CN106250676A - Element geochemistry survey data method for optimizing based on information gain-ratio - Google Patents
Element geochemistry survey data method for optimizing based on information gain-ratio Download PDFInfo
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Abstract
The present invention is directed to existing geochemistry data analysis and subjective bias problem easily occur, it is proposed that one can accurately analytical geochemistry data based on information gain-ratio element geochemistry survey data method for optimizing: obtain geochemistry data in enumeration district；Grid matrix is calculated accordingly at enumeration district structure white space grid matrix drafting；Data are screened, rejects wrong data, by remaining data by interpolated projections to calculating in grid matrix；By known orefield coordinate projection to calculating in grid matrix, in correspondence knows the calculating grid in orefield, mineral products grade employing respective markers is represented, calculate in grid in corresponding unknown orefield and fill in expression unknown mark；Randomly select some containing ore deposit grid with some unknown grids are as training data；Calculate each element and corresponding ore-bearing potential information gain-ratio, be selected to ore deposit advantageous elements；Become ore deposit advantageous elements that enumeration district (ED) geochemistry data is carried out preferably.Geochemistry data can be analyzed by the present invention accurately.
Description
Technical field
The present invention relates to a kind of element geochemistry survey data method for optimizing based on information gain-ratio.
Background technology
The analysis of geochemical data is to a link very important during mineral exploration, existing exploration
It is that the sediments/soil/ground vapour sample data after testing projects to flat square seat that geochemistry data analyzes method
In mark system, making isogram or using threshold as the Spring layer of boundary delineation single element, the analysis to data mainly depends on
By virtue of experience it is accomplished manually by worker.This data analysing method is the highest to survey personnel's skill requirement, and this
Kind data analysing method can not form the method for system and exchange and teach, and causes each worker to pass through conventional
Experience carries out analysis and the judgement of subjectivity.Owing to different operating personnel's knowledge experience level is different, this dependence subjective analysis and
There is difference when the mineral products of areal are judged by different staff in the data analysing method judged.And in choosing
Select Nei Cheng ore deposit, region advantageous elements evaluation criterion disunity, directly affects exploration and evaluation of mineral resources effect, therefore need badly
A kind of quantization method for optimizing for exploration geochemistry data.
Summary of the invention
For the problems referred to above, the present invention provides the element earth based on information gain-ratio of a kind of accurate judgement metallogenic factors
Chemistry survey data method for optimizing.
For reaching above-mentioned purpose, present invention element geochemistry based on information gain-ratio survey data method for optimizing includes
Following steps:
Step 1: selected enumeration district, obtains the geochemistry data in enumeration district；
Step 2: build blank space lattice matrix at enumeration district；According to described space lattice matrix draw calculation grid
Matrix；
Step 3: screen the data obtained in step 1, rejects the data of mistake；By remaining data by inserting
Value projects to, in the calculating grid matrix built in step 2, form element property grid matrix
Step 4: by the element property grid matrix in known orefield coordinate projection to step 3, by known ore deposit
The mineral products grade in the place of production is divided into some ranks, fills in expression mineral products grade rank calculating of corresponding known orefield in grid
Labelling, fills in expression unknown mark in the calculating grid in corresponding unknown orefield, forms mineral products grade grid matrix；
Step 5: if randomly select from the mineral products grade grid matrix of step 4 some corresponding orefields containing ore deposit grid and
The unknown grid in dry corresponding unknown orefield is as training data；
Step 6: calculate the information gain-ratio of each element and corresponding ore-bearing potential, chooses the element that information gain-ratio is front 30%
As becoming ore deposit advantageous elements；
Step 7: enumeration district (ED) geochemistry data is carried out preferably by the one-tenth ore deposit advantageous elements according to choosing in step 6.
Further, the method obtaining geochemistry data in described step 1 is as follows: select 1:20 ten thousand-1:5 ten thousand scale
Arrange geochemistry survey grid at enumeration district, gather the sediments in enumeration district according to described chemistry survey grid or soil is geochemical
Imitate product, detects described sediments or pedogeochemistry sample, obtains geochemistry data.
Further, before or after described step 3, data conversion step is also included；Described data conversion step will be complete
Portion's data are converted into the data of Normal Distribution by data conversion.
