南四湖人工湿地建设示范工程

人工湿地具有高效率、低投资、低运转费、低维持技术、处理量灵活、低能耗、处理效果好等优点。济宁市为了更好地治理南四湖水污染,在流入南四湖境内的重点河流开展了人工湿地建设工程。南四湖人工湿地的建设产生了极大的社会、经济和生态效益。总结了南四湖人工湿地建设措施,提出了相关的建议。     

Estimation of soil compaction parameters by using statistical analyses and artificial neural networks

This study presents the application of different methods (simple–multiple analysis and artificial neural networks) for the estimation of the compaction parameters (maximum dry unit weight and optimum moisture content) from classification properties of the soils. Compaction parameters can only be defined experimentally by Proctor tests. The data collected from the dams in some areas of Nigde (Turkey) were used for the estimation of soil compaction parameters. Regression analysis and artificial neural network estimation indicated strong correlations (r ² = 0.70–0.95) between the compaction parameters and soil classification properties. It has been shown that the correlation equations obtained as a result of regression analyses are in satisfactory agreement with the test results. It is recommended that the proposed correlations will be useful for a preliminary design of a project where there is a financial limitation and limited time.     

Gypsum karst intensification as a consequence of sulphur mining activity (Jaziv field,Western Ukraine)

The scope of this study is to evaluate the parameters of the gypsum–anhydrite strata karstification under the influence of the quarry exploitation of Jaziv sulphur field (West Ukraine) accompanying by drainage. The quarry drainage provoked the enormous depression cone forming with 100 km² in area and the corresponding intensification of chemical denudation of the gypsum–anhydrite strata. The gypsum karstification rate for the 29-year period of the quarry drainage was 0.06% with the dissolved rock volume of 1,328,507 m³ that is about 80 times higher than in natural conditions. For the drainage period (29 years) the karst denudation rate was 17,952 m³/km² against the natural background of 231.3 m³/km². The absolute value of artificial denudation for the studied massif area is 1.79 cm for 29 years or 0.062 mm/year while the denudation rate under natural conditions would be 0.231 cm for 29 years or 0.0008 mm/year. The forecasted volumes of the surface-evident collapses are evaluated using the relationship between the calculated amount of dissolved sulphate rocks and volumes of the current surface-evident collapses. According to this evaluation, the current collapses correspond to about 34% only from the dissolved rocks volume calculated for the drainage period.     

Application of neural network and MODIS 250m imagery for estimating suspended sediments concentration in Hangzhou Bay,China

Suspended sediments concentration (SSC) in surface water derived from bottom sediment resuspension or discharge of sediment-laden rivers is an important indication of coastal water quality and changes rapidly in high-energy coastal area. Since artificial neural networks (ANN) had been proven successful in modeling a variety of geophysical transfer functions, an ANN model to simulate the relationship between surface water SSC and satellite-received radiances was employed. In situ SSC measurements from the Hangzhou Bay and the Moderate-resolution Imaging Spectroradiometer (MODIS) 250 m daily products were adopted in this study. Significant correlations were observed between in situ measurements and band 1–2 reflectance values of MODIS images, respectively. Results indicated that application of ANN model with one hidden layer appeared to yield superior simulation performance (r ² = 0.98; n = 25) compared with regression analysis method. The RMSE for the ANN model was less than 10%, whereas the RMSE for the regression analysis was more than 25%. Results also showed that different tidal situations affect the model simulation results to some extent. The SSC of surface water in Hangzhou Bay is high and changes rapidly due to tidal flood and ebb during a tidal cycle. The combined utilization of Terra and Aqua MODIS data can capture the tidal cycle induced dynamic of surface water SSC. This study demonstrated that MODIS 250 m daily products and ANN model are useful for monitoring surface SSC dynamic within high-energy coastal water environments.     

夏季对流云人工增雨效果评价方法初探

由于对流云尺度小、生消快,降水时空分布不均匀等特点,对其进行人工增雨效果评价是十分困难的事.本文利用2003年在"江淮地区对流云人工增雨外场试验"试验区获取的对流云人工增雨监测资料,采用成对对流云试验方案,开展对对流云人工增雨效果进行评估.通过对催化云催化前后雷达特征量和地面雨量变化分析,以及催化云与非催化云自身对比分析和双比分析,初步得出:人工催化后10～20 min增雨效果不明显,人工催化30 min后才能产生明显的增雨效果,其效果在100%以上.     

