栉江珧人工育苗试验

报道了栉江珧（Pinna（Alrina）peclinala Linncaus）人工育苗的试验结果。结果表明采用变温刺激法、阴干流水刺激法及阴干流水升温刺激法催产亲贝效果较好。在水温20．6～24．7℃,密度1．018～1．023水体申经50d培育后幼虫附着变态成稚贝,变态率10％-20％,10d后最大幼贝长达6mm。     

水雷目标识别中的数据融合技术

主动声纳发射声信号“照射”被识别目标,并从目标产生的回波中提取出目标的特征信息,结合可能得到的先验知识,对目标的类别作出判断。论文偿试把现代信号处理技术与信息融合技术相结合,应用到具体的水雷目标识别领域,以提高水雷回波识别系统的准确性和可靠性。     

Estimating anisotropic aquifer parameters by artificial neural networks

In recent years, many approaches have been developed using the artificial neural networks (ANN) model incorporated with the Theis analytical solution to estimate the effective hydrological parameters for homogeneous and isotropic porous media, such as the Lin and Chen approach (ANN approach) and the principal component analysis (PCA)‐ANN approach. The above methods assume a full superimposition of the type curve and the observed drawdown and try to use the first time‐drawdown data as a match point to make a fine approximation of the effective parameters. However, using first time‐drawdown data or early time‐drawdown data does not always allow for an accurate estimation of the hydrological parameters, especially for heterogeneous and anisotropic aquifers. Therefore, this article corrects the concept of the superimposed plot by modifying the ANN approach and the PCA‐ANN approach, as well as incorporating the Papadopoulos analytical solution, to estimate the transmissivities and storage coefficient for anisotropic, homogeneous aquifers. The ANN model is trained with 4000 training sets of the well function, and tested with 1000 sets and 300 sets of synthetic time‐drawdown generated from the homogeneous and heterogeneous parameters, respectively. In situ observation data from the time‐drawdown at station Shi‐Chou on the Choushui River alluvial fan, Taiwan, is further adopted to test the applicability and reliability of the proposed methods, as well as provide a basis for comparison with the Straight‐line method and the Type‐curve method. Results suggest that both of the modified methods perform better than the original ones, and using late time‐drawdown to optimize the effective parameters is shown to be better than using early time‐drawdown. Additionally, results indicate that the modified ANN approach is better than the modified PCA‐ANN approach in terms of precision, while the efficiency of the modified PCA‐ANN approach is approximately three times better than that of the modified ANN approach. Copyright © 2010 John Wiley & Sons, Ltd.     

植被叶面积指数估算的红边指数建模分析

针对在路域环境监测中,如何精确估算叶面积指数问题,该文提出以长韶娄高速路域为研究区,筛选出4种常用植被指数和4种红边指数两类指数,分别构建了经验模型和机器学习的反演模型,利用Sentinel-2影像数据和同步的LAI-2000地面实测数据完成路域植被叶面积指数反演。结果表明,红边波段参与运算的植被指数与植被叶面积指数敏感性是显著相关,红边指数在反演精度上更优。由此可知,相较于常见植被指数,红边指数增强了其与叶面积指数的敏感性,提高了叶面积指数估算模型精度。     

建设数字孪生城市的逻辑与创新思考

介绍了数字孪生城市的提出背景以及基本概念,分析了数字孪生城市与智慧城市之间的关系,并介绍了构建数字孪生城市的主要支撑技术,最后总结了数字孪生城市的应用现状及发展趋势。作者认为,数字孪生技术要在智慧城市建设中得以更广泛的应用还将面临数据、基础知识库、系统融合以及人才问题等方面的挑战,并从宏观与微观层面提出解决这些问题的制度路径和技术路径。     

一种基于空间分析服务链组合的自然资源保护红线审计模型方法

区别于传统的审计方法,针对领导干部自然资源资产离任审计,提出一种空间分析服务链组合的自然资源保护红线审计空间分析建模方法,实现了自然资源保护红线审计的地理处理分析服务链模型,并将其应用到云南省领导干部自然资源资产离任审计工作中。实验表明,该模型具有可行性能够辅助审计部门工作人员快速发现疑点线索,简化用户操作,提高审计效率。     

