CN107392475A - Coal resources mining right valuation methods known to one attribute intensity function - Google Patents
Coal resources mining right valuation methods known to one attribute intensity function Download PDFInfo
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Abstract
The invention discloses coal resources mining right valuation methods known to an attribute intensity function, including step：First, determine the ATTRIBUTE INDEX of coal resources mining right to be assessed and determine the evaluation of estimate of ATTRIBUTE INDEX；2nd, case coal resources mining right is stored；3rd, attribute intensity function coefficient is obtained；4th, the price of coal resources mining right to be assessed is predicted；5th, the estimate of the variance of coal resources mining right forecast price to be assessed is determined；6th, quasi-optimal case coal resources mining right collection is built；7th, optimal case coal resources mining right collection is determined；8th, coal resources value of mining property to be assessed is assessed.The present invention determines the evaluation of estimate of each ATTRIBUTE INDEX by case coal resources mining right, the price of coal resources mining right to be assessed is predicted using the price of adjustment case coal resources mining right, set optimal case coal resources mining right collection Criterion of Selecting and determine similarity vector, obtain coal resources value of mining property to be assessed.
Description
Technical field
The invention belongs to coal resources mining right valuation technique field, and in particular to coal known to an attribute intensity function
Charcoal resource mining right valuation methods.
Background technology
Coal resources mining right refers to the Exploitation license obtained in accordance with the law as defined in scope, the resource that cuts coal and obtains
Obtain the right for the product that cuts coal.During coal resource integration, the coal resources mining right valuation methods based on case
It is a kind of effective ways for best embodying mining right market value.Existing case coal resources mining right quotes fuzzy set patch
The concept of recency, the case selection of Market Comparison Approach in appraisal of real estate is studied, establish degree of membership assignment expert
Appraisal procedure, this method be case decision thought in Concerning Property Evaluation of Mineral Resources field with laying a good foundation.But coal
Charcoal Resource assetses and coal resources mining right in the property of value, influence factor etc. there is basic difference, because coal provides
Source mining right is in coal resources reserves, natural endowment condition, ature of coal, mining conditions, geographical position, conditions of transportation and degree of prospecting
Etc. attribute and real estate attribute basic difference be present, estimate both at home and abroad on the coal resources mining right based on case at present
Valency method is excessively simple, does not solve case selection criterion and key issues of similarity model is established, this method can not be direct
Apply to evaluate coal resources mining right.Therefore, coal resources mining right known to an attribute intensity function is nowadays lacked
Valuation methods, by case decision-making and Modern statistics theory and method, to case coal resources mining right Criterion of Selecting and phase
Method for solving is provided like degree, the coal resources mining right appraisal flow based on case is established, for coal resources reasonable disposition and adopts
Mineral property right exchange construction provides the support in theoretical and method.
The content of the invention
In view of the above-mentioned deficiencies in the prior art, the technical problem to be solved by the present invention is that provide an attribute intensity
Coal resources mining right valuation methods known to function, the evaluation of each ATTRIBUTE INDEX is determined by case coal resources mining right
Value, the price of coal resources mining right to be assessed is predicted using adjustment case coal resources mining right, sets optimal case
Example coal resources mining right collection Criterion of Selecting simultaneously determines similarity vector, obtains coal resources value of mining property to be assessed, is coal
The charcoal rational distribution of resources and the construction of mining right trade market provide the support in theoretical and method.
