Possibilities of Cause-and-Effect Simulation in the Study of System Climate-Ocean-Sediments
219
the versions I, 11.2, 111.1 of hypothesis B are correct. Then step 8 is realized;
(3) each variable from the conjunction relating to the file rc can be represented in its turn as a conjunctive function of variables from the conjunction
relating to the file roo Then the versions 1,11.2,111.1 of hypothesis C are true,
and step 8 is fulfilled; (4) not all variables from the conjunction relating either to the file ro or to the file rc are submitted to the conditions of items (2)
or (3). This means that some complicated hypothesis is true, and step 8 is realized.
6. Hypothesis A is verified. To do this, the files ro and rc are united in one file
T*. Then Procedure III is applied to T*. If the function f can be expressed as
a conjunction of variables from T*, then the hypothesis A is accepted, and
step 8 is realized. If there is no such dependence in T*, the hypothesis A is
rejected.
7. Conclusions as to the absence of CE relations between the phenomena under study are drawn.
8. Steps 1-7 are applied to the file T - instead of the file T+, and then step 9 is
fulfilled.
9. By the Morgan rule, the results of steps 1-7 and 8 are united. The variables
which are not arguments of the function f are removed from data files (from
T* for the hypotheses A and from ro, rc for the others). Then the procedures
II, III and also some additional operations which are different for the different
hypotheses are applied to these files. As a result, a formula (DNF) describing
the resultant type of CE relation for the problem under study is constructed.
10. End of data processing.
5
Possible Application
There were no real data to carry out demonstrative investigation of the system
climate-ocean-sediments, and even data in Tables 2-4 are imaginary. Thus, only
general trends of the system study are outlined here.
1. Spatial CE analysis. This trend is the most suitable for thematic investigations and study of phenomena having a low velocity of change. While using the
spatial CE analysis, data relates to stations, profiles, areas or to other spatially
distributed objects (e.g., Table 2) and the time is assumed to be fixed. As a result,
regularities in the spatial distribution of a certain sediment properties are
found, in particular the climatic-oceanic settings causing this property are revealed. Clearly, the knowledge of such settings may be helpful in paleoclimatic
investigations. Dependencies revealed by CE analysis, are described by formulas. In the case of spatial CE analysis, they can also be expressed by maps.
2. Time CE analysis. Obviously, the time CE analyses is mainly appropriate
for the study of phenomena with a high velocity of change. In this case, a data
file includes time moments (years) of observations as objects (e.g., Tables 3,4).
It is clear that all observations must be related to one fixed territory (the same
station, region and so on). If several territories are considered, several data files
219
the versions I, 11.2, 111.1 of hypothesis B are correct. Then step 8 is realized;
(3) each variable from the conjunction relating to the file rc can be represented in its turn as a conjunctive function of variables from the conjunction
relating to the file roo Then the versions 1,11.2,111.1 of hypothesis C are true,
and step 8 is fulfilled; (4) not all variables from the conjunction relating either to the file ro or to the file rc are submitted to the conditions of items (2)
or (3). This means that some complicated hypothesis is true, and step 8 is realized.
6. Hypothesis A is verified. To do this, the files ro and rc are united in one file
T*. Then Procedure III is applied to T*. If the function f can be expressed as
a conjunction of variables from T*, then the hypothesis A is accepted, and
step 8 is realized. If there is no such dependence in T*, the hypothesis A is
rejected.
7. Conclusions as to the absence of CE relations between the phenomena under study are drawn.
8. Steps 1-7 are applied to the file T - instead of the file T+, and then step 9 is
fulfilled.
9. By the Morgan rule, the results of steps 1-7 and 8 are united. The variables
which are not arguments of the function f are removed from data files (from
T* for the hypotheses A and from ro, rc for the others). Then the procedures
II, III and also some additional operations which are different for the different
hypotheses are applied to these files. As a result, a formula (DNF) describing
the resultant type of CE relation for the problem under study is constructed.
10. End of data processing.
5
Possible Application
There were no real data to carry out demonstrative investigation of the system
climate-ocean-sediments, and even data in Tables 2-4 are imaginary. Thus, only
general trends of the system study are outlined here.
1. Spatial CE analysis. This trend is the most suitable for thematic investigations and study of phenomena having a low velocity of change. While using the
spatial CE analysis, data relates to stations, profiles, areas or to other spatially
distributed objects (e.g., Table 2) and the time is assumed to be fixed. As a result,
regularities in the spatial distribution of a certain sediment properties are
found, in particular the climatic-oceanic settings causing this property are revealed. Clearly, the knowledge of such settings may be helpful in paleoclimatic
investigations. Dependencies revealed by CE analysis, are described by formulas. In the case of spatial CE analysis, they can also be expressed by maps.
2. Time CE analysis. Obviously, the time CE analyses is mainly appropriate
for the study of phenomena with a high velocity of change. In this case, a data
file includes time moments (years) of observations as objects (e.g., Tables 3,4).
It is clear that all observations must be related to one fixed territory (the same
station, region and so on). If several territories are considered, several data files