mysteries of egyptian zodiacs - HiddenMysteries Information Central
mysteries of egyptian zodiacs - HiddenMysteries Information Central
mysteries of egyptian zodiacs - HiddenMysteries Information Central
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22 1 The Problems <strong>of</strong> Historical Chronology<br />
T . Such a function X(T ) is called by Fomenko the volume<br />
function for X. Of course, it is easy to define many other<br />
similar numerical functions that could be used as an “identificator”<br />
<strong>of</strong> the text X. For instance, the frequency the year T<br />
is mentioned in the subsequent chapters <strong>of</strong> X, the number <strong>of</strong><br />
all the names <strong>of</strong> historical persons listed in the text, or how<br />
many times these names were mentioned in the whole text. In<br />
his monograph [103], A.T. Fomenko used several such functions<br />
to analyze similarities and differences between various<br />
historical documents, for which carried appropriate statistical<br />
calculations and precise evaluations <strong>of</strong> probabilities. The<br />
main problem was to identify which <strong>of</strong> the considered documents<br />
referred to the same epoch or two different epochs.<br />
In the case <strong>of</strong> two volume functions, this could be done as<br />
follows: It is clear that for two different documents X and Y<br />
their volume functions X(T ) and Y (T ) can be completely different<br />
even if they refer to the same epoch. However, if X and<br />
Y describe the same sequence <strong>of</strong> events, then it is most probable<br />
that they will have the same distribution <strong>of</strong> local maxima.<br />
It is quite obvious, that important events in both documents<br />
would be presented in a more elaborated form. That means<br />
for those “important years” T the volume functions X(T )<br />
and Y (T ) would have local maxima. Consequiently, the both<br />
functions X(T ) and Y (T ) would have similar distribution <strong>of</strong><br />
their maxima or the “important years.” A question arises how<br />
to determine the probability that two volume functions with<br />
similar maxima distribution are referreing to the same sequence<br />
<strong>of</strong> events. A.T. Fomenko did the probability calculation<br />
and verify their accuracy on the chronicles related to the<br />
well documented epochs. On Figure 1.23 we show the distribution<br />
<strong>of</strong> local maxima for five different chronicles describing<br />
the same sequence <strong>of</strong> events. It is clear that, indeed, their<br />
maxima are located almost in the same positions.<br />
On the other hand, the coincidence <strong>of</strong> local maxima <strong>of</strong> two<br />
volume functions can be used to identify, with very high probability,<br />
that two hisorical texts describe the same epoch and<br />
the same sequence <strong>of</strong> events, even if they were mistakenly<br />
associated with different epochs. This method <strong>of</strong> matching<br />
dependent texts is called by A.T. Fomenko the principle <strong>of</strong><br />
maximal correlation. This principle was empirically checked<br />
using the reliable historical data <strong>of</strong> 16th – 19th centuries, and<br />
its correctness was confirmed. Therefore, the locations <strong>of</strong> the<br />
maxima constitute the numerical data that can be associated<br />
with the text X in order to characterize the epoch it is referring<br />
to.<br />
An example <strong>of</strong> a simple scalar function, which can be easily<br />
extracted from the historical database, is the functions<br />
<strong>of</strong> the time-span <strong>of</strong> the reign <strong>of</strong> subsequent rulers belonging<br />
to a certain specific dynasty. Such a dynasty function can be<br />
illustrated by its graph, which is shown on Figure 1.24. On<br />
the horizontal axis are placed the subsequent numbers <strong>of</strong> the<br />
consecutive rulers (or names <strong>of</strong> kings, emperors, etc.) and on<br />
the vertical axis is marked the length <strong>of</strong> the reign <strong>of</strong> the corresponding<br />
ruler. Fomenko calls such a sequence <strong>of</strong> rulers a<br />
numerical dynasty or simply a dynasty. The dynasty in the<br />
above example consists <strong>of</strong> 12 rulers. Again, it is clear that two<br />
Length <strong>of</strong> Reign (in years)<br />
25<br />
20<br />
15<br />
10<br />
5<br />
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Dynasty Function<br />
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1 2 3 4 5 6 7 8 9 10 11 12<br />
Consecutive Rulers<br />
Figure 1.24: Example <strong>of</strong> a dynasty function<br />
chronicles (even if they have some discrepancies and are written<br />
in different languages with different calendar conventions)<br />
describing the same portion <strong>of</strong> history, would produce similar<br />
dynasty functions. It is possible to determine the confidence<br />
interval corresponding to a very high probability, that allows<br />
us to identify such dependent dynasty functions, in which case<br />
we can determine that the similarities are not coincidental and<br />
in fact, they indicate that they represent the same sequence<br />
<strong>of</strong> historical events.<br />
The Roman coronation<br />
<strong>of</strong> the Holy Roman<br />
emperors in 10-13<br />
Centuries<br />
41<br />
38<br />
¢<br />
¢<br />
32<br />
¢<br />
24<br />
21 22<br />
1<br />
23<br />
¢<br />
21<br />
¢<br />
18<br />
¢<br />
¢<br />
13<br />
¢<br />
11<br />
9<br />
¢<br />
8<br />
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3<br />
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2<br />
3<br />
4<br />
5<br />
6<br />
7<br />
8<br />
9<br />
10<br />
11<br />
12<br />
13<br />
¢<br />
2<br />
¢<br />
Biblical Israeli rulers<br />
from 922 BC<br />
Figure 1.26: Parallel between the Roman coronation <strong>of</strong> the<br />
Holy Roman emperors and the biblical Israeli rulers<br />
It may sounds strange that mathematical methods can be<br />
effectively used to investigate correctness <strong>of</strong> historical dating,<br />
but it is exactly what is the case here. The methods <strong>of</strong><br />
Fomenko, which are based on theoretical and empirical analy-<br />
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8<br />
12<br />
14<br />
12<br />
10<br />
¢<br />
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¢<br />
20<br />
¢<br />
22<br />
24<br />
¢<br />
¢<br />
30<br />
33<br />
¢<br />
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41<br />
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