In order to solve the above technical problems, the technical solution adopted by the present invention is：Coal known to one attribute intensity function
Resource mining right valuation methods, it is characterised in that this method comprises the following steps：
Step 1: determine the ATTRIBUTE INDEX of coal resources mining right to be assessed and determine the evaluation of estimate of ATTRIBUTE INDEX：First,
Give coal resources mining right to be assessed ATTRIBUTE INDEX, the ATTRIBUTE INDEX include coal seam thickness, regularity of coal seam, ash content,
Caloric value, mining depth, coal price and transportation range, wherein, using detector for measuring depth of coal bed measure the coal seam thickness and
The mining depth, regular coal seam thickness statistic is measured using detector for measuring depth of coal bed and obtains the regularity of coal seam, is used
Coal ash measures the release of 1kg raw coal combustions with raw coal quality than obtaining the ash content using calorimeter after weighing instrument measurement burning
Heat obtains the caloric value, manually gives the coal price and stores in memory, obtaining coal using navigator rises
Beginning, the distance between position obtained the transportation range；Then, it is determined that the ATTRIBUTE INDEX of coal resources mining right to be assessed is commented
It is worth ysjAnd ysj≤ η, wherein, η is the upper limit threshold of ATTRIBUTE INDEX, and j is ATTRIBUTE INDEX numbering and j is non-negative whole not less than 3
Number, i.e. j=1,2 ..., n, ysjValue is determined using expert point rating method；
Step 2: storage case coal resources mining right：Provided the coal resources mining right merchandised as case coal
Source mining right, the ATTRIBUTE INDEX of the case coal resources mining right is consistent with coal resources mining right ATTRIBUTE INDEX to be assessed,
M case coal resources mining right is stored in memory, and m is positive integer and m is more than ATTRIBUTE INDEX numbering j；
Step 3: obtain attribute intensity function coefficient：According to attribute intensity functionComputer uses
Regression analysis calculates regression coefficientWith the attribute coefficients of j-th of ATTRIBUTE INDEXWherein, ycjProvided for c-th of case coal
The evaluation of estimate of j-th of ATTRIBUTE INDEX of source mining right, c is positive integer and c is not more than m；
Step 4: predict the price of coal resources mining right to be assessed：First, according to formula
The Tuning function Δ P of computer computation attribute indexc；Then, according to formulaComputer calculates
To the forecast price P of coal resources mining right to be assessed after c-th of case coal resources mining right adjustmentSc, wherein, PCcFor c
Transaction value before individual case coal resources mining right adjustment；
Step 5: determine the estimate of the variance of coal resources mining right forecast price to be assessed：According to formulaComputer calculates c-th of case coal
To the forecast price P of coal resources mining right to be assessed after the adjustment of resource mining rightScVariance estimation values sigma2(PSc), wherein,
σ2(PCc) for the variance of c-th case coal resources mining right transaction value,For the attribute coefficients and k of k-th of ATTRIBUTE INDEX
No more than n,For the attribute coefficients of j-th of ATTRIBUTE INDEXWith the attribute coefficients of k-th of ATTRIBUTE INDEXAssociation side
Difference,For the attribute coefficients of c-th of case coal resources mining right transaction value and j-th of ATTRIBUTE INDEXAssociation
Variance；
Step 6: structure quasi-optimal case coal resources mining right collection：First, computer is individual to the m calculated in step 5
The estimate of the variance of the forecast price of coal resources mining right to be assessed is carried out after the adjustment of case coal resources mining right from
It is small to be sorted to big；Then, computer sets the threshold xi of the estimate of variance in memory, according to formula σ2(PSc)≤ξ, meter
Calculate mechanism and build quasi-optimal case coal resources mining right collection Cb；
Step 7: determining optimal case coal resources mining right collection, process is as follows：
Step 701, the optimal case coal resources mining right subset of structure：Computer is dug up mine in quasi-optimal case coal resources
Power collection CbThe middle case coal resources mining right for choosing varying number forms optimal case coal resources mining right subsetIts
In,M is quasi-optimal case coal resources mining right collection CbThe number of middle case coal resources mining right
Amount, i are the quantity for the case coal resources mining right chosen, and l is optimal case corresponding to the case coal resources mining right chosen
Example coal resources mining right subsetNumbering；
Step 702, according to formulaComputer calculates optimal case coal resources and adopted
Mineral rights subsetIn minimum variance between each forecast priceAnd optimal case coal resources mining right collection is determined, its
In, PlFor the set of forecast price corresponding to the case coal resources mining right of selection, D (Pl) adopted for optimal case coal resources
Mineral rights subsetIn between each forecast price variance-covariance matrix and For quasi-optimal case coal resources mining right collection CbIn the 1st case coal resources mining right forecast price,It is defined most
Excellent case coal resources mining right collection CbIn the 2nd case coal resources mining right forecast price,For quasi-optimal case coal
Charcoal resource mining right collection CbThe forecast price of middle m-th case coal resources mining right, SlFor optimal case coal resources mining right
SubsetIn each case coal resources mining right composition similarity vector, SfFor f-th of Similarity value in similarity vector；
Step 8: assess coal resources value of mining property to be assessed：According to formulaComputer is calculated and treated
Coal resources value of mining property V is assessed, and the estimated value of coal resources mining right to be assessed is shown by display, wherein, Z
For the coal resources reserves of coal resources mining right to be assessed.
