基于Landsat 8遥感数据的天津市地表温度反演

以Landsat 8遥感数据为数据源,进行天津市地表温度反演研究。首先采用单通道算法反演地表温度,并利用均值标准差法进行温度分级。然后建立不同温度等级面积比例的估算模型。再通过随机样点,从不同温度等级和土地覆盖类型2个角度,分别建立并比较不同类样点的地表温度与各指数的拟合模型。结果表明:次高温区域面积比例与人口密度、人均GDP都具有较高的决定系数;地表温度与NDVI、BAEM的二元线性回归决定系数高于地表温度与单一指数的决定系数;将样点分类后,低温点与MNDBI的决定系数高于其他温度等级样点,水域和植被样点与各种指数的决定系数高于其他地物类型样点。     

Forecasting China’s primary energy demand based on an improved AI model

An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.     

基于智能优化算法的河流水质模型参数的优化简

为探索河流水质模型参数新的求解方法,根据有限的实测数据,分别应用免疫进化优化算法和免疫进化优选的捕食搜索算法,对河流水质模型计算公式中的多参数进行优化。将优化得到的计算公式用于国内外若干河流的河段中DO浓度值的拟合,并与实测结果进行了比较。结果表明,将免疫进化优化算法或免疫进化优选的捕食搜索算法优化得到的水质模型参数精度不仅较高,而且相对稳定,从而为河流水质模型参数的优化提供了一种新方法。     

Post-flooding disaster crop diversity recovery: a case study of Cowpea in Mozambique

To restore food security to a traditional African cropping system following a sudden loss of seed, genetic diversity must be re-established. This study examines the extent to which Cowpea diversity was reinstated two years after a flood disaster in Gaza Province, Mozambique. The contribution that seed from various sources made to the recovery was assessed using semi-structured interviews and morphological and molecular data. Data suggest that diversity had recovered to some extent yet there was evidence of a narrowing of the genetic base, with fewer rare alleles and differences in the distribution of allele frequencies. Although the main channels for accessing seed after the flood were seed relief and markets, these sources contributed to minimal and different diversity. It appears that diversity was regained primarily through social networking in the form of loans or gifts of seed from friends and relatives. The results of the study are discussed in relation to seed relief approaches.     

湖域工业点源初始排污权配置定额模型与算法研究

针对湖域工业点源初始排污权定额配置问题,以“公平、效率、可行”为配置原则,通过引入权重系数的字典序最小化最大值方法,构建了基于多主体多种初始排污权多期配置的字典序定额模型,并给出求解算法。进而以江苏省太湖流域27类主要工业行业的初始氨氮排污权单期配置为例,从行业初始排污权短缺率与行业治污效益两方面,对比分析了基于等短缺率定额模型、等环境容量比例定额模型、字典序定额模型计算得到的3种定额配置方案效果。结果表明：相对于另外两种定额模型,字典序定额模型所得配置方案可实现平均行业短缺率最小(4613%),平均行业治污效益最大。研究也表明在“公平、效率、可行”配置原则下,字典序定额配置方法能够更为有效的促进企业治污技术提标升级和区域产业结构升级     

Landsat7 ETM+ SLC-OFF数据的修复及其在武汉东湖水质反演中的应用

自从2003年5月31日,从陆地卫星 7发回的ETM+图像数据就存在缺陷。这是由于增强专题制图仪的扫描线校正器发生故障引起的。这些称为SLC OF数据的图像有一些黑色的不存在任何数据的扫描行。丢失的数据约占全景数据的25％,使它们难以正常使用。但是,数据本身仍然保留了良好的辐射和几何性质,如加以妥善修复,仍可以在一些特殊领域中使用。首先介绍了如何使用自适应局部回归算法(ALR)恢复这些图像,然后使用修复后的图像反演武汉东湖的水质参数。结果表明：ALR算法可以对SLC OF图像进行较好的修复,而且利用修复后的图像和东湖的地面水质监测数据,通过多元逐步回归分析,可以建立很好的叶绿素a、透明度、总磷以及总氮等水质参数的经验遥感反演模型,模型的相关系数R²分别为0.86、0.75、0.73和0.71。反演得到的水质参数分布与实际情况符合。这些数据有许多优点,如空间分辨率高、存档数据非常丰富、可以从NASA的服务器免费下载等。在其他遥感数据不足或无法获得的情况下,这些数据经过适当的修复,可以作为补充或替代数据使用。〖     

