Newsgroups: alt.paranet.ufo
From: kymhorsell@gmail.com
Subject: modeling ufo interplanetary travel

[uploaded 69 times; last 31/10/2024]

EXECUTIVE SUMMARY:
- We extend a s/w that correlates day by day planetary parameters with
  (lagged) daily UFO sightings.
- We use the s/w to match patterns found in the observations against
  a 2nd model of a "UFO fleet" operating across the solar system
  according to simple rules. All the simplest variations on the theme
  were pre-computed to match against the actual correlations we observed.
- Looking at UFO types "all", "Lights" and "Non Lights" we find the
  simplest apparent set of assumptions that matches the observations is:
  the probability of a flight from A to B depends on the present
  distance between A and B; most UFO's originate nr Saturn; "Light" UFO's
  seem to originate nr Neptune (and maybe even the Sun, the s/w finds);
  Non Light UFO's originate mostly from Saturn with some from Neptune.
- Other origins can't be eliminated because only the simplest set of
  scenarios were used in this study. Even more slightly complex
  assumptions are likely to produce different results given the
  chaotic and inter-correlated nature of planetary movements.



We've seen in a previous post how the positions of the planets seem to
correlate highly with day by day UFO sightings across N America.  
In particular we found the distance between Saturn and the Earth seemed
to explain a big chunk of sightings and other data showed it was not
likely a significant number of UFO sightings were just a matter of
confusing Saturn with a "real" UFO.  (E.g. the same patterns were seen
for day/night sightings and sightings of objects that don't seem to be
confusable with a planet).

To extend that work I've added more planetary parameters to the mix. 
The visual position of each planet -- declination and right
ascension -- boost the list to 13 parameters for each "normal"
planet, and 15 in the case of Saturn with its rings.  We can now
correlate this set of time series against UFO data for various types
of object to see how well each planetary param can predict future
sightings. It's assumed a lag between the change of a planetary
position "now" and UFO activity in N days might indicate "something"
is travelling between that planet and Earth and taking maybe around N
days to do it. In this way we found last time a lower bound on
putative UFO movements between planets was substantially sub-FTL.

Working with an AI s/w has been overall a boon to this work. 
While an AI program spitting out results can be tedious to check and
nr impossible to debug, it can also help in its own development. 
In this case the s/w, which uses some standard stats
tools to do some of the heavy lifting, discovered one package gave
unusual results in some cases. This is often the case when packages
are pushed (by statisticians) further than their designers envisioned.
But a "problem" with AI's is they tend to push whatever tools they are
allowed to use *well* past design limits. They have generally no
concepts how a package is typically used or what kind of data people
normally give it; they just use it if, when, and how they see fit.
Sometimes the tool obviously breaks or spits out an answer that
is wrong but without printing a warning message with it the AI might
pick up on.

After much nail biting the problem in question was tracked down and fixed. 
The up side is the stats s/w now outputs numbers with a known and 
laboriously hand-checked ;) error bound -- generally +- 5%.  If 2 R2
correlations (normally I use the R2 statistic from various time series
regressions) differ by say 10% across their common average then the
larger one is "most likely" really the larger. If they are closer than
10% then the ordering can't be unambiguously determined.

So the AI can now "confidently" print out a list of correlations of
sightings of UFO types (shape/color) against day by day (and hour by hour if
necessary) planetary movements at the time and order them from largest
to smallest.  The larger correlations are then the "most likely" ones
to be "real" and not due to some luck-of-the-draw in the data.  And
the order of the correlations show e.g. which planets are "more involved" 
in the particular kind of UFO activity, and which are less involved.

For example. We can correlate the daily UFO sighting totals against
planetary movements from an s/w ephemeris and find the table:

Planet	Parm	R2
		(from a TS regr of daily optimally lagged planet 
                param predicting UFO sightings)
mercury	Dec	0.56812030
neptune	rg	0.50386267
venus	Dec	0.47351440
uranus	rg	0.45647785
saturn	rg	0.43902437
venus	RA	0.41095631
jupiter	Dec	0.27301541
pluto	rg	0.23986765
mars	RA	0.21302930
  Dec == declination (celestial latitude) of planet in degrees
  RA == right ascension (celestial longitude) in degrees
  rg == distance between planet and Earth in AU

The table shows the "most involved" param with daily total UFO sightings 
is the declination of Mercury.  The next most correlated is the
"geocentric distance" to Neptune.  (Note the diff in R2 between 1st
and 2nd place is slightly more than 10% of either).  Etc.

