基于相位差测深声呐(PDBS)技术的莱州湾人工鱼礁探测

相位差测深声呐(Phase Differencing Bathymetric Sonar,PDBS),也被称作干涉式声呐(Interferometric Sonar),可以同步采集水深点云数据和双频侧扫声呐图像,完全适用于大范围的近海人工鱼礁探测。本文采用基于PDBS原理的Edge Tech 6205地形地貌一体化测量设备对莱州湾某海域海洋牧场投礁区进行全覆盖探测,获取了高精度水深数据以及双频侧扫声呐图像。对水深数据进行地形特征变量计算,精细刻画了研究区的微地形地貌特征,并结合侧扫声呐图像通过多数据融合实现了对鱼礁边界的精准识别。在此基础上利用地理信息系统中的空间分析方法对人工鱼礁的水下物理参数进行计算和统计,并探讨了研究区地形地貌的成因及其演化模式,最后论证了基于PDBS的近海人工鱼礁探测技术具有高效率、低成本、高精度等诸多优势。研究结果表明,研究区水深介于4.1~7.3 m,鱼礁分布区有较大的海底起伏且在礁体周围存在明显的沉降和冲刷现象;鱼礁总占地面积约占研究区的14.04%,总空方量共计2 528.22 m³,鱼礁高度介于1.26~3.63 m且呈正态分布。本研究为近海人工鱼礁探测提供了数据和技术支撑,具有较强的实践意义。     

加速仪数据在CHAMP卫星精密定轨中的贡献

通过用几个实例计算，评估了CHAMP卫星加速仪数据对SLR数据定轨精度的贡献．结果显示用加速仪数据代替非保守力对CHAMP卫星进行精密定轨时，其SLR的残差从原来的16．5cm减少到2．7cm，与精密轨道相比，卫星位置误差由18．9cm减少到6．2cm(一天资料)．     

新发现的江河寄生性等足类——细角鳃虫的人工感染试验

珠江水系贺江段近年出现严重危害网箱养殖和江河鱼类资源的大型寄生虫病害．初步鉴定该虫隶属于甲壳纲．等足目．鳃虫科．细角鳃虫属．是国内新发现的淡水鱼类寄生虫。用该虫对草鱼、银鲫、麦鲮进行人工感染．结果表明：该虫具有很强的寄生能力．累积感染率为76．2％～100．0％；对寄生部位具有一定的选择性，以寄生在鳃部的比例（55．6％～72．0％）最大．胸鳍（11．7％～28．8％）次之；对试验鱼有较强的致死性；该虫吸血后体长（L）增长较大．体宽（W）基本不变；从寄主体上主动脱落的虫体，其L／W的增长率（16．32％～18．00％）较大，而一直寄生在寄主身上的虫体．其L／W的增长率则因各自摄食量的不同而存在较大的差异。     

区域开发环境评价中人工智能扩展GIS在累积过程分析中的应用

采用人工智能方法，扩展GIS(地理信息系统)的功能，建立能对累积影响途径全部推理过程做出必要解释的累积效应专家系统。充分发挥其推理及解释的功能，克服GIS在累积效应过程分析和推理中的不足，解决了在区域开发环境影响评价中。用GIS对区域影响环境评价的累积效应影响的时空分析，虽有一定的优势，但不能对累积效应的过程进行分析，即不能确定和分析累积效应的因果关系，不能区分累积方式的难题。研究结果表明，该系统能为区域开发环境影响评价提供决策支撑。     

The strategy of building a flood forecast model by neuro‐fuzzy network

A methodology is proposed for constructing a flood forecast model using the adaptive neuro‐fuzzy inference system (ANFIS). This is based on a self‐organizing rule‐base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall‐runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self‐constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back‐propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model. Copyright © 2005 John Wiley & Sons, Ltd.     

Long Time Stability for the Main Problem of Artificial Satellites

We investigate the significance of long time stabilty predictions in the light of Nekhoroshev's theory by studying the orbits of artificial satellites. As a simplified model problem we consider the so-called J₂problem for an earth's satellite, neglecting luni-solar perturbations and nonconservative effects. We consider a wide range of orbits, excluding those which are too close to the critical inclination. Most of the orbits turn out to be stable for times larger than the estimated age of the solar system, thus proving that, as far as dissipation can be neglected, stability in Nekhoroshev's sense may be effective for physically realistic systems. This revised version was published online in July 2006 with corrections to the Cover Date.     

