环境污染预测的人工神经网络模型

作者用基于Ｂ－Ｐ算法的人工神经网络，提出了建立环境污染物浓度预测的方法，并通过一个大气污染物ＳＯ２浓度的人工神经网络预测实例，证实了人工神经网络用于环境污染预测的可行性。     

Machine learning based mapping of the wave attenuation mechanism of an inclined thin plate

The surface piercing and floating coastal defense structures can be applied as an alternative to conventional rubble mound structures in some specific circumstances. A partially submerged steeply inclined thin plate (ITP) is also one of the candidate alternative structures. Knowledge about the wave attenuation mechanism of ITP improves the engineer's ability to make more cost-effective design. From this motivation, the mechanism of ITP was modeled by artificial neural networks based on experimental data. It is particularly aimed to reveal some fundamental facts about the attenuation mechanism of ITP, which could not be previously attained solely by the conventional analysis of the relevant experimental data. Surface plots, which depict the relationships between the governing design variables were generated from the developed model. In this way, the influence of each individual parameter on the performance was decomposed in a more precise way. Based on the data-driven model outputs, it was inferred that the most dominant design variable is the wavelength. The ITP performance is enhanced with increasing submergence degree, an effect that becomes even more pronounced in severe wave climate conditions. In such wave conditions, decreasing inclination angles also improve the functionality of the structure. However, the generated data-driven model indicated that the combination of the examined variables can have a more complicated effect on the ITP performance, especially for the longer wave lengths.     

Hyporheic and total transient storage in small,sand‐bed streams

Key processes in stream ecosystems are linked to hydraulic retention, which is the departure of stream flow from ideal ‘plug flow’, and reflects fluid movement through surface and hyporheic storage zones. Most existing information about hyporheic exchange is based on flume studies or field measurements in relatively steep streams with beds coarser than sand. Stream tracer studies may be used to quantify overall hydraulic retention, but disaggregation of surface and hyporheic retention remains difficult. A stream tracer approach was used to compute the rates at which stream water is exchanged with water in storage zones (total storage) in short reaches of two small, sand‐bed streams under free and obstructed flow conditions. Tracer curves were fit to the one‐dimensional transport with inflow storage model OTIS‐P. Networks of piezometers were used to measure specific discharge between the stream and the groundwater. In the sand‐bed streams studied, parameters describing total retention were in the upper 50% of data compiled from the literature, most of which represented streams with beds coarser than sand. However, hyporheic storage was an insignificant component of total hydraulic retention, representing only 0·01–0·49% of total exchange, and this fraction did not increase after installation of flow obstructions. Total retention did not vary systematically with bed material size, but increased 50–100% following flow obstruction. Removal of roughness elements, such as large wood and debris dams, is detrimental to processes dependent upon transient storage in small, sand‐bed streams. Copyright © 2007 John Wiley & Sons, Ltd.     

How does landscape structure influence catchment transit time across different geomorphic provinces?

Despite an increasing number of empirical investigations of catchment transit times (TTs), virtually all are based on individual catchments and there are few attempts to synthesize understanding across different geographical regions. Uniquely, this paper examines data from 55 catchments in five geomorphic provinces in northern temperate regions (Scotland, United States of America and Sweden). The objective is to understand how the role of catchment topography as a control on the TTs differs in contrasting geographical settings. Catchment inverse transit time proxies (ITTPs) were inferred by a simple metric of isotopic tracer damping, using the ratio of standard deviation of δ¹⁸O in streamwater to the standard deviation of δ¹⁸O in precipitation. Quantitative landscape analysis was undertaken to characterize the catchments according to hydrologically relevant topographic indices that could be readily determined from a digital terrain model (DTM). The nature of topographic controls on transit times varied markedly in different geomorphic regions. In steeper montane regions, there are stronger gravitational influences on hydraulic gradients and TTs tend to be lower in the steepest catchments. In provinces where terrain is more subdued, direct topographic control weakened; in particular, where flatter areas with less permeable soils give rise to overland flow and lower TTs. The steeper slopes within this flatter terrain appear to have a greater coverage of freely draining soils, which increase sub‐surface flow, therefore increasing TTs. Quantitative landscape analysis proved a useful tool for inter‐catchment comparison. However, the critical influence of sub‐surface permeability and connectivity may limit the transferability of predictive tools of hydrological function based on topographic parameters alone. Copyright © 2009 John Wiley & Sons, Ltd.     

云南天文台人造卫星观测与相关应用研究

回顾了过去２０年，特别是近１０年来云南天文台人造卫星的观测与应用情况。介绍在观测仪器的研制、改进和观测方法研究以及有关激光测月资料的归算与应用方面所作过的工作。根据既有的条件，就今后若干年内可能进行的几项工作提出了粗浅的看法。     

运用BP网络预测地下水位

人工神经网络是一门新兴的交叉学科，是处理非线性问题的有效方法。本文把影响地下水位的因素集作为网络的输入向量，地下水位本身作为网络的输出向量，构成了预测地下水位的ＢＰ网络模型。一个实例的应用实践表明，用ＢＰ网络预测地下水位较准确地反映了客观实际，比其它方法如回归模型具有较高的拟合精度和预测精度。     

流域年均含沙量的B-P网络预测模型及其效果检验

应用误差反向传播算法的人工神经网络，建立了流域年均含沙量的预测模型。该模型用于某流域年均含沙量预测的拟合率达９０％以上，预留检验预报的准确率为７５％。     

A combined theory for zonal harmonic and resonance perturbations of a near-circular orbit with applications to COSMOS 1603 (1984-106A)

Theory for the motion of a satellite in a near-circular orbit and perturbed by zonal and resonance terms in the Earth's gravity field is developed. Commensurability with respect to both primary and secondary terms is considered with the solution dependent on the depths of the resonances. The theory is applied to the motion of COSMOS 1603 (1984-106A) which approached 14 : 1 resonance in 1987. Values of lumped harmonics derived from least-squares analysis are in close agreement with previous studies of 1984-106A and global gravity field models. The theory is finally extended to incorporate the effects of air drag.     

A particle classification system for the PAMELA calorimeter

In this paper we propose a particle classification system for the imaging calorimeter of the PAMELA satellite-borne experiment. The system consist of three main processing phases. First, a segmentation of the whole signal detected by the calorimeter is performed to select a Region of Interest (RoI); this step allows to retain bounded and space invariant portions of data for the following analysis. In the next step, the RoIs are characterized by means of nine discriminating variables, which measure event properties useful for the classification. The third phase (the classification step) relies on two different supervised algorithms, Artificial Neural Networks and Support Vector Machines. The system was tested with a large simulated data set, composed by 40 GeV/c momentum electrons and protons. Moreover, in order to study the classification power of the calorimeter for experimental data, we have also used biased simulated data. A proton contamination in the range 10⁻⁴–10⁻⁵ at an electron efficiency greater than 95% was obtained. The results are adequate for the PAMELA imaging calorimeter and show that the approach to the classification based on soft computing techniques is complementary to the traditional analysis performed using optimized cascade cuts on different variables.