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Computer Aided Economic Science for Environmental Development

We are part of the American Butterfly Global economic science initiative. A system has been designed for a new type of economics, a new economic computer science has been created, which avoids rounding errors and other

chaotic factors within large financial networks. This has been enhanced, by structuring the base of the network complexity around the mathematical principles of String Theory.

The last significant factor is the electronic probability theory, based on the Monte Carlo Effect method for creating the largest of nuclear reactions. But in short, its simply a case of making sure each probable outcome

is at least 95% to one, and when it is, its deemed “suitably efficient”

Probability math takes centre stage in the 3rd American Butterfly books, It manifests itself as the product S-World UCS “Universal Colonization Simulator.”

It is exactly what is says it is, a tutorial game, that is the Global Network, of which parts are sent years into the future, so those in the network can see future successes and failures well before they actually happen. An Extremely practice usage for quantum probability theory, to simulate ones future

Added to this, the efficiency of the first Economic String Theory business and computing model and in theory, backed by high success probability stats. S-World Global Network generates such finances that the network can literally buy the world out of economic dangers and stop Global Warming within 20 or so years, plus create a extremely space and scientific research programme, not currently dreamed about in today’s economics.
All thanks to some rather simple but effective Probability Math, combined with Chaos Math and Sting Theory. We call it CFM “Compatible Finite Mathematics. But, its not been validated by the physics and math Community, as it turns out, such comminutes are rather elusive, which is odd, hence making this site and others.

We are looking for physicists mathematics, and computer science persons, to help prove our finding.