And now the complication. The AI has warned me already that we can't
just assume most UFO's are coming from Mercury because of the first R2
in the list.  They may be coming *via* Mercury, for example.  And in the
latest twist the AI s/w has proved to itself and me the correlation
between Mercury's declination and UFO sightings may be "induced" by
something else because the movement of Mercury is synchronized with
other planets in the solar system. The distance between planets and
their periods are not random numbers. They are correlated by Bode and Kepler!

Up to recently I had assumed planetary parameters were "more or less"
statistically independent, close enough. But it turns out some are
way way NOT independent of others.

It is therefore necessary to run the AI to look at the pattern of
correlations and *measure* which set of simple assumptions best
matches the list of values we found.  We need the s/w to essentially
"get inside the head of" UFO captains and simulate flying between
planets under different kinds of assumptions, and pick out which set
produces results most like the correlations we have above. Only in
SOME cases will the largest correlation straight out point at the most
interesting planet.  Sometimes the real interest will be lower down on
the list or maybe be "hidden" and not appear on the list at all.

To that end I hacked together another model that takes the planetary
parameters output from the ephemeris s/w, takes a set of assumptions
and strategies a UFO captain might use to decide when and where to fly
from their current location, and collect the correlations as we have
measured above for "real UFO sightings", and determine which strategy
looks to be closest to those observations.

While there is no guarantee we will find the *actual* strategy used
to fly between different planets of our solar system, we will likely
end up with "a" simple set of assumptions that produce a similar
result to the one we actually see.  It will give us a "mental model"
of what may be going on, rather than "fact".

It would obviously be interesting to see what those set of strategies
might look like.

Drum roll Mr Music! ....

The output from testing a big set of simple strategies is as follows:

Strategy		R2 (measure of likelihood the set of
		        assumptions named
			explains the observed set of Dec/RA/rg correlations)
only6-t			0.81282165
only72-t		0.47853941
only60-t		0.37906993
only76-t		0.35098475
only64-t		0.33747267
dis1-t			0.29975186
everywhere-t		0.25808418


All the strategies above assume a UFO captain starts from some subset
of planets and has a free choice to go to any other in the solar system.  
For completeness I also include the Sun (ouch ouch ouch!)  as both a
source and destination.  His destination choice is weighted by how
close each other planet is at the time.  Closer planets are weighted
proportionally more likely to be chosen for the next trip.  Depending
on the distance the trip takes a proportionate time. If the
destination planet is Earth then we assume on approach to Earth the
UFO is seen, to be included in the sightings on that day. If the UFO
is *leaving* Earth for some other planet we assume it is sighted
leaving on the day the trip starts.

The strategies above then only differ by which planets are assumed to
be the possible starting points for trips. E.g "only6" means "only
Saturn". "dis1" is "everywhere except Mercury".  "only76" is only
Saturn and Uranus. &ct.

So we see the stand-out best match of our "Let's Play UFO Captain" is
"Only Saturn".  The set of correlations at the top of the post seem to
unambiguously point at Saturn -- of course more likely one of its more
interesting moons -- as the major origin of almost all UFO objects
sighted on Earth.

This is consistent with what we found before using much simpler
methods that just looked at the correlations between sightings and the
distance of each planet. Saturn appeared at the top of that (simple) list.  
So we have "simulated UFO flights" and found the same answer so now
have slightly more confidence that finding is correct.

What seems to have been ruled out now is something that had seemed at
one time more likely -- UFO's originating on most planets in the solar system. 
It seems the big correlations we obtain for other planets -- either
their distance from Earth or their apparent position in the sky (as
seen from Earth) -- are "by products" of the movement of all the
planets being coordinated by the laws of gravitation. :)

Of course this latest work is predicated on the simple assumptions
we've made are "correct", or approximately correct.  If the true
situation is more complicated then all bets are off and maybe UFO's
might originate from other planets than Saturn.