Further, the sizing grid of the blank space lattice matrix built in described step 2 be 10m*10m～
1000m*1000m。
Further, the ratio containing ore deposit grid cell with unknown grid cell in described step 5 is 1:5～5:1, described
It is 1:1 containing ore deposit grid cell and the unknown preferred ratio of grid cell.
Further, the conversion of described data uses Box-Cox conversion, and described Box-Cox alternative approach is as follows: YiFor original
I-th data in data, the i-th data after conversion are Yi(λ)；When λ is more than 0 or is less than 0, describedWhen λ is equal to 0, described Yi(λ)=ln (Yi)；Wherein, described λ is the constant making likelihood function maximum.
Further, the computational methods of the information gain-ratio in described step 6 are as follows:Wherein, institute
StateDescribedDescribedIn above-mentioned formula, | D | represents the tuple number in data set D, and m represents attribute A
Value number, DiRepresenting the tuple-set that the i-th value of attribute A is corresponding, v is the value number representing generic attribute, pjRepresent
Tuple is the probability of j class.
Further, also including into ore deposit grade and judge step after step 7, it is as follows that described one-tenth ore deposit grade judges that step includes
Operation:
1, it is extracted into the data of ore deposit advantageous elements, is depicted as the isogram of ore deposit advantageous elements；
2, judge Cheng Kuang position according to the crossing instances of the isogram of each one-tenth ore deposit favorable factor and become ore deposit grade.
Present invention element geochemistry based on information gain-ratio survey data method for optimizing, uses and calculates information gain-ratio
Method judge the impact on becoming ore deposit grade of each element, it is possible to judging of simple, intuitive.The present invention is based on information gain-ratio
Element geochemistry survey data method for optimizing define computational methods and the data processing method of set of system, it is simple to work
The exchange of personnel and teaching, can improve the efficiency of geochemical to a certain extent.The present invention is based on information gain-ratio
Element geochemistry survey data method for optimizing, by the COMPREHENSIVE CALCULATING to each element, filter out into ore deposit favorable factor, entirely
Face considers the impact of each element, and therefore, effectiveness is high, the suitability is strong, accuracy good.By unit based on information gain-ratio
Element geochemistry data method for optimizing, provides succinct directly one-tenth ore deposit advantageous elements for geochemistry mineral exploration the most square
Method, reduces the dependence to staff personal experience and the Different Individual subjective consciousness shadow to becoming ore deposit advantageous elements evaluation to bring
Ringing, that accomplishes objective reality evaluates each element one-tenth ore deposit profitability in reconnoitring district, carries out the preferred of Exploration guide element.Rely on
Computer generation for artificial selection reconnoitre district's geochemistry data preferably with evaluation, strengthen evaluate objectivity, improve data
The efficiency processed and quality, practical, accuracy is high, it is achieved convenient, processes quickly.
Accompanying drawing explanation
Fig. 1 is the operating procedure of present invention geochemical based on information gain-ratio data method for optimizing；
Fig. 2 be present invention geochemical based on information gain-ratio data method for optimizing embodiment 1 in be filled with
Mineral products grade level flag and the calculating grid matrix of unknown mark；
Fig. 3 is the partial enlarged drawing of Fig. 2；
Fig. 4 is each in the embodiment 1 of present invention geochemical based on information gain-ratio data method for optimizing
The sequence of the information gain-ratio of element.
Fig. 5 is the distribution mode calculating grid matrix.
Detailed description of the invention
Below in conjunction with Figure of description, the present invention will be further described.
Embodiment 1
As Figure 1-4, the operation of the geochemical data method for optimizing based on information gain-ratio of the present embodiment
Process is as follows:
1, collect goldfield, Gansu Province 1:50000 sediments geochemistry data, comprise altogether 18 kinds of element: Ag,
As, Au, Bi, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Rb, Sb, Sn, Ti, W, Zn, cover 264 sq-kms and reconnoitre district's area.
2, build blank space lattice matrix according to 100m*100m, cover and reconnoitre district's spatial dimension；According to space lattice
Matrix draw calculation grid matrix M.Calculate grid matrix as shown in Figure 5.
