Windfall Geotek Inc C.WIN

AI works read below the proof

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owered by Artificial Intelligence(AI) since 2005! 
Windfall Geotek- The first(2005) and  latest Artificial Intelligence(AI) and pattern recognition algorithms for the mining. 
Windfall Geotek can ‘SCORE A MINE TO FIND THE NEXT MINE’. Or we can use an old expression” The best place to find a mine is beside a mine”. This is exactly what our CARDS system is able to do. We can work in 2D and 3D. 
I'm sending you some benefits of using CARDS: 
CARDS is a tried and tested technology developed and continuously improved by DIAGNOS multidisciplinary scientific team;
It generates added value to different layers of existent geophysical, geochemical and geological data;
It finds patterns in a multidimensional dataset that are too difficult to perceive by humans;
It generates prospectively maps that can be easily integrated in GIS such as MapInfo, ArcGIS and GeoSoft;
The results are produced in order to support geologists and geophysicists in the exploration process;
The Prospectively maps can be used as a marketing tool to promote exploration investments; 
WHY CARDS EXCEEDS ALL OTHER STATISTICAL TOOLS? 
1.      The use of neighbourhood operations: a neighbourhood for each point:
The grid pixels are not only analysed individually, the spatial relationship between each pixel and its surroundings is taken into account in the modeling. For example, a RELATIVE DEVIATION function returns to the central pixel a percentage of variation of the different pixel values in the neighbourhood. This type of function can be used, for example, to find edges of polygons of different lithological units whereby it returns a low value for the interior of a lithological unit or a higher value along the contacts of two lithological units (Carranza, 2008).
2.      No use of negative occurrences in creating signature:
We are confident of positive occurrences but no one can be sure that a negative cell is negative and not only poorly explored. We use only ‘positive’ and ‘unknown’ labels in our models.
3.      No over-learning: Several models are combined to avoid over-learning.
4.      A result of aggregation of different models: 
THE EFFECTIVE WAY TO HAVE A GOOD PREDICTION IS TO COMBINE MULTIPLE MODELS. 
The backbone of CARDS is the MCubiX-KE data mining engine. MCubiX-KE uses powerful pattern recognition algorithms to learn the “signatures” or “fingerprints” of known mineralized sites, uses these as a training data set, and identifies points (targets) with a high statistical probability of similarity to known areas of mineralization across less explored regions. 
Data is entered into CARDS in the form of geo-referenced data points and images. Each point in the database is linked to its own set of characteristics that are extracted from a variety of sources, for example:  

• Geological maps: rock type, alteration
• Geophysical surveys: magnetic fields, derivative fields, gravity, radiometry
• Geochemical surveys: rock, soil, Lake Bottom, drill hole assays
• Digital elevation models
• Satellite imagery
• Proximity to mineral occurrences / mineralized drill holes
• Proximity to lithological contacts / specific intrusive suites
• Proximity to interpreted lineaments / mapped faults and shear zones  

You don't need to hold all this variety of data’s  or variables. More than 80% than all our discoveries were done just using Geophysical surveys and Digital elevation models. In addition, in the analysis of each point in the database, the characteristics of all points within a specified distance (neighbourhood) are weighed into the evaluation of that point. In this manner, points lacking data can still be highlighted by CARDS if the combination of their limited characteristics and their proximity to points with other significant characteristics is similar to that of known positive points.  
Targets generated by CARDS should be evaluated in conjunction with all readily available geological data in the evaluation of the economic potential of a property as well as in the outlining of exploration targets. In the same time, aside from a roster of well-known companies that have used CARDS technology to augment their mineral exploration programs in the past.