just wanted to write to you again:
I'm sitting here now and it's 2:00 am at my place.
I looked at the course in Australia and it's worse than it was here in Germany on Friday
I had now found two contact addresses for our new company that I found very interesting and then researched, I wanted to send them to you here because they are really very interesting.... unfortunately I can't find them anymore because of all the searching around.
However, I might have something else for you here, as I believe this partnership is very important
and our team at BRN has thought of it very well. Still, I'm very sorry I didn't find the other one I already had, but I'll find it again, I promise you.
I'll tell you what, on days like this I think it's great to be a BRN shareholder. When I came to you, this forum consisted of nothing but people who only believed in BRN, I liked that. People who believe in making a quick buck can be right or wrong here, just like any other stock.
I've been sitting for a year now and am in the red. Would be fun if it was different. I would not have thought that today it would go down further than Friday.
This Saturday I had fun with the message and with my hick hack with Rise of the Ashes.
We cannot change the course here, we can decide whether to invest.
If you don't want to or can't prepare yourself for a longer investment, I thought this is the wrong forum for you.
and now I go to sleep knowing that our course in Germany is red, but ok... I know it's a shame... but I think whoever stays here for a long time will be rewarded... except for the Chienese who catches one too War on... good night
one more thing... i miss FF!!!!!
EXECUTIVE SUMMARY
The client is a large Power Company that generates and distributes power from traditional as well as alternative sources such as Solar, Wind, etc. The main challenge for them was how to balance Power scheduling / allocation between traditional energy and alternative energy. This was due to the daily unpredictable variations from their solar Power generation. This required accurate solar power generation prediction based on geographical parameters like longitude, latitude, weather, sun intensity, cloud cover, relative humidity etc. After a detailed evaluation of their operations, AI Labs (
www.ailabsinc.com) used its proprietary Minsky AI Engine to optimize the models by using a combination of AI algorithms and prediction attributes. In this case, Minsky used historical power generation data along with other weather related attributes for model creation. Weather forecast data was then used in conjunction with the Minsky models to predict Solar Power Generation for future dates. This solution was optimized and implemented in less than a week.