{"id":10451,"date":"2021-12-20T09:37:04","date_gmt":"2021-12-20T08:37:04","guid":{"rendered":"https:\/\/www.revistanuclear.es\/uncategorized\/radiological-characterization-of-an-area-impacted-by-mining-using-a-neural-network-developed-with-python\/"},"modified":"2021-12-20T09:45:36","modified_gmt":"2021-12-20T08:45:36","slug":"radiological-characterization-of-an-area-impacted-by-mining-using-a-neural-network-developed-with-python","status":"publish","type":"post","link":"https:\/\/www.revistanuclear.es\/en\/climate-and-environment\/radiological-characterization-of-an-area-impacted-by-mining-using-a-neural-network-developed-with-python\/","title":{"rendered":"Radiological characterization of an area impacted by mining using a neural network developed with Python"},"content":{"rendered":"
\"\"<\/span>SEE FULL VERSION<\/span><\/a>
<\/div>T<\/span>he application of neural networks is a mathematical technique that is arousing great interest among scientists. Neural networks are a tool that allows the scientist to make predictions from a set of theoretical or experimental results. In this work, the authors have applied a neural network developed with the Python programming language to the radiological characterisation of a waste dump of the abandoned copper mine Antigua Pilar<\/em> located in the Madrid municipality of Comenarejo. This mine has the peculiarity of being located in an area rich in minerals with a higher content of natural radionuclides, which makes it very interesting from a radiological point of view.<\/span><\/p>\n
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