Coal resources mining right valuation methods known to an above-mentioned attribute intensity function, it is characterised in that：The η takes
It is worth for 10；The evaluation of estimate of the coal seam thickness is ys1AndWherein, thi is actual coal seam
Thickness；The evaluation of estimate of regularity of coal seam be ys2 andWherein, sta is that regular coal seam accounts for entirely
The mass percent of well coal amount；The evaluation of estimate of ash content be ys3 andWherein, AdFired for coal
Dust burdening after burning；The evaluation of estimate of caloric value is ys4AndWherein, Cal is
Heating value of coal；The evaluation of estimate of mining depth be ys5 andWherein, dep is actual
Mining depth；The evaluation of estimate of coal price be ys6 andWherein, pri is
Manually given coal price per ton；The evaluation of estimate of transportation range be ys7 and
Wherein, dis is actual shipment distance.
Coal resources mining right valuation methods known to an above-mentioned attribute intensity function, it is characterised in that：The c
The variances sigma of individual case coal resources mining right transaction value2(PCc), the attribute coefficients of j-th ATTRIBUTE INDEXWith k-th of attribute
The attribute coefficients of indexCovarianceC-th of case coal resources mining right transaction value and j-th of attribute
The attribute coefficients of indexCovarianceCalculated and obtained using the LS Returns Law and Statistics Method.
Coal resources mining right valuation methods known to an above-mentioned attribute intensity function, it is characterised in that：The side
The threshold xi value of the estimate of difference meets：0.030≤ξ≤0.035.
The present invention has advantages below compared with prior art：
1st, the present invention obtains the case coal consistent with coal resources mining right ATTRIBUTE INDEX to be assessed by regression analysis
The attribute intensity function that charcoal resource mining right determines, coal resources mining right ATTRIBUTE INDEX to be assessed is determined using expert point rating method
Value, coal resources mining right ATTRIBUTE INDEX to be assessed determines reliable effective.
2nd, the present invention enters by using adjustment case coal resources mining right to the price of coal resources mining right to be assessed
Row prediction, further obtains reliable forecast price, that is, first passes through attribute intensity function to each case coal resources mining right
Price be adjusted to predict the adjusted value of coal resources mining right to be assessed, then with case coal resources mining right
Similarity is that weight is weighted to forecast price, draws the final estimated price of coal resources mining right to be assessed, is avoided straight
Connecing causes larger error with attribute intensity function.
3rd, the inventive method step is simple, strict logic, passes through the case coal resources mining right arrangement group of varying number
Optimal case coal resources mining right subset is combined into, it is each to calculate its for each optimal case coal resources mining right subset
Minimum variance between forecast price, optimal case coal resources mining right collection is finally determined, built for mining right trade market
Support in theoretical and method is provided, is easy to promote the use of.
In summary, the present invention determines the evaluation of estimate of each ATTRIBUTE INDEX by case coal resources mining right, using tune
Whole case coal resources mining right is predicted to the price of coal resources mining right to be assessed, sets optimal case coal resources
Mining right collection Criterion of Selecting simultaneously determines similarity vector, obtains coal resources value of mining property to be assessed, for mining right transaction city
The support provided in theoretical and method is built in field, is easy to promote the use of.
Below by drawings and examples, technical scheme is described in further detail.
Brief description of the drawings
Fig. 1 is the schematic block circuit diagram that the coal resources mining right that the present invention uses evaluates equipment.
Fig. 2 is the method flow block diagram of coal resources mining right valuation methods of the present invention.
Description of reference numerals:
1-detector for measuring depth of coal bed；2-calorimeter；
3-weighing instrument；4-navigator；
5-computer；6-display screen；
7-memory.
