It is a very difficult problem to predict landslide and slope-rupture.
It cannot he denied that various predictions of these means have their own merits and demerits.
But, at present, the best way for the prediction of slope-rupture is, I think, to make a quantity analysis through a precise and rigid grasp of some factors in slope-rupture.
In the analysis multiple regression analysis of multivariate analysis is used.
An unknown field of this learning is considered here.
In the dissertation, a theoretical study for the establishment of this means in the scientific field concerned is taken into consideration.
The theoretical method of this investigation is, first of all, briefed in “Construction of predict technology of slope-rupture”.(Fig. 1)
Fig. 1 shows, especially, that, for an appropriate selection of factors for each phenomenon, we should always return from the column of the selection of each factor in each natural phenomenon to the column of the setting up of construction factors of slope-rupture.
Therefore, this is a feedback circuit in the systematization of predict technology of slope-rupture.
How to grasp construction factors of slope-rupture and their functions is an important condition in the establishment of predict theory. This is briefed in Fig. 2.
By the following expression, the answer can be got.
R=
R0X1r1X2r2X3r3X4r4 I
log
R=log
R0+
r1log
X1+
r2log
X2+
r3log
X3+
r4log
X4 II
This is an expression which shows a model for predict decision value of slope-rupture.
Fig. 3 shows related situations of coefficient factors.
As primary factors in the occurence slop-rupture are subsurfacegeology, “Key to the classification of the subsur facegeology” is indicated in Table 1.
View full abstract