�Զ������ݻ������õ����ѿ��Ƶ㡣�Զ��ѿ��Ƶ�ΪԼ�����Զ��ѽ��е��ֵ���Ե���ͳ�Ƶ�ԪΪ�Ӵ���ͳ�����벻ͬդ���ڵIJ�ֵ����Ŀ��������ò�ֵ�����벻ͬդ��ĸ��ʣ��Ա���������ϣ��õ�������Ϣά�Լ����ϵ��������˼·Ӧ���ڽ�����ݸ����ζ��ѷ��������У��ֱ�����˶��ѳ�����Ϣά�������Ϣά�����������90% ���ϵ�ͳ�Ƶ�Ԫ���ϵ�� �� 0. 9�����ѷ��������нϸߵ��������ԣ�������������������ߵ����ϵ�� �� 0. 999��������ݶ��ѵļ����������˼·�Dz���������Ϣά����Ч�������ܹ���߹���Ч�ʣ����нϺõ�Ӧ��ǰ����

 The fracture controlling points can be obtained by data processing of faults�� Taking the controlling
points as the restraint��we carry on an interpolation to the fault�� In single statistics unit��for windows��different
numbers of interpolation points fall into different grids��the probability of interpolation points are obtained in differ-
ent grids�� Through the variable data fitting��we get the fault information dimension and correlation coefficient�� This
approach is used in the Jinhu Sag E 1 f 2 fracture fractal evaluation�� fracture length information dimension and area in-
formation dimension were calculated�� ��esults show that more than 90% of all statistics unit correlation coefficients
are higher than 0.9��fault development zones have higher self- similarity and the fault overall fractal characteristic
curve correlation coefficient is greater than 0. 999�� The fault information dimension calculation of Jinhu Sag show
that the approach is an effective way to measure the fault information dimension��and it can improve the working ef-
ficiency and has a better application prospect��