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。     

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%.     

近10 a武汉市城市热岛效应演变及其#br# 与土地利用变化的关系

城市化进程的加快,农村人口大量涌入城市,城市布局及局部气候改变等因素使得城市热岛效应问题日益突出,已成为当前城市环境研究热点之一。以武汉市为例,应用遥感技术与地理信息系统技术,选取2004~2015年5个时相Landsat系列影像数据,利用单窗算法反演地表温度,并以此为基础进行热岛强度分级,获取了近10 a武汉市城市热岛效应变化结果,并分析了武汉市11个辖区城市热岛效应动态变化特征及热岛效应与土地利用变化的关系。研究结果表明：（1）自2007年后,武汉市老城区热岛面积持续减少,而新城区热岛面积则持续增加,呈现出以老城区为中心向新城区扩张的趋势,至2015年,新老城区热岛面积仅相差20.74 km2;（2）东西湖区、蔡甸区、江夏区与洪山区是近些年城市热岛面积增长较为显著的辖区,其中江夏区的热岛面积年际变化最大,最高值达95.42 km2;（3）城市热岛效应与土地利用类型的面积年际平均值拟合关系显示,2004~2015年,城市热岛效应与建筑用地的R2值最大,为0.681 2,建筑用地面积的增加是城市热岛强度面积扩张的重要影响因素。     

响应面法和神经网络优化Acinetobacter sp. DNS32发酵基质

为了提高阿特拉津降解菌Acinetobacter sp.DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分(玉米粉、豆饼粉、K2HPO4)进行优化研究。响应曲面法确定3种成分的含量为玉米粉39.494 g/L,豆饼粉25.638 g/L和K2HPO43.265 g/L时,预测发酵活菌最大生物量为7.079×108CFU/mL,实测量为7.194×108CFU/mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L时,预测最大值为7.199×108CFU/mL,实测量为7.244×108CFU/mL;最终确定培养基配方:玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L,CaCO3为3.000 g/L,MgSO4.7H2O和NaCl均为0.200 g/L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36.6%。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

基于人工蜂群算法与BP神经网络的水质评价模型

针对BP网络水质评价模型的不足,引入人工蜂群(ABC)算法,将求解BP神经网络各层权值、阀值的过程转化为蜜蜂寻找最佳蜜源的过程,提出了一种新的结合人工蜂群算法的BP网络水质评价方法(ABC-BP)。并以2000—2006年渭河监测断面的10组实测数据作为测试样本对其水质进行了评价,实验结果表明该方法得到的水质评价结果准确,并具有很强的稳定性和鲁棒性。