عنوان :
شناسايي زونهاي مستعد كاني سازي سرب و روي در محدوده برگه 100000 :اورچه با استفاده از روش شبكه عصبي فازي در محيط GIS
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
اكتشاف معدن
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان،دانشكده مهندسي معدن
صفحه شمار :
د، 90ص.: مصور
استاد راهنما :
حسن طباطبايي، نادر فتحيان پور
توصيفگر ها :
تلفيق اطلاعات , شبكه عصبي - فازي , منطق فازي , كاني سازي تيپ مي سي سي پي , تحليل خوضه هاي آبريز , سنجش از راه دور
تاريخ نمايه سازي :
1394/10/14
استاد داور :
محمدرضا ايران نژادي، رضا جعفري
تاريخ ورود اطلاعات :
1396/10/06
چكيده انگليسي :
91AbstractIn order to make a mineral exploration program successful a large amount of exploratory data includinggeophysical geochemical and remotely sensed images gathered during different mineral explorationstages are needed It is well known that all exploratory data are inherently associated with some sort ofuncertainties so employing data driven methods such as Boolean or weight of evidence may causesignificant errors in the course on data integration Therefore most researchers have focused on usingknowledge driven methods such as fuzzy logic and more recently the combined fuzzy and neuralnetwork approaches called neuro fuzzy method which deploy the privileges of both data and expertknowledge simultaneously The investigated area is bounded by the Varcheh geological map which is part of Sanandaj Sirjanstructural zone This zone is considered as highly favorable for Pb Zn MVT mineralization In this studythe available exploratory data including geochemical stream samples airborne magnetic data alterationzones including silicified dolomitized and iron oxide minerals derived from remotely sensed imageryand other lithological and structural layers derived from 1 100000 geological map were preprocessed andprepared for mineral potential mapping Through employing all prepared exploratory evidences the favorability data integration methodologybased on using both fuzzy logic and neuro fuzzy approaches were carried out The results showed thatthe fuzzy logic approach alone could detect 74 percent of all 39 known Pb Zn mineralization while theneuro fuzzy approach outperformed the fuzzy logic approach by including 82 percent of all 39 knownmineralization prospects inside the high priority zones of final favorability map Keywords Data integration Fuzzy logic Neuro fuzzy Mississippi valley type MVT deposit Catchmentsampling
استاد راهنما :
حسن طباطبايي، نادر فتحيان پور
استاد داور :
محمدرضا ايران نژادي، رضا جعفري