控制海水入侵的地下水多目标模拟优化管理模型

为实现滨海含水层地下水开采-回灌方案优化、控制海水入侵面积和降低海水入侵损失等多重管理目标,建立了海水入侵条件下地下水多目标模拟优化管理模型SWT-NPTSGA。模拟模型采用基于变密度流的数值模拟程序SEAWAT来模拟海水入侵过程。优化模型采用小生境Pareto禁忌遗传混合算法NPTSGA来求解,该算法在保证多目标权衡解的收敛性和计算效率的前提下,能维护整个进化群体的全局多样性。将SWT-NPTSGA程序应用于一个理想滨海含水层地下水开采方案和人工回灌控制海水入侵的优化设计中,结果表明该管理模型能够同时处理最大化总抽水流量、最小化人工回灌总量和最小化海水入侵范围等3个目标函数之间的权衡关系。通过采用人工回灌海水入侵区的减灾策略,既能增加滨海地区的供水量,又可减少海水入侵的范围,由此进一步验证了模型的有效性和可靠性。     

长潭岗水库汛期日平均进库流量预报模型设计

摘要：为了指导长潭岗水库安全、高效运行,保护下游人民生命财产,本文对长潭岗水库的日平均进库流量进行了建模。本文使用水库上游集雨面积的降水量、蒸发量资料以及水库的日平均进库流量数据建立人工神经网络模型,通过对模型隐含层和输出层的层函数进行不同的组合,得到了4种复杂程度和表达能力逐渐增加的模型。各模型训练结果较好,验证结果均能在0.05的显著性水平上通过检验,其中模型2111（第一隐含层为一元二次线性函数其余层次均为一元一次线性函数）的效果最好,层函数的复杂程度对峰值输出的准确度有一定的正面的贡献。该模型能够满足气象局的专业气象服务需求。     

Evaluation of Linear and Non-Linear Downscaling Methods in Terms of Daily Variability and Climate Indices: Surface Temperature in Southern Ontario and Quebec,Canada

We downscaled atmospheric reanalysis data using linear regression and Bayesian neural network (BNN) ensembles to obtain daily maximum and minimum temperatures at ten weather stations in southern Quebec and Ontario, Canada. Performance of the linear and non-linear downscaling models was evaluated using four different sets of predictors, not only in terms of their ability to reproduce the magnitude of day-to-day variability (i.e., “weather,” mean absolute error between the daily values of the predictand(s) and the downscaled data) but also in terms of their ability to reproduce longer time scale variability (i.e., “climate,” indices of agreement between the predictand's observed annual climate indices and the corresponding downscaled values). The climate indices used were the 90th percentile of the daily maximum temperature, 10th percentile of the daily minimum temperature, number of frost days, heat wave duration, growing season length, and intra-annual temperature range.

Our results show that the non-linear models usually outperform their linear counterparts in the magnitude of daily variability and, to a greater extent, in annual climate variability. In particular, the best model simulating weather and climate was a BNN ensemble using stepwise selection from 20 reanalysis predictors, followed by a BNN ensemble using the three leading principal components from the aforementioned predictors. Finally, we showed that, on average, the first three indices presented higher skills than the growing season length, number of frost days, and the heat wave duration.     

西沙赵述岛海域珊瑚礁生态修复效果的初步评估

珊瑚恢复是一个协助退化、受损的珊瑚礁生态系统恢复的过程.近10 a来,西沙珊瑚礁生态系统不断退化,至2009年珊瑚覆盖率已下降至不足10%.针对西沙群岛珊瑚礁生态系统的退化状况,2011年12月于西沙赵述岛海域投放人工礁基并开展珊瑚移植实验,比较了人工修复区和自然恢复区1a后的修复效果.结果显示,投放礁基且进行珊瑚移植的区域,移植珊瑚的存活率不到10%;投放礁基但未进行珊瑚移植的区域,珊瑚补充量高达6~7 ind/m2;自然恢复区其珊瑚覆盖率提高了19.4%.依据珊瑚礁生态修复效果评估方法,人工修复且进行移植珊瑚的区域的生物修复权重值为27.5,人工修复但未移植珊瑚区及自然恢复区的生物修复权重值为39.3,珊瑚修复生物指标为亚健康.我们的结果表明,在健康、有良好珊瑚幼虫补充的珊瑚礁生态系统中,珊瑚礁群落可以自行恢复,其恢复只是一个时间的问题;而在缺少珊瑚幼虫附着基底的区域,通过人为增加一些附着基底,可加速其恢复进程.