The Application Of The Method Of Principal Component Of The Trend In Geological Anomaly

As geophysical and geochemical anomalies is well-know for people an important basis of forecasting, and the concept and meaning of "geological anomaly," of in the 1960s developed continuously. In recent years, organized by Zhao Pengda academicians, the China University of Geosciences launched a series of quantitative prediction of the mineralization comprehensive study, and minerals (metal ores) has made better progress and greater good effect. In fact, "geological anomaly" than the geophysical and geochemical anomaly with a deeper meaning, it has a more broad prospects both the area of mineralization forecasting and resolving basic. As a geological anomaly in the composition, structure, sequence and the causes of the surrounding environment and a significant difference in the geological or geological body composition, this concept has been covering the deposit as "useful component of natural crust in the concentration broken" natural attributes. Accordingly, posed a geological anomaly identified mineralization predictable basis. It is also a special type of deposit, and new types of prerequisites, is the root of geophysical and geochemical anomalies. Deposit is the product of geological anomalies, geophysical and geochemical anomaly is the product of the physical nature and the nature of the chemical form of expression.The basic purpose of mineralization forecasting is to predict the location found no deposit and the deposit generally know that these basic type, size and grade. Depends not only on the unusual characteristics of various geological background and unusual material composition, but also on their occurrence and material composition. Their traditional practices are based on geological data and experienced statistical analysis of experts to study various types of geological data the relationship to achieve the forecast of mineral resources. With the large number of multi-sources of information and data (such as geology, remote sensing, earthquakes, MT, high-precision gravity and magnetic, IP, geophysical, geochemical, etc.) , the accumulation and mineralization forecasting the continuous development of their own disciplines (such as geological anomaly The theory of the establishment, from qualitative to quantitative prediction of the forecast changes, etc.), in the past , the ways of manual handling is unthinkable and not impossible. And because of the data is a typical multi-source spatial data, their different dimension, diversity, the traditional computer database technology for such a space of multi-source data management and analysis is also powerless. Therefore, how to adapt to changes in the situation, make full use of these wealth of information quickly and effectively to the economic forecast mineralization, geological workers are facing a major problem.With the development of human technology and Earth exploration of the technology is not perfect, mankind has a power beyond their abilities, which is computer technology. on the platform of computer technology , human can identify renewedly the mystery of nature,and re-examine the Earth. China's mineral resources shortage has become a constraint on economic sustainable development one of the major bottlenecks, the application of statistical techniques to study the geological context of mineralization, geological survey and mineral resources prospecting and evaluation of the technology is an effective way.During empirical research on geochemical data, in order to more fully and accurately reflect the distribution of mineral elements of the characteristics of the development law, people tend to consider its relations with a number of indicators, which in a multicultural statistics also known as variable . The result is as follows: On the one hand, in order to avoid the omission of important information people consider the possible number of instructions, on the other considering the increasing indicators will add to the complexity of the problem, and due to the indicators are refection of the same thing .It is inevitably led to the large number of overlapping and duplication of such information sometimes abliterate true characteristics and the inherent law,Based on the above issues, people want to quantitative study of the variables involved the less, and more message. The principal component analysis and study on the research that how to change a few of the original composition linear variable to explain the vast majority of the original information of a multiple statistical methods use principal component analysis to reduce the workload in a certain area to be more obvious characteristics of elements, element Distribution of more focused, so this is mainly used this method.Complexity of the problem based on the geological, most of the geological variables are random variables, most of them belongs to the relationship between the correlation that the mathematical analysis can not be used in function to that. For example, in a porphyry copper deposit, the elements of the elements Cu Ag, Pb, Zn, and so there is a dependent relationship, but there is no certainty the function can only be a correlation relationship. If according to a number of pieces of laboratory specimens to identify the correlation between the value of the mathematical expression, and to measure the dependence of variables, the study of this deposit has great value. Mathematical statistics in the regression analysis is to study such a strong relationship between the mathematical tools. It is a number of variables of observational data as the starting point, through this data structure analysis, the search for variable-dependent relationship exists between. Can be summed up that regression analysis is to examine statistical correlation between variables among a number of statistical analysis. So this is also the first to take mathematics and geology the most widely used method - the method of fitting the trend, and on the basis of this improvement.Using principal component method of delineation of the trend of geological anomalies problem, for observation of the data elements involved in the excessive, the phenomenon of redundancy, to take a principal component analysis of the methods of these interrelated variables to "transform", with Smaller, non-overlapping information of the new variables to reflect the original variables most of the information provided, through a smaller number of new variables to solve the problem of the purpose. In examining the relations between the variables commonly used method is the linear regression, in multivariate analysis, often using least-squares fitting multiple linear regression model. However, when the argument between the approximate linear relationship, that is, multicollinearity, the establishment of direct least squares multiple linear regression equation since some of the variable factor of instability. Also due to multiple linear regression of the significant test method can be used for trend surface analysis, so we wanted to use trend surface analysis to solve the problem. The trend of the commonly used a special function - polynomial functions, the trend is the selection of the number of the problems we face, in order to partially delineated abnormal, excessive fitting of the residual value of smaller, which may be part of meaningful The abnormal trend to return to, in such circumstances trend of the number should not be too high; polynomial the number too low, the extent of not fitting. In geological modeling, to fit the data points are often uneven, in order to more accurately describe the characteristics of observation points, we hope to have the greatest possible number of points around the adoption of the plane, so here is used in subparagraph To fit polynomial, which is kind of interpolation, has been a continuous surface, and B-spline surfaces can be given the interpolation surface is very smoothly, so once again we apply B-spline interpolation. In multivariate analysis, to be constructed in the surface and can be taken to the square of residuals and the smallest way, which is the least-squares fitting surface, these kind of fitting, can change the parameters with the smooth surface. And then calculated the new data fit with the trend of the data margin, the difference in the Matrix, find out in a given threshold, the abnormal fluctuations through the use of matlab graphics toolbox, to map out 3-D graphics, in the plane Graphics directly to determine anomalies. Finally, the actual data in a certain area to test the feasibility of the method.