在实验误差条件下,用最陡下降法求极值

Nona Otkhozoria, Vano Otkhozoria, Shorena Khorava
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引用次数: 0

摘要

在实验中存在错误的情况下,采用最陡下降法学习最优搜索的一种扩展一级方法。对最陡下降法进行了研究,并成功地应用于实验中没有错误的情况。然而,在实际情况中,所使用的测量手段总是有确定的误差,这是由于响应的适当含义接收到错误。当步长不依赖于目的函数的含义时,建立了最陡下降算法的模型。设计了步进过程在计算机数学MathCAD中的实现算法和程序编制。给出了不同意义下的实现结果错误,并根据函数意义和参数意义给出了最优点方向的步进运动。建立了所需策略量逼近所需策略量的最小值,在不同水平的地震振幅周围实验误差在不同阶跃条件下的最优搜索效率。
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SEARCH FOR AN EXTREMUM USING THE STEEPEST DESCENT METHOD UNDER THE CONDITIONS OF EXPERIMENTAL ERRORS
One of the spread first level methods of optimum search is learned by the steepest descent method in conditions when there are mistakes in the experiment. The steepest descent method is investigated and is successfully applied in situations, when, there are no mistakes of experiment. However, in real situations the used means of measurement always have determined errors owing to what the appropriate meanings of the response receives with mistakes. The model of the steepest descent algorithm in created, when the length of the step does not depend on the meaning of the purpose functioning. Stepping process realization algorithm and program provision in MathCAD, computer mathematic, system is designed. The realization outcome mistakes for different meaning are presented, the step movement of the optimum dot direction is shown according to function meaning and argument meaning as well. The amount needed for the tactics necessary to approach the minimum is established, the quake amplitude in the surrounding of different level experiment mistakes at the optimum search efficiency in different step conditions.
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来源期刊
Pharmacy World & Science
Pharmacy World & Science 医学-药学
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>12 weeks
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