Yanpeng Liu's research while affiliated with East China University of Technology and other places

... The PLS-DA is a supervised classification technique using labeled data compared to the traditional analysis, which achieves maximum separation between categories by rotating the PCA components to reinforce the separation between observation groups, which in turn identifies different categories of separated variables [2,[5][6][7][8][9][10]. Currently, the discriminatory models are constructed by such methods to study the chemical composition of minerals such as magnetite [4,11], scheelite [12], tourmaline [13], and chalcopyrite [8], and to discriminate deposits and ore types such as the uranium deposits [14], gold deposits [15], magmatic Ni-Cu sulfide deposits [16,17], sphalerite [18], and lead-zinc deposits [19], as well as the ore-prospecting prediction [20,21]. ...

... To establish another approach to geochemical mapping, Zuo et al. [26] applied deep learning and indicated that this method could deal with nonlinear and complex problems. In addition, various ML techniques have been used to detect the content as well as the potential of minerals and geochemical anomalies as the following works [18,25,[27][28][29][30][31][32][33][34]. ...