基于模糊支持向量回归算法的微地形异常值剔除研究  

Eliminating the Exceptional Values of Microtopography Based on Fuzzy Support Vector Regress Algorithm

作　　者：罗柏文[1] 夏毅敏[2] 樊宏亮 韩振兴 宋子辉 

机构地区：[1]湖南科技大学 [2]中南大学 [3]中煤能源集团公司平朔2#井洗煤厂 [4]开滦集团东欢坨矿业公司 [5]北京京北方科技股份有限公司

出　　处：《金属矿山》2009年第10期122-125,共4页Metal Mine

基　　金：国家自然科学基金(编号:50875265;50474052)

摘　　要：在水下微地形探测过程中,由于混响、噪声干扰、底质特性以及坡角等因素的影响,即使利用超声波振幅相关检测法精密检测回波信号,计算出来的微地形高程数据也会出现一些异常值,而运用传统的最小二乘法重构出数字微地形难以表征其真实的形貌,由此建立了准确度因子为散射回波最大相关系数的模糊支持向量回归算法。该算法具有严格的数学基础,尤其在在小样本情况下,在数据回归方面具有很大的应用潜力。对比实验证明,该算法的回归直线能有效地消除异常值的影响,充分反映出了实际微地形的表面轮廓。In the survey of underwater microtopography, due to the influence of such factors as reverberation, noises disturbance, characteristics of bottom materials and gradient, there can be some exceptional altimetric values of microtopography in the computation result even if an accurate detection of echo signals is made by ultrasonic wave amplitude-related method, and the true landform is hard to characterize by digital microtopography reconstructed by the conventional least square method. Therefore, the algorithm of fuzzy support vector regression with the most interrelated coefficient of dispersion echo as accuracy factor was established, which, based on a strict mathematical theory, has great application potential in data regression, especially for small samples. The comparative experiments indicate that the algorithm＇s regression line can effectively eliminate the effect of exceptional values, so as to well reflect the exterior figure of actual mierotopography.

关 键 词：微地形 超声波 最小二乘法 散射回波 模糊支持向量 

分 类 号：O4-39[理学—物理] TU457[建筑科学—岩土工程]