Counterpropagation fuzzy–neural network for streamflow reconstruction

This study combines neural networks and fuzzy arithmetic to present a counterpropagation fuzzy–neural network (CFNN) for streamflow reconstruction. The CFNN has a rule‐based control, a modified self‐organizing counterpropagation network, and a fuzzy control predictor. It can generate rules automatically by increasing the training data to improve the accuracy of streamflow reconstruction. The CFNN establishes the input and output relationship of a watershed without set‐up parameters. The parameters are estimated systematically by the approach converging to an optimal solution. One sequence of data generated by the Monte Carlo method is used to demonstrate the accuracy of the CFNN. The streamflow data of the Da‐chia River, in central Taiwan, is also used to evaluate the performances of the CFNN. The results indicate the reliability and accuracy of the CFNN for streamflow reconstruction. Copyright © 2001 John Wiley & Sons, Ltd.     

A second order analytical atmospheric drag theory based on the TD88 thermospheric density model

A second order atmospheric drag theory based on the usage of TD88 model is constructed. It is developed to the second order in terms of TD88 small parameters K _n,j . The short periodic perturbations, of all orbital elements, are evaluated. The secular perturbations of the semi-major axis and of the eccentricity are obtained. The theory is applied to determine the lifetime of the satellites ROHINI (1980 62A), and to predict the lifetime of the microsatellite MIMOSA. The secular perturbations of the nodal longitude and of the argument of perigee due to the Earth’s gravity are taken into account up to the second order in Earth’s oblateness.     

制约卫星轨道寿命的另一种机制(续)

对于制约低轨人造地球卫星轨道寿命的耗散机制，人们已有足够的重视，但在深空探测中，另一种制约低轨卫星轨道寿命的引力机制同样应予重视，前文讨论了高轨卫星的情况，在第三体引力作用下，有可能导致卫星轨道偏心率产生变幅较大的长周期变化。特别是极轨卫星，其轨道偏心率在一定的时间内可增大到使其近星距rp=a(1-e)≈Re（Re是中心天体的赤道半径），从而落到中心天体上，结束其轨道寿命，目前对低轨卫星作了详尽的理论分析，研究表明，与高轨卫星有类似结果，但其力学机制却不相同，低轨卫星的轨道寿命与第三体引力无关。它取决于中心天体非球形引力位中的扁率项（即J2项）与其他带谐项之间的相对大小，这不仅是一个纯理论结果，也有实际背景，在太阳系中慢自传天体（月球和金星等）的低轨卫星就存在这一问题，还给出了有关判据，并以计算实例作了验证。     

基于智能体和人工神经网络的元胞自动机建模及城市扩展模拟

城市扩展模拟可为城市可持续发展与国土空间规划提供参考。智能体模型(ABM)与元胞自动机(CA)结合可兼顾城市空间增长的自组织性和不同决策主体的决策过程,人工神经网络(ANN)可描述智能体与城市扩展之间复杂的非线性关系。该文基于ANN-ABM-CA耦合模型,在构建CA转换规则时基于ABM刻画人类决策行为的影响,并采用ANN挖掘不同类型的智能体在城市扩展过程中的偏好差异,同时考虑宏观和微观层面的智能体决策行为,结合城市扩展的10个驱动因素,模拟武汉市主城区2005-2015年的扩展情况,结果表明:1)相比传统的ANN-CA模型,ANN-ABM-CA模型模拟性能更优,从宏观与微观相结合的角度更好地解释了城市扩展的驱动机制,OA值为97.46%,Kappa系数为0.9176,FoM值为0.4375,结果可靠且合理;2)不同收入层级的居民智能体对城市扩展的决策偏好不同;3)武汉主城区城市扩展模式主要为边缘型扩展,洪山区西南部有少部分填充型扩展、东南部出现飞地型扩展,与实际扩展情况相符。