推荐系统算法在钦杭成矿带南段文地幅矿床预测中的应用
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摘要
推荐系统算法是大数据挖掘的重要技术之一。根据钦杭成矿带南段文地幅1∶5万地质矿产调查所获得的数据,研究选取中型银金矿床、小型银金矿床(点)、确证无银金矿床、未评价区域(针对银金矿床)、中型铅锌矿床、小型铅锌矿床(点)、确证无铅锌矿床、未评价区域(针对铅锌矿床)作为待预测的能动项,选取加里东期混合岩、燕山早期侵入岩、燕山晚期侵入岩、北东向断裂、北西向断裂以及Au、Ag、Pb、Zn元素作为因素项,运用基于内容的推荐系统算法,构建能动项-因素项的效用矩阵,计算已知矿床(点)与其他未评价区域之间的相似度,进而预测银金矿床和铅锌矿床潜在的找矿区域。实验结果表明,推荐系统算法能够较好地挖掘与成矿有关的信息,快速抓取出与某类矿床(点)相似的潜在成矿区域。对于银金矿床,相似度较高的区域主要分布在已知矿点周围以及北东向断裂的两侧,少量分布于叠加断裂附近。对于铅锌矿床,中型铅锌矿床的结果显示出较高的区分度,高值区基本涵盖了所有已知的铅锌矿点,小型铅锌矿床的结果更加集中。除已知矿点外,还有几处高值区可作为重点的找矿靶区。
Recommendation system algorithm is one of the important technologies of big data mining.In this study,we applied the content-based recommendation system algorithm to construct an utility matrix of the active and factor items,based on data obtained from the 1∶50000 geological and mineral resource survey at the Wendi district of southern Qinzhou-Hangzhou metallogenic belt,South China.The predicted active item included the middle-and small-sized(ore spot)electrum and verified non-electrum deposits;it also included the unevaluated electrum deposits,medium-and small-sized(ore spot)lead-zinc and verified non-lead-zinc(ore spot)deposits,and the unevaluated lead-zinc deposits.Caledonian migmatite,early Yanshanian and late Yanshanian intrusions,NE-and NW-trending faults,and Au,Ag,Pb and Zn elements were considered the factor item.The Euclidean distance similarity between known deposit(or ore spot)and other unevaluated areas was calculated and then used to predict the prospecting area of silver-gold and lead-zinc deposit.The results show that the recommendation system algorithm can effectively mine mineralization related information,and quickly extract the potential deposit areas based on its similarity to certain types of deposits(ore spot).For electrum deposit within the Wendi district,high similarity areas were mainly distribute around known ore deposits and on both sides of NE-trending faults,with a small portion distributed near the overlapped fracture.In comparison,for lead-zinc deposits,medium-sized deposit showed a high degree of discrimination.The high-value areas covered almost all known lead-zinc deposits while more concentrated distribution were found for small-sized deposits.In addition to known deposits,several high value areas can also be used as key prospecting targets.
Recommendation system algorithm is one of the important technologies of big data mining.In this study,we applied the content-based recommendation system algorithm to construct an utility matrix of the active and factor items,based on data obtained from the 1∶50000 geological and mineral resource survey at the Wendi district of southern Qinzhou-Hangzhou metallogenic belt,South China.The predicted active item included the middle-and small-sized(ore spot)electrum and verified non-electrum deposits;it also included the unevaluated electrum deposits,medium-and small-sized(ore spot)lead-zinc and verified non-lead-zinc(ore spot)deposits,and the unevaluated lead-zinc deposits.Caledonian migmatite,early Yanshanian and late Yanshanian intrusions,NE-and NW-trending faults,and Au,Ag,Pb and Zn elements were considered the factor item.The Euclidean distance similarity between known deposit(or ore spot)and other unevaluated areas was calculated and then used to predict the prospecting area of silver-gold and lead-zinc deposit.The results show that the recommendation system algorithm can effectively mine mineralization related information,and quickly extract the potential deposit areas based on its similarity to certain types of deposits(ore spot).For electrum deposit within the Wendi district,high similarity areas were mainly distribute around known ore deposits and on both sides of NE-trending faults,with a small portion distributed near the overlapped fracture.In comparison,for lead-zinc deposits,medium-sized deposit showed a high degree of discrimination.The high-value areas covered almost all known lead-zinc deposits while more concentrated distribution were found for small-sized deposits.In addition to known deposits,several high value areas can also be used as key prospecting targets.