Finite element modeling of wave propagation problems in multilayered soils resting on a rigid base

A new finite element scheme is proposed, in this paper, for solving two-dimensional wave propagation problems in multilayered soils resting on a rigid base. The multilayered soils are treated as multiple horizontal layers of lateral infinite extension in geometry. Since these horizontal layers can be truncated by two artificially truncated vertical boundaries, two high-order artificial boundary conditions are applied for propagating the incoming waves from the interior domain into the far field of the system. Both the semi-analytical method and the truncated boundary migration procedure are used to derive the high-order artificial boundary conditions, which are comprised of a physically meaningful dashpot and a generalized energy absorber. The main advantage of using the proposed finite element scheme is that the derived artificial boundary condition can be straightforwardly implemented in the finite element analysis, without violating the band/sparse structure of the conventional finite element equation. The related numerical examples have demonstrated that the proposed finite element scheme is of high accuracy in dealing with wave propagation problems in multiple horizontal layers.     

基于不同学科解决粗差探测问题的方法研究

通过对已有粗差探测成果的研究,本文按照基于的学科不同将其大致分为4类:数理统计粗差探测方法,基于多元统计分析粗差探测方法,线性代数粗差探测方法,人工智能粗差探测方法。然后从这4个方面辐射出已有的关于粗差发现、定位、定值等相关方法的研究,并且针对国内学者对用人工智能方法实现粗差探测未进行成熟研究的现状,提出可行策略并进行实现从而为人工智能和测量数据处理2个学科的结合开拓新的研究方向。     

AFSA-BP神经网络在大坝变形预测中的应用

经典BP神经网络的初始权值和阈值随机给定,使得训练速度慢、网络易于陷入局部极值。引入具有强大全局搜索能力的人工鱼群算法(AFSA)优化BP网络的权值和阈值,建立了基于AFSA-BP神经网络的预测模型,并对大坝的实测资料进行了实证分析。与经典BP神经网络预测模型的预测结果比较表明:AFSA-BP神经网络模型不仅训练速度快,而且预测精度明显提高,是一种较好的大坝变形预测模型。     

ID3决策树推理模型及其在道路网选取中的应用

介绍了自动制图综合中知识推理的研究现状及存在的问题,指出了借鉴人工智能优秀技术成果提升自动综合智能化水平是解决当前问题的重要途径之一。对ID3智能算法的基本原理进行了详细介绍,提出基于ID3决策树的知识推理模型。将该模型引入到道路网智能化选取当中。对该模型应用到道路网自动选取的合理性进行了论述,并进行了实验验证。在对实验结果进行详细分析的基础上,探讨了该算法应用于道路网选取的优势和不足,指出了进一步研究的方向。     

Sediment flux sensitivity to climate change: A case study in the Longchuanjiang catchment of the upper Yangtze River, China

Climate change may affect the sediment generation and transportation processes and the consequent sediment flux in a river. The sensitivity of suspended sediment flux to climate change in the Longchuanjiang catchment is investigated with Artificial Neural Networks (ANNs). ANNs were calibrated and validated using sediment flux data from 1960 to 1990 during which the influence from human activities was relatively stable. The established ANN is used to predict the responses of sediment flux to 25 hypothetical climate scenarios, which were generated by adjusting the baseline temperature up to − 1, 1, 2 and 3 °C and by scaling the baseline precipitation by +/− 10% and +/− 20%. The results indicated when temperature remains unchanged, an increase in rainfall will lead to a rise in sediment flux; when rainfall level remains unchanged, an increase in temperature is likely to result in a decrease in sediment flux. Same percentage of changes in rainfall and temperature are likely to trigger higher responses in wetter months than in drier months. However, it is the combination of the change in temperature and rainfall that determines the change of sediment flux in a river. Higher sediment flux is expected to appear under wetter and warmer climate, when higher transport capacity is accompanied by higher erosion rate.