3, the geochemistry data obtained in inspection 1, rejects the data of mistake, remains geochemistry data to be calculated, logical
Cross each unit prime number according to carrying out space Kriging regression, project to geochemistry data to be calculated calculate in grid matrix,
Forming element property grid matrix, in element property grid matrix, each cell is 18 dimension attributes comprising every kind of element property
Vector；Use mi,jRepresent the cell in element property grid matrix；
mi,j=| Agi,j Asi,j Aui,j Bii,j … Sni,j Tii,j Wi,j Zni,j|；
4, by the element property grid matrix in known orefield coordinate projection to 3, according to known orefield containing ore deposit
Grade height, fills in 3,2,1 in corresponding element property grid, fills in 0 in element property grid corresponding for unknown orefield,
And this value is attached to the vectorial m of grid matrixi,jIn, as the 19th attribute, so, element property grid matrix is the formation of
Mineral products grade grid matrix.Unknown orefield refers to whether this position is contained mineral products and be in the place of unknown state.
5, as shown in Figures 2 and 3, randomly select from the mineral products grade grid matrix of 4 60 corresponding orefields containing ore deposit
The unknown grid cell in grid cell and 60 corresponding unknown orefields is as training data；In the calculation, unknown orefield regards
For without mineral products.
6, calculate the information gain-ratio of each element and corresponding ore-bearing potential, calculate the information gain of each element and corresponding ore-bearing potential
The method of rate is as follows: the computational methods of the information gain-ratio in described step 6 are as follows:Wherein, describedDescribedDescribedIn above-mentioned formula, | D | represents the tuple number in data set D, and m represents attribute A
Value number, DiRepresenting the tuple-set that the i-th value of attribute A is corresponding, v is the value number representing generic attribute, pjRepresent
Tuple is the probability of j class.Calculate complete each element to sort as shown in Figure 4 with the information gain-ratio of corresponding ore-bearing potential.Choose letter
Breath ratio of profit increase front 30% element as becoming ore deposit advantageous elements.
7, according to information gain-ratio ranking results, select front 30% for becoming ore deposit advantageous elements, preferred in 18 kinds of elements
Six kinds of elements of W, Au, Sb, Sn, Ag, Hg are as top-priority one-tenth ore deposit advantageous elements in the work of this regional exploration.
8, according to the data of six kinds of elements in 7, the isogram of these six kinds of elements is drawn, in drawing process, if
Intersecting occurs in the Spring layer of two or more element, then this intersection region is possible to be minerogenetic province, in the zone of intersection
The one-tenth ore deposit advantageous elements occurred is the most, and the one-tenth ore deposit probability of this position is the highest, and, containing of the one-tenth ore deposit advantageous elements in this position
Measuring the highest, this position occurs that the probability of high-grade mineral products is the highest.
In the above-mentioned methods, in order to further enhance the precision of calculating, data can calculated to calculating in grid matrix
Carrying out data conversion process before projection or after projection to data, the conversion of described data uses Box-Cox conversion, described Box-Cox
Alternative approach is as follows: YiFor the i-th data in initial data, the i-th data after conversion are Yi(λ)；When λ is more than 0 or little
In 0 time, describedWhen λ is equal to 0, described Yi(λ)=ln (Yi)；Wherein, described λ is to make likelihood function
Big constant.
The present embodiment element geochemistry based on information gain-ratio survey data method for optimizing, uses and calculates information gain
The method of rate judges the impact on becoming ore deposit grade of each element, it is possible to judging of simple, intuitive.The present embodiment increases based on information
The element geochemistry survey data method for optimizing of benefit rate defines computational methods and the data processing method of set of system, it is simple to
The exchange of staff and teaching, can improve the efficiency of geochemical to a certain extent.The present embodiment is based on information
The element geochemistry survey data method for optimizing of ratio of profit increase, by the COMPREHENSIVE CALCULATING to each element, filters out into ore deposit favourable
Factor, considers the impact of each element comprehensively, and therefore, effectiveness is high, the suitability is strong, accuracy good.
Above, only presently preferred embodiments of the present invention, but protection scope of the present invention is not limited thereto, any it is familiar with basis
Those skilled in the art in the technical scope that the invention discloses, the change that can readily occur in or replacement, all should contain
Within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain that claim is defined.
