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为了发挥Fortran易于科学计算的优点和C#在界面编写以及批量处理文件的优点,首先通过Fortran控制台程序编写相应算法的动态链接库,然后利用C#编写的界面程序调用在Fortran中生成的DLL文件,从而实现混合编程。详细阐述了两种语言混合编程的实现方法。通过利用卫星测高数据计算南海海域的垂线偏差,验证了该方法的正确性及优越性。通过混合编程,充分发挥两种计算机语言各自的优点,说明了可以利用混合编程的方法大批量自动化地处理卫星测高数据,同时该方法便于算法维护和升级。 相似文献
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Data are very important to build the digital mine. Data come from many sources, have different types and temporal states. Relations between one class of data and the other one, or between data and unknown parameters are more nonlinear. The unknown parameters are non-random or random, among which the random parameters often dynamically vary with time. Therefore it is not accurate and reliable to process the data in building the digital mine with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method to process data in building the digital mine is put forward. In the meantime, the corresponding mathematical model is also given. The generalized nonlinear least squares problem is more complex than the common nonlinear least squares problem and its solution is more difficultly obtained because the dimensions of data and parameters in the former are bigger. So a new solution model and the method are put forward to solve the generalized nonlinear dynamic least squares problem. In fact, the problem can be converted to two sub-problems, each of which has a single variable. That is to say, a complex problem can be separated and then solved. So the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations. The method lessens the calculating load and opens up a new way to process the data in building the digital mine, which have more sources, different types and more temporal states. 相似文献
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本文以模糊数学理论为基础,通过对影响地形图质量的多种因素分析,建立了地形图质量评定的模糊综合评判模型。实例分析表明该模型可以克服传统地形图评价方法的主观性和模糊性,证明该法是行之有效的。 相似文献
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现使用的陀螺经纬仪具有摆动周期长,结构复杂等缺点。为了克服这些缺点,本文提出了单自由度陀螺寻北仪的结构模型,并用分析力学的方法研究了其定向原理,分析了陀轴的运动规律,指出发展单自由度陀螺寻北仪的可能性。 相似文献
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1 OPTIMALCONDITIONANDITSGEOMETRI CALCHARACTERSTheadjustmentmodelwithnobservationandm(m <n) parametersmaybewrittenaslr =yr(xa) erei ~N( 0 ,gij) ( 1 )where lr(r=1 ,2 ,… ,n)representscomponentsofobservations;er(r =1 ,2 ,… ,n)representscomponentsoferror;yr(ua) (a =1 ,2 ,… ,m)isassumedt… 相似文献