شماره مدرك
10843
شماره راهنما
9985
پديد آورنده
نجمي، مجيد
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
سال دفاع
1394
صفحه شمار
د، 90ص.: مصور
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 ورود اطلاعات
1396/10/06
كتابنامه
كتابنامه
رشته تحصيلي
معدن
دانشكده
مهندسي معدن
كد ايرانداك
ID9985
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