基于小波分析的功能磁共振图像的去噪预处理

对基于小波分析的fMRI去噪作了较具体的论述，并在Donoho和Johnstone的Hard函数及Soft函数基础上提出了更合适的Hard—Soft函数．从结果分析看，Hard—Soft函数比Soft函数在保留图像细节上占优，而去噪性能比Hard函数要好．因而能够在图像去噪和保护信息上达到更好的均衡，克服了Hard函数和Soft函数的两个极端状况．     

有攻角高超声速穿甲弹气动烧蚀的研究

该文采用“轴对称比拟”的研究方法，运用相似性理论，基于小横向流假设，研究了有攻角高超声速穿甲弹的气动烧蚀。通过耦合计算物面流线几何形状、比例因子、气动加热烧蚀模型，结果表明弹丸头部出现了严重的不对称变形，这将引起弹丸气动力的较大变化，可能导致弹丸飞行稳定性和密集度的降低，对今后进行高超声速穿甲弹的设计有重要的促进作用。     

双向Elman神经网络在卫星电池阵功率预测中的应用研究

针对神经网络预测电池阵功率存在的模型阶数难以确定及预测精度低下的问题，提出一种基于改进的Elman神经网络的双向预测模型。该模型利用关联层动态神经元的反馈连接，将未来预测网络和过去预测网络的信息进行融合。使网络对时间序列特征信息的记忆得到加强，从而提高预测精度。用该文提出的双向预测模型对电池阵功率进行预测，输入层仅需一个节点，不需事先对模型进行定阶。仿真预测表明，预测精度比单向模型明显提高，且网络具有较好的泛化能力。     

基于支持向量机的短期GDP预测模型与应用研究

支持向量机是最近几年国际上模式识别研究的热点,具有全局最优和良好的泛化能力.本文在理论分析江门市GDP预测指标体系的前提下,研究了基于SVM的预测方法,并运用实际数据进行建模和预测,获得了比较准确的预测结果.     

基于灰色理论的煤炭需求预测模型研究

研究了GM(1，1)模型在我国煤炭需求预测中的应用，并以实际数据为基础，建立了我国煤炭需求量的数列预测模型。经检验，模型可靠，可用于对我国煤炭需求总量的预测。简要分析了根据实际变化不断改进模型的必要性。     

宾馆燃油锅炉的噪声控制

对一种新型燃油锅炉的噪声源进行了分析，采用燃油锅炉噪声综合控制技术，如消声、吸声、隔声以及通风散热等措施使其达到环保要求，此技术具有推广价值，特别是各种噪声控制方法以及设计参数的选择，对于类似的噪声治理的课题具有借鉴意义。     

人工神经网络构造经济预测模型方法的探讨

探讨利用人工神经网络建立经济模型的一般原理和方法,并通过构造一个宏观经济模型的实例加以说明.与传统的回归分析方法相比,人工神经网络具有良好的适应性和分析预测能力.     

基于BP神经网络预报的动态矩阵预测控制

提出了一种基于BP神经网络预报的动态矩阵预测控制新算法 ,在该算法中 ,先用BP神经网络辨识对象模型 ,同时预测对象的未来输出 ,然后用动态矩阵控制算法进行滚动优化和反馈校正。该方法解决了非线性、时变对象难以建模及控制的问题 ,仿真结果验证了这一新型算法的可行性     

A multi-layer zone model for predicting temperature distribution in a fire room

Modelingoffireinacompartmentcanbeachievedeitherusingazonemodelingmethodoracomputationalfluiddynamics (CFD )modelingmethod .Themostcommonzonemodelisthetwo zonemodel.Themaincharacterofthismodelisthatitdividestheroom (s)intoahot ,upperlayerandacooler,lowerlayer ,andthatthephysicalpropertiesofeachlayer ,suchasitsgastemperatureandspeciesconcentrationsarealluniform .Somemodelsofthistypehavebeendeveloped[1～3] ,andacomprehensivereviewoftheexistingtwo zonefiremodelscanbefoundinreference [4 ].Thecomp…     

Approaches to prediction of impact of Qinghai-Tibet Railway construction on alpine ecosystems alongside and its recovery

With the aid of the Remote Sensing (RS) and Geographic Information System (GIS) technology, the ecosystem pattern and fragility distribution maps of the 50-km-wide zone along the Qinghai-Tibet Railway were compiled and by using the superimposition method, range, area and indexes of the impact of various engineering activities on the ecosystems alongside the railway were studied. By making reference to the ecosystem recovery process of the Qinghai-Tibet Highway, mechanisms of recovery of the alpine ecosystems alongside the Qinghai-Tibet Railway were studied and extents and rates of the recovery were predicted.The results indicate that the impact of the railway engineering on the Alpine ecosystem depends mainly on how much the original surface soil in the zone has been disturbed and how fragile of the ecosystem per se. Restoration of vegetation coverage and species abundance shows a significantly reverse relationship with disturbance of the original surface soil but an extremely positive one with the length of the restoration period and mean annual precipitation and annual mean relative humidity in the period and no obvious bearings with altitude and temperature. In sections with an annual precipitation over 200mm, as long as a certain percentage of original soil is left in situ, it takes only 30 years or so for biodiversity to get basically restored to the original level after the construction is completed but at least 45-60 years or more for vegetation coverage.