定方法研究

基于腐蚀图像包含大量腐蚀信息的客观现实,将数字图像技术和不变矩理论应用于腐蚀图像预处理和特征提取,用腐蚀图像的7个不变矩特征值来描述腐蚀形貌特征,利用概率神经网络模式识别技术,建立了以不变矩为特征参数的概率神经网络模式识别模型,实现了金属材料腐蚀等级的评定。以铝合金材料在EXCO溶液中加速腐蚀等级评定为例,分析表明,不变矩作为一种高度浓缩的图像特征,能够表示腐蚀形貌与腐蚀特征的映射关系,该方法简单易行,识别率可达到87.95%,满足工程应用要求。     

Climate change in mountain regions: how local communities adapt to extreme events

This paper examines how local communities adapt to climate change and how governance structures can foster or undermine adaptive capacity. Climate change policies, in general, and disaster risk management in mountain regions, in particular, are characterised by their multi-level and multi-sectoral nature during formulation and implementation. The involvement of numerous state and non-state actors at local to national levels produces a variety of networks of interaction and communication. The paper argues that the structure of these relational patterns is critical for understanding adaptive capacity. It thus proposes an expanded concept of adaptive capacity that incorporates (horizontal and vertical) actor integration and communication flow between these actors. The paper further advocates the use of formal social network analysis to assess these relational patterns. Preliminary results from research on adaptation to climate change in a Swiss mountain region vulnerable to floods and other natural hazards illustrate the conceptual and empirical significance of the main arguments.     

Social capital networks for achieving sustainable development

There have been few empirical studies investigating whether and how social capital (SC) relates to better achievement of sustainability goals and, if so, how. This research investigates the roles three types of SC, namely, bonding, bridging, and bracing SC, play in achieving sustainable development (SD), using a case study of the Japanese region to explore the process of SC accumulation leading to collective action. The research question as to whether SC accumulation makes a difference in the progress towards sustainability is addressed qualitatively and quantitatively using a case study, and network and regression analysis; in particular the impact and functions of bracing SC are closely investigated. The study concludes that SC accumulation can indeed make a difference in achieving sustainability and that bracing SC plays an essential role in expediting the processes of goal sharing and resource flow by connecting various networks across sectors and scales, thereby making collective action possible. These findings suggest that creating an environment in which the generation of all three types of SC is encouraged may help local governments to achieve their desired policy goals for SD.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.