本文關(guān)鍵詞： 投影尋蹤分類 實(shí)數(shù)編碼遺傳算法 化探數(shù)據(jù)處理 異常識(shí)別提取 云南個(gè)舊　出處：《吉林大學(xué)學(xué)報(bào)(地球科學(xué)版)》2017年04期 　論文類型：期刊論文

【摘要】：為了進(jìn)行地球化學(xué)異常的識(shí)別與提取,針對(duì)化探數(shù)據(jù)的特點(diǎn),本文提出了一種將高維降維技術(shù)——投影尋蹤分類(PPC)模型與實(shí)數(shù)編碼遺傳算法(RCGA)相結(jié)合的計(jì)算方法,分析了運(yùn)用RCGA-PPC模型進(jìn)行化探異常識(shí)別與提取的關(guān)鍵技術(shù)問(wèn)題,并在MATLAB環(huán)境下開發(fā)了該方法的軟件應(yīng)用模塊。以云南個(gè)舊地區(qū)水系沉積物地球化學(xué)數(shù)據(jù)為例,選取區(qū)域內(nèi)Sn、Cu、Pb、Zn、As、Cd等主要成礦元素及與成礦關(guān)系密切的9種元素作為計(jì)算變量,利用RCGA-PPC模型對(duì)其進(jìn)行處理和異常識(shí)別。研究表明:RCGAPPC模型中最佳投影值較高的地區(qū)與該區(qū)域?qū)嶋H礦床(點(diǎn))吻合情況較好。該模型對(duì)化探異常的識(shí)別能力較強(qiáng),是一種有效的化探多元素綜合異常識(shí)別與提取方法。
[Abstract]:In order to identify and extract geochemical anomalies and in view of the characteristics of geochemical data, this paper presents a calculation method which combines the high-dimensional reduced-dimension technique, projection pursuit classification (PPC) model, with real coded genetic algorithm (RCGA). This paper analyzes the key technical problems of geochemical anomaly identification and extraction using RCGA-PPC model, and develops the software application module of this method under the MATLAB environment. Taking the geochemical data of water system in Gejiu area of Yunnan Province as an example, In this paper, the main metallogenic elements, such as PbPbPbPbPbPbPbPbPbPbPbPbPb, and 9 elements closely related to mineralization, are selected as calculation variables in the region. The RCGA-PPC model is used to deal with and identify anomalies. The results show that the best projection value of the WRCGAPPC model is in good agreement with the actual ore deposits (points) in the region, and the model has a strong ability to identify geochemical anomalies. It is an effective method to identify and extract multi-element anomaly in geochemical exploration.
【作者單位】： 中山大學(xué)地球科學(xué)與工程學(xué)院;中山大學(xué)廣東省地質(zhì)過(guò)程與礦產(chǎn)資源探查重點(diǎn)實(shí)驗(yàn)室;中國(guó)地質(zhì)大學(xué)(武漢)資源學(xué)院;中國(guó)地質(zhì)大學(xué)地質(zhì)過(guò)程與礦產(chǎn)資源國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(41502310) 廣東省自然科學(xué)基金博士啟動(dòng)項(xiàng)目(2015A030310246)~~
【分類號(hào)】：P632

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

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本文編號(hào)：1553711