一种基于BP算法学习的小波神经网络

为发展 Szu的基于信号表示的小波神经网络 ,提出一种多输入多输出的小波网络模型 ,网络隐层采用框架小波函数、输出层采用 Sigmoid激励函数 ,并选用“熵误差函数”以加速网络的学习速度。奇偶判别和混沌时间序列预测例子的实验结果表明了它具有良好的函数逼近能力和推广能力 ,收敛速度和均方误差均优于相同结构的多层感知器模型。     

黄海、渤海底层温度数值预报方法的研究

根据文献［ｌ］建立的底层温度（ＴＨ）与其水柱垂向平均温度（）的经验关系，结合流体动力学方程和（垂向平均）热传导方程，发展了以水气温差和风速为已知量的底层温度二维数值预报模式。该模式避开了海面热量和动量输入在垂直水柱中分配的复杂物理过程而直接报出底层水温场，具有较好的实用性；此外，从试报结果看，效果令人满意。     

连云港近岸海域物理自净能力研究及水质预测——Ⅲ.西大堤建成后对物质输运的影响

在连云港近岸海域计算潮流场基础上建立拉格朗日余流模型,并对连云港市两大堤建成前后的拉格朗日余流变化进行了分析,且选择有代表性的排污口进行了数值跟踪。     

松辽盆地西部张裂缝预测的应力场方法

以松辽盆地地质资料为基础，介绍了应力场和张裂缝预测的计算方法。通过了各种岩性的张破裂概率隶属函数，预测松辽盆地酉部张裂缝区的分布。据此，为今后的油气勘探提出了几点认识和建议。     

一个具有下垫面温度耦合的大气环流的统计—动力模式

本文从动力学定律出发,推导了一个线性的、具有下垫面温度耦合的大气环流的统计—动力模式,并用该模式对500hPa高度场及1000hPa温度场作1～30天的平均预报试验。模式的预报结果大大优于惯性预报,但耦合与不耦合的结果差别不大。     

Pressure prediction in the Bullwinkle Basin through petrophysics and flow modeling (Green Canyon 65, Gulf of Mexico)

Reservoir pressures within the Bullwinkle minibasin (Green Canyon 65, Gulf of Mexico continental slope) increase at a hydrostatic gradient whereas pressures predicted from porosity within mudstones bounding these reservoirs increase at a lithostatic gradient: they are equal at a depth 1/3 of the way down from the crest of the structure. Two- and three-dimensional steady-state flow models demonstrate that bowl-shaped structures will have lower pressures than equivalent two-dimensional structures and that if a low permeability salt layer underlies the basin, the pressure is reduced. We conclude that at Bullwinkle, pressure is reduced due to an underlying salt body and the bowl-shape of the basin. A geometric approach to predict sandstone pressure is to assume that the reservoir pressure equals the area-weighted average of the mudstone pressure. When the mudstone pressure gradient is constant, as at Bullwinkle, the reservoir pressure equals the mudstone pressure at the average depth (centroid) of the reservoir.     

Hammerstein型非线性积分方程解的存在性

该文采用化为积分方程组的方法 ,利用锥上不动点指数计算 ,在不要求非线性项 f (x,u)非负的情况下 ,证明 Hammerstein型非线性积分方程 φ(x) =∫Gκ(x,y) f (y,φ(y) ) dy非平凡解和多解存在性的一些新的结果。此结果可用来证明非线性常微分方程两点边值问题解的存在性。     

混合型单调算子对的不动点研究及其在微分方程组的应用

提出了混合型单调算子对的概念,并给出了其不动点的存在唯一性;研究了它在微分方程组的具体应用.     

诊断台风异常路径的三层权重控制点方案

本方案采用850、700、500hPa三个层次的环境平均流场作控制点法。综合考虑这些层次上的引导气流在不同时、空域中的相对重要性。试验结果表明,其效果比单一取某层作引导为佳。且对用来预测台风的未来24小时路径是否异常具有一定的参考价值。     

Filters for linear sea-wave prediction

Deterministic sea-wave prediction (DSWP) models are appearing in the literature designed for quiescent interval prediction in marine applications dominated by large swell seas. The approach has focused upon spectral methods which are straightforward and intuitively attractive. However, such methods have the disadvantage that while the sea is aperiodic in nature, the standard discrete spectral processing techniques force an absolutely periodic structure onto the resulting sea surface prediction models. As it is the shape of the sea surface that is important in such applications, particularly near the end of the domain which is important, the standard windowing techniques used in signal processing work to reduce leakage artifacts cannot be employed. This has necessitated the use of end matching methods that can be both inconvenient and may reduce the fraction of the time for which legitimate predictions are available. As a result, an investigation has been undertaken of the use of finite impulse response prediction filters to provide the necessary dispersive phase shifting required in DSWP systems. The present work examines the theoretical basis for such filters and explores their properties together with their application to both long and short crested swell seas. It is shown that wide band forms of such filters are only convergent in the sense of distributions having both infinite duration impulse responses and asymptotically divergent first derivatives. However, appropriate band limitation can produce useful finite impulse responses allowing implementation via standard discrete convolution methods. It is demonstrated that despite the prediction filters having a non-causal impulse response such filters can be used in practice due to a combination of the asymmetric nature of the impulse response and the fundamental nature of the prediction process. The findings are confirmed against actual sea-wave data.