Claims (8)
1. an element geochemistry survey data method for optimizing based on information gain-ratio, it is characterised in that: described method bag
Include following steps:
Step 1: selected enumeration district, obtains the geochemistry data in enumeration district；
Step 2: build blank space lattice matrix at enumeration district；According to described space lattice matrix draw calculation grid square
Battle array；
Step 3: screen the data obtained in step 1, rejects the data of mistake；Remaining data are passed through interpolated projections
In the calculating grid matrix built in step 2, form element property grid matrix
Step 4: by the element property grid matrix in known orefield coordinate projection to step 3, by known orefield
Mineral products grade be divided into some ranks, calculating in grid to fill in and represent the mark of mineral products grade rank in corresponding known orefield
Note, fills in expression unknown mark in the calculating grid in corresponding unknown orefield, forms mineral products grade grid matrix；
Step 5: randomly select from the mineral products grade grid matrix of step 4 some corresponding orefields containing ore deposit grid and some right
Answer the unknown grid in unknown orefield as training data；
Step 6: calculate the information gain-ratio of each element and corresponding ore-bearing potential, chooses the element conduct that information gain-ratio is front 30%
Become ore deposit advantageous elements；
Step 7: enumeration district (ED) geochemistry data is carried out preferably by the one-tenth ore deposit advantageous elements according to choosing in step 6.
2. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 1, it is characterised in that:
The method obtaining geochemistry data in described step 1 is as follows: select 1:20 ten thousand-1:5 ten thousand scale to arrange the earth at enumeration district
Chemistry survey grid, gathers the sediments in enumeration district or pedogeochemistry sample, to described water according to described chemistry survey grid
It is deposit or pedogeochemistry sample detects, obtain geochemistry data.
3. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 1, it is characterised in that:
Data conversion step was also included before or after described step 3；Total data is become by described data conversion step by data
Change the data being converted into Normal Distribution.
4. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 1, it is characterised in that:
The sizing grid of the blank space lattice matrix built in described step 2 is 10m*10m～1000m*1000m.
5. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 1, it is characterised in that:
The ratio containing ore deposit grid cell with unknown grid cell in described step 5 is 1:5～5:1, described containing ore deposit grid cell with not
Know that the preferred ratio of grid cell is 1:1.
6. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 3, it is characterised in that:
The conversion of described data uses Box-Cox conversion, and described Box-Cox alternative approach is as follows: YiFor the i-th number in initial data
According to, the i-th data after conversion are Yi(λ)；When λ is more than 0 or is less than 0, describedWhen λ is equal to 0, institute
State Yi(λ)=ln (Yi)；Wherein, described λ is the constant making likelihood function maximum.
7. element geochemistry survey data method for optimizing based on information gain-ratio as claimed in claim 1, it is characterised in that:
The computational methods of the information gain-ratio in described step 6 are as follows:Wherein, describedDescribedDescribedIn above-mentioned formula, | D | represents the tuple number in data set D, and m represents attribute A
Value number, DiRepresenting the tuple-set that the i-th value of attribute A is corresponding, v is the value number representing generic attribute, pjRepresent
Tuple is the probability of j class.
8. the method for optimizing of element geochemistry survey data based on information gain-ratio as claimed in claim 1, its feature exists
In: also include into ore deposit grade after step 7 and judge that step, described one-tenth ore deposit grade judge that step includes following operation:
1, it is extracted into the data of ore deposit advantageous elements, is depicted as the isogram of ore deposit advantageous elements；
2, judge Cheng Kuang position according to the crossing instances of the isogram of each one-tenth ore deposit favorable factor and become ore deposit grade.
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Cited By (3)
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| CN113326784A (en) * | 2021-06-01 | 2021-08-31 | 中国石油天然气集团有限公司 | Mineral resource detection method, system and equipment |
| CN115759815A (en) * | 2022-11-03 | 2023-03-07 | 中国科学院广州地球化学研究所 | Exploration method for judging porphyry copper ore type by using crustal maturity index |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106908855A (en) * | 2017-02-23 | 2017-06-30 | 中国地质大学（武汉） | A kind of method that geochemistry element combinations are selected based on GIS spatial analysis |
| CN106908855B (en) * | 2017-02-23 | 2019-08-30 | 中国地质大学（武汉） | A method of geochemistry element combinations are selected based on GIS spatial analysis |
| CN113326784A (en) * | 2021-06-01 | 2021-08-31 | 中国石油天然气集团有限公司 | Mineral resource detection method, system and equipment |
| CN115759815A (en) * | 2022-11-03 | 2023-03-07 | 中国科学院广州地球化学研究所 | Exploration method for judging porphyry copper ore type by using crustal maturity index |
| CN115759815B (en) * | 2022-11-03 | 2023-11-03 | 中国科学院广州地球化学研究所 | Investigation method for judging zebra copper ore type by using crust maturity index |
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