Embodiment
As depicted in figs. 1 and 2, coal resources mining right valuation methods known to an attribute intensity function of the invention,
Comprise the following steps：
Step 1: determine the ATTRIBUTE INDEX of coal resources mining right to be assessed and determine the evaluation of estimate of ATTRIBUTE INDEX：First,
Give coal resources mining right to be assessed ATTRIBUTE INDEX, the ATTRIBUTE INDEX include coal seam thickness, regularity of coal seam, ash content,
Caloric value, mining depth, coal price and transportation range, wherein, using detector for measuring depth of coal bed 1 measure the coal seam thickness and
The mining depth, regular coal seam thickness statistic is measured using detector for measuring depth of coal bed 1 and obtains the regularity of coal seam, is used
Coal ash measures the release of 1kg raw coal combustions with raw coal quality than obtaining the ash content using calorimeter 2 after the measurement burning of weighing instrument 2
Heat obtain the caloric value, manually give the coal price and be stored in memory 7, coal is obtained using navigator 4
The distance between charcoal original position obtains the transportation range；Then, it is determined that the ATTRIBUTE INDEX of coal resources mining right to be assessed
Evaluation of estimate ysjAnd ysj≤ η, wherein, η is the upper limit threshold of ATTRIBUTE INDEX, and j is ATTRIBUTE INDEX numbering and j is non-not less than 3
Negative integer, i.e. j=1,2 ..., n, ysjValue is determined using expert point rating method；
In the present embodiment, the η values are 10, and the evaluation of estimate of each ATTRIBUTE INDEX, simple general-purpose are determined using ten point system；
The ATTRIBUTE INDEX includes coal seam thickness, regularity of coal seam, ash content, caloric value, mining depth, coal price and transportation range 7
Individual ATTRIBUTE INDEX；
It should be noted that coal seam thickness, regularity of coal seam, ash content, caloric value, mining depth, coal price and transport
Distance is the important factor in order of Coal Resources Property and coal resources mining right in the property of value, wherein, coal seam is divided into surely
Determine coal seam, comparatively regularcoal seam, irregular coal seam and extremely irregularcoal seam, regularity of coal seam is that regular coal seam accounts for the hundred of full well coal amount
Divide ratio, wherein, regular coal seam discreet value determines that coal seam thickness discreet value, mining depth are estimated using detection expert estimation in advance
Value, coal price discreet value and transportation range discreet value can use detection in advance and expert to estimate to determine；Ash content discreet value and
Caloric value discreet value can be obtained by sampling.
The evaluation of estimate of the coal seam thickness is ys1AndWherein, thi is real
Border coal seam thickness；The evaluation of estimate of regularity of coal seam is ys2AndWherein, sta is stable
Coal seam accounts for the mass percent of full well coal amount；The evaluation of estimate of ash content is ys3AndWherein,
AdFor the dust burdening after coal burning；The evaluation of estimate of caloric value is ys4AndIts
In, Cal is heating value of coal；The evaluation of estimate of mining depth is ys5AndWherein, dep is actual
Mining depth；The evaluation of estimate of coal price is ys6AndWherein, pri is artificial
Given coal price per ton；The evaluation of estimate of transportation range is ys7And
Wherein, dis is actual shipment distance.
In the present embodiment, first against degree of membership section to coal seam thickness, regularity of coal seam, ash content, caloric value, mining depth
Degree, coal price and transportation range do preliminary evaluation, obtain evaluation of estimate；Then value is determined using expert point rating method, institute
Stating the expert in expert point rating method includes colliery chief engineer, financial administrator and assets assessment teacher, to be evaluated in the present embodiment
The ATTRIBUTE INDEX evaluation of estimate value for estimating coal resources mining right is the evaluation of estimate y of coal seam thicknesss1=7.02, regularity of coal seam is commented
It is worth ys2=7.18, the evaluation of estimate y of ash contents3=6.36, the evaluation of estimate y of caloric values4=6.44, the evaluation of estimate y of mining depths5
=6.82, the evaluation of estimate y of coal prices6=6.13, the evaluation of estimate y of transportation ranges7=2.36.
Step 2: storage case coal resources mining right：Provided the coal resources mining right merchandised as case coal
Source mining right, the ATTRIBUTE INDEX of the case coal resources mining right is consistent with coal resources mining right ATTRIBUTE INDEX to be assessed,
M case coal resources mining right is stored in memory 7, m is positive integer and m is more than ATTRIBUTE INDEX numbering j；
Step 3: obtain attribute intensity function coefficient：According to attribute intensity functionComputer 5 uses
Regression analysis calculates regression coefficientWith the attribute coefficients of j-th of ATTRIBUTE INDEXWherein, ycjProvided for c-th of case coal
The evaluation of estimate of j-th of ATTRIBUTE INDEX of source mining right, c is positive integer and c is not more than m；
It should be noted that the present embodiment chooses 12 cases consistent with coal resources mining right ATTRIBUTE INDEX to be assessed
Coal resources mining right, the evaluation of estimate and transaction value of the ATTRIBUTE INDEX of 12 case coal resources mining rights are as follows：
In the present embodiment, regression coefficient is calculated using regression analysis by above-mentioned 12 case coal resources mining rightJth
The attribute coefficients of individual ATTRIBUTE INDEX
Step 4: predict the price of coal resources mining right to be assessed：First, according to formula
The Tuning function Δ P of the computation attribute index of computer 5c；Then, according to formulaComputer 5 is counted
Calculate after c-th of case coal resources mining right adjusts to the forecast price P of coal resources mining right to be assessedSc, wherein, PCcFor
Transaction value before c-th of case coal resources mining right adjustment；
Step 5: determine the estimate of the variance of coal resources mining right forecast price to be assessed：According to formulaComputer 5 calculates c-th of case coal
To the forecast price P of coal resources mining right to be assessed after the adjustment of resource mining rightScVariance estimation values sigma2(PSc), wherein,
σ2(PCc) for the variance of c-th case coal resources mining right transaction value,For the attribute coefficients and k of k-th of ATTRIBUTE INDEX
No more than n,For the attribute coefficients of j-th of ATTRIBUTE INDEXWith the attribute coefficients of k-th of ATTRIBUTE INDEXAssociation side
Difference,For the attribute coefficients of c-th of case coal resources mining right transaction value and j-th of ATTRIBUTE INDEXAssociation
Variance；
In the present embodiment, the variances sigma of c-th of case coal resources mining right transaction value2(PCc), j-th of attribute
The attribute coefficients of indexWith the attribute coefficients of k-th of ATTRIBUTE INDEXCovarianceC-th of case coal money
The attribute coefficients of source mining right transaction value and j-th of ATTRIBUTE INDEXCovarianceUsing the LS Returns Law and
Statistics Method, which calculates, to be obtained.