引文
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[17]林振文,周永章,秦艳,等.钦杭带南段庞西垌-金山银金矿田控矿构造分析及找矿指示[J].矿床地质,2017,36(4):866-878.
[18]王祖伟,周永章.粤桂边境庞西垌-金山银金矿床成矿条件与形成机理[J].中山大学学报(自然科学版),2002,41(3):81-85.
[19]吕文超,陈庆,朱本铎,等.广东和寮铅锌矿稀土元素地球化学特征及其地质意义[J].稀土,2016(3):75-78.
[20]吕文超,周永章,张焱,等.基于重力异常对钦杭成矿带南段和寮地区成矿预测[J].矿物学报,2011(增刊):971-971.
[21]高乐.基于GIS对庞西垌地区文地幅成矿远景预测报告[D].广州:中山大学,2012.
[2]刘艳鹏,朱立新,周永章.卷积神经网络及其在矿床找矿预测中的应用研究:以安徽省兆吉口铅锌矿床为例[J].岩石学报,2018,34(11):3217-3224.
[3] CARRANZA E J M,LABORTE A G.Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra(Philippines)[J].Computers&Geosciences,2015,74:60-70.
[4] ZUO R G,XIONG Y H.Big data analytics of identifying geochemical anomalies supported by machine learning methods[J].Natural Resources Research,2017,27(1):1-9.
[5]周永章,王俊,左仁广,等.机器学习、深度学习及Python语言[J].岩石学报,2018,34(11):3173-3178.
[6] LIU X Y,ZHANG Q,ZHANG C L,et al.Global major events in Miocene and its significance:revelation from data mining[J].Chinese Science Bulletin,2017,62(15):1645-1654.
[7]周永章,张良均,张奥多,等.地球科学大数据挖掘与机器学习[M].广州:中山大学出版社,2018.
[8] RESNICK P,VARIAN H R.Recommender system[J].Communications of the ACM,1997,40(3):56-58.
[9]周永章,陈烁,张旗,等.大数据与数学地球科学研究进展:大数据与数学地球科学专题代序[J].岩石学报,2018,34(2):256-263.
[10] ADOMAVICIUS G,TUZHILIN A.Toward the next generation of recommender systems:a survey of the state-of-the-art and possible extensions[J].IEEE Transactions on Knowledge and Data Engineering,2005,17(6):734-749.
[11] ZENEBE A,NORCIO A F.Representation,similarity measures and aggregation methods using fuzzy sets for contentbased recommender systems[J].Fuzzy Sets and Systems,2009,160(1):76-94.
[12] KUMAR A,GUPTA S,SINGH S K,et al.Comparison of various metrics used in collaborative filtering for recommendation system[C]∥Proceedings of Eighth International Conference on Contemporary Computing(IC3),IEEE.2015,1:150-154.
[13]周永章,李兴远,郑义,等.钦杭结合带成矿地质背景及成矿规律[J].岩石学报,2017,33(3):667-681.
[14]周永章,张国桓,吴勇庆,等.广东庞西垌地区矿产远景调查报告(文地幅、石角幅、塘蓬幅、河唇幅,1∶50000)[R].北京:中国地质调查局,2016.
[15]吕文超,周永章,张焱,等.钦杭成矿带南段文地幅水系沉积物地球化学异常识别[J].中山大学学报(自然科学版),2012,51(5):107-112.
[16]吕文超,刘小雨,陈庆,等.广东庞西垌银金矿床稀土元素地球化学特征[J].金属矿山,2014,43(3):108-110.
[17]林振文,周永章,秦艳,等.钦杭带南段庞西垌-金山银金矿田控矿构造分析及找矿指示[J].矿床地质,2017,36(4):866-878.
[18]王祖伟,周永章.粤桂边境庞西垌-金山银金矿床成矿条件与形成机理[J].中山大学学报(自然科学版),2002,41(3):81-85.
[19]吕文超,陈庆,朱本铎,等.广东和寮铅锌矿稀土元素地球化学特征及其地质意义[J].稀土,2016(3):75-78.
[20]吕文超,周永章,张焱,等.基于重力异常对钦杭成矿带南段和寮地区成矿预测[J].矿物学报,2011(增刊):971-971.
[21]高乐.基于GIS对庞西垌地区文地幅成矿远景预测报告[D].广州:中山大学,2012.