采用支持向量机算法优化电化学处理油田污水的工艺参数

采用支持向量机(SVM)算法,将Box-Behnken设计法与支持向量回归算法(SVR)实验参数优化软件相结合,优化电化学去除油田污水COD的工艺参数。通过量子粒子群算法对SVM算法参数进行优化,从建立的回归模型中找到工艺参数的全局最佳点:电解时间60 min,电解电流3 A,三维电极填充料中石英砂质量695 g。模型得到的COD理论最优去除率为92.48%,验证实验得到的COD去除率为91.43%。     

River channel network design for drought and flood control: A case study of Xiaoqinghe River basin, Jinan City, China

Vulnerability of river channels to urbanization has been lessened by the extensive construction of artificial water control improvements. The challenge, however, is that traditional engineering practices on isolated parts of a river may disturb the hydrologic continuity and interrupt the natural state of ecosystems. Taking the Xiaoqinghe River basin as a whole, we developed a river channel network design to mitigate river risks while sustaining the river in a state as natural as possible. The river channel risk from drought during low-flow periods and flood during high-flow periods as well as the potential for water diversion were articulated in detail. On the basis of the above investigation, a network with “nodes” and “edges” could be designed to relieve drought hazard and flood risk respectively. Subsequently, the shortest path algorithm in the graph theory was applied to optimize the low-flow network by searching for the shortest path. The effectiveness assessment was then performed for the low-flow and high-flow networks, respectively. For the former, the network connectedness was evaluated by calculating the “gamma index of connectivity” and “alpha index of circuitry”; for the latter, the ratio of flood-control capacity to projected flood level was devised and calculated. Results show that the design boosted network connectivity and circuitry during the low-flow periods, indicating a more fluent flow pathway, and reduced the flood risk during the high-flow periods.     

Methodology of industry scale analysis under the constraint of regional resource capacity using HSY algorithm

This paper develops a methodology of proper scale analysis for regional industry development, which can be used in industry planning with the consideration of regional resource capacities. In the face of different data sources and even data scarcity, alternative methods based on linear programming and quadratic programming algorithms for calculating the resource intensity factors are designed. Based on the empirical study of industrialization, initial scenarios of industry development were set. Using HSY algorithm, sensitive industries that may cause exceeding regional resource capacity can be identified, and the risk of exceeding can be predicted and expressed in probability. Furthermore, a proper scale range can be designed for these sensitive industries according to resource capacity. Taking the case of Dalian city in China, this paper estimated the regional urban development plan, various resources capacities were studied, and land resources were estimated to be the most critical resource for the city. The land resource depletion intensities of different industries are calculated by quadratic programming algorithm. Under the constraint of 427.56 km² available industrial land resources, the electronic and power industries have the most significant impact on total land use, if the scale of power industry exceeds 1.27 billion USD, the probability of land resource capacity breakthrough will be 50%.     

培养藻类制取生物能源的研究

能源紧张和环境污染是全世界所面临的共同问题,用藻类替代传统作物生产生物能源是生物质能的重要发展方向之一。文章介绍了国内外对藻类培养条件、光生物反应器型式、藻类基因工程、藻细胞收集方法以及能源藻类生产系统的研究成果。研究认为,以藻类为原料生产生物燃料具有良好的发展前景,并指出了今后能源藻类生长的重点研究方向。