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Project 81 Exploration Update - Crawford Twp. Property CARDS-Artificial Intelligence (AI) Report
(via TheNewswire) Toronto, Ontario / TheNewswire / July 17, 2018 - Noble Mineral Explo...
About this update from Noble Mineral Exploration Inc.
[{"type":"text","content":"Project 81 Exploration Update - Crawford Twp. Property CARDS-Artificial Intelligence (AI) Report(via TheNewswire)\n\n \nToronto, Ontario / TheNewswire / July 17, 2018 - Noble Mineral Exploration Inc. (\"Noble\" or the \"Company\") (TSX-V:NOB, FRANKFURT: NB7, OTC.PK:NLPXF) is pleased to publish the Artificial Intelligence exploration potential results for the Crawford Township Property that has been optioned to Spruce Ridge Resources (\"Spruce Ridge\" TSX-V: SHL). The AI study has been recently completed by Albert Mining Inc., of Brossard, Quebec using their proprietary Computer Aided Resources Detection Software (CARDS) \"Artificial Intelligence\" (AI) Technology and Data Mining Techniques to further enhance and upgrade the target selection process within Project 81. \n\n \n \n\"CARDS\" is a state of the art computer system that uses the latest artificial intelligence (AI) and pattern recognition algorithms to analyse large digital exploration data sets, such as with Project 81, and produce exploration targets. CARDS uses many layers of gridded data(variables) to learn the \"signature\" of known mineralized sites (positive cells) in a given area, which are then scored and cells with high similarity to the \"sought signature\" are identified.\n\n \n \nProject 81, is a 70,000 hectares, under-explored, contiguous land package covering 12 townships just 3km north of the Kidd Creek Mine. (Figure-1).\n\n \n \nThe Crawford Township Property (~17,000 hectares - 171.28 Km2) target objectives were Copper-Zinc and Nickel targets. The results of the study generated eleven (11) Cu-Zn targets that show 80%+ similarity prediction using the AGEO Cu-Zn Model (Figure 2), and nine (9) Ni targets that show 80%+ similarity prediction using the AGEO Ni model (Figure 3). AGEO (Aggregation of GEO-referenced model) is one of two (2) algorithms used to determine and validate the accuracy of prediction of the model. The other being the C-Cluster algorithm which is used to compare and validate predictions generated by the AGEO algorithm\n\n \n \nThe Study incorporated a total of 2,632 training points that were subjected to evaluation using merged helicopter-borne Time Domain Electromagnetic (HTEM) and Magnetic surveys completed by Triumph Geophysics in 2017 for Noble Minerals Exploration Inc., at 25m resolution, together with historical diamond drill hole ...