城市勘测
城市勘測
성시감측
URBAN GEOTECHNICAL INVESTIGATION & SURVEYING
2015年
1期
89-92
,共4页
大面积%带状%高程拟合%最小二乘支持向量机%二次曲面拟合%BP神经网络
大麵積%帶狀%高程擬閤%最小二乘支持嚮量機%二次麯麵擬閤%BP神經網絡
대면적%대상%고정의합%최소이승지지향량궤%이차곡면의합%BP신경망락
large%zonal%elevation fitting%LS-SVM%quadratic polynomial curve surface fitting%back propagation neural network
介绍大面积带状区域高程拟合方法研究的必要性，并列举了最小二乘支持向量机、BP神经网络、二次曲面拟合三种高程拟合方法。结合工程实例，重点对三种拟合方法在同一个大面积带状区域的高程拟合结果进行对比分析。结果表明，针对本文大面积带状区域，最小二乘支持向量机进行高程拟合获得较高的内外符合精度，该方法具有较好的可塑性和更强的泛化能力。
介紹大麵積帶狀區域高程擬閤方法研究的必要性，併列舉瞭最小二乘支持嚮量機、BP神經網絡、二次麯麵擬閤三種高程擬閤方法。結閤工程實例，重點對三種擬閤方法在同一箇大麵積帶狀區域的高程擬閤結果進行對比分析。結果錶明，針對本文大麵積帶狀區域，最小二乘支持嚮量機進行高程擬閤穫得較高的內外符閤精度，該方法具有較好的可塑性和更彊的汎化能力。
개소대면적대상구역고정의합방법연구적필요성，병열거료최소이승지지향량궤、BP신경망락、이차곡면의합삼충고정의합방법。결합공정실례，중점대삼충의합방법재동일개대면적대상구역적고정의합결과진행대비분석。결과표명，침대본문대면적대상구역，최소이승지지향량궤진행고정의합획득교고적내외부합정도，해방법구유교호적가소성화경강적범화능력。
This article described the necessity of research on elevation fitting methods in the large and zonal area , and presented the LS-SVM,Back Propagation neural network ,and quadratic polynomial curve surface fitting method . With engineering examples are carried out ,focusing on three fitting methods in elevation with a large and zonal area .The results show the LS-SVM obtained a higher elevation fitting comply with internal and external precision in the large and zonal area ,and the method has a more good plasticity and generalization ability .