Finally, we can do the same tricks for different types of UFO's.  Some
shapes or colors cause the AI used here to give up and not decide from
the observations which flying strategy is more likely.  There is not
enough data (the high quality UFO sighting data I use from NUFORC
starts in early 2006) or the data we have is too noisy from mistakes
and hoaxes to choose between even the simple alternatives we have used above.

But a couple of key UFO types run through the simulate-and-match s/w fine.

E.g.  "light in the sky" UFO's are likely a grab-bag of all kinds of
things including mundane satellites, planets, and LED kites.  But also
a few "unknown" objects.  Let's see whether the AI can drill down into
the data and find a planet where they might be coming from.

The list of correlations between planetary params and "lights" type
UFO sightings is:

Planet	Param		R2
saturn	rg		0.52515325
uranus	rg		0.48244359
mercury	Dec		0.45859890
neptune	rg		0.39373586
venus	Dec		0.37491284
jupiter	Dec		0.34234073
jupiter	RA		0.30687365
mars	rg		0.22915010
pluto	rg		0.18996626

Wow. Right at the top is says the distance to Saturn is the major
correlation. Surely this must mean the AI will pick "Saturn only" again...

Using the simulate-and-match s/w the top strategies that match the
above list of correlations is:

Strategy		R2 (likelihood of strategy producing the
			correlations we see above)
only80-t		0.68358740
only8-t			0.60636297
only83-t		0.52888418
only84-t		0.51587928
only6-t			0.33140172
only87-t		0.30025828
only86-t		0.28551806

Interesting! Now it says the pattern for "Lights" suggests they are
coming from Neptune and the Sun! In 2nd place it says "Neptune only"
is a likely explanation for the observations. In 3rd place it says
"Neptune and Earth" and 4th is "Neptune and Mars". It's only down in 5th
place it "takes the bait" of the large corr between distance to Saturn
and daily UFO sightings and says it might be all coming from Saturn. 
But the relative chance of "only saturn" versus "only neptune" is
around a 2-to-1 difference in favor of Neptune.


Finally, we can take the complement of "Lights" and look at "Non
Light" UFO's. At least these should reasonably be expected NOT to be
confused with a long list of star-like suspects. Of course it's also
expected daytime or dark UFO's can be confused with aircraft and
drones and other mundane things. But we might expect a lower noise factor.

The list of planetary correlations for Not-a-Light UFO sightings is:

Planet	Param		R2 (planet param predicting daily sightings of
			Non Lights)
mercury	Dec		0.56434431
neptune	rg		0.53736315
uranus	rg		0.50838866
venus	Dec		0.48216660
saturn	rg		0.45602463
venus	RA		0.39064275
jupiter	RA		0.26042923
mars	rg		0.25687112
pluto	rg		0.24839742

This time Neptune comes 2nd in the list. Will the AI pick Neptune as
the source for Non Lights. Or is it "more complicated than that"?

The list of strategies that match the above correlations is found to be:

Strategy		R2
only83-t		0.46722888
only86-t		0.35696505
only6-t			0.31287376
dis1-t			0.25339020

The most likely simple strategy that produces the observed pattern of
correlations between planetary params and UFO sightings is "only83" --
that Non Light UFO's are coming from Earth and Neptune.

But now we have a problem. The AI picks Saturn for "all UFOs" but has
picked Neptune for Lights and Not Lights -- i.e.  each ~1/2 of "all UFOs". 
It has not spotted (because it wasn't told about the relationship between 
the UFO types) that these predictions are somewhat logically inconsistent.

One resolution for us (apart from going back and making the s/w
understand that its solutions for "all UFOs" must jive with "Light"
and "not Light" being 2 non-overlapping subsets of the same thing) is
immediately apparent. The No 2 pick for "Not Lights" is "only86" --
Neptune & Saturn.

So the overall solution might be "most UFO's appear to come from
Saturn", but "Light" UFO's mostly come from Neptune (and maybe the Sun?).
"Non Light" UFO's (mostly) come from Saturn and the rest from Neptune.

At least that's seemingly the simplest explanation for all the
correlations we have, above.

--
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