In the present embodiment, case coal resources mining right is adjusted using the Tuning function of ATTRIBUTE INDEX, case coal money
The price of coal resources mining right to be assessed is predicted after the mining right adjustment of source, determines that coal resources mining right to be assessed is pre-
The estimate of the variance of price is surveyed, it is as a result as follows：
Step 6: structure quasi-optimal case coal resources mining right collection：First, computer 5 is individual to the m calculated in step 5
The estimate of the variance of the forecast price of coal resources mining right to be assessed is carried out after the adjustment of case coal resources mining right from
It is small to be sorted to big；Then, computer 5 sets the threshold xi of the estimate of variance in memory 7, according to formula σ2(PSc)≤ξ,
Computer 5 builds quasi-optimal case coal resources mining right collection Cb；
In the present embodiment, the threshold xi value of the estimate of the variance meets：0.030≤ξ≤0.035.
It should be noted that the threshold xi of the estimate of variance described in the present embodiment preferably takes 0.030, therefore, standard is most
Excellent case coal resources mining right collection CbBy the 2nd case coal resources mining right, the 3rd case coal resources mining right, the 4th
Individual case coal resources mining right, the 5th case coal resources mining right, the 6th case coal resources mining right and the 7th case
Example coal resources mining right composition.
Step 7: determining optimal case coal resources mining right collection, process is as follows：
Step 701, the optimal case coal resources mining right subset of structure：Computer 5 is adopted in quasi-optimal case coal resources
Mineral rights collection CbThe middle case coal resources mining right for choosing varying number forms optimal case coal resources mining right subsetIts
In,M is quasi-optimal case coal resources mining right collection CbThe number of middle case coal resources mining right
Amount, i are the quantity for the case coal resources mining right chosen, and l is optimal case corresponding to the case coal resources mining right chosen
Example coal resources mining right subsetNumbering；
It should be noted that in the present embodiment, quasi-optimal case coal resources mining right collection CbMiddle case coal resources are adopted
The quantity M of mineral rights is 6, when the quantity i of the case coal resources mining right of selection is 1, the mining of quasi-optimal case coal resources
Power collection CbIncluding 6 types；When the quantity i of the case coal resources mining right of selection is 2, quasi-optimal case coal resources are adopted
Mineral rights collection CbIncluding 15 types；When the quantity i of the case coal resources mining right of selection is 3, quasi-optimal case coal money
Source mining right collection CbIncluding 20 types；When the quantity i of the case coal resources mining right of selection is 4, quasi-optimal case coal
Charcoal resource mining right collection CbIncluding 15 types；When the quantity i of the case coal resources mining right of selection is 5, quasi-optimal case
Example coal resources mining right collection CbIncluding 6 types；When the quantity i of the case coal resources mining right of selection is 6, quasi-optimal
Case coal resources mining right collection CbIncluding 1 type；Therefore, quasi-optimal case coal resources mining right collection CbShare 63 species
Type, respectively to the quasi-optimal case coal resources mining right collection C of 63 typesbIt is numbered, l=1~63.
Step 702, according to formulaComputer 5 calculates optimal case coal money
Source mining right subsetIn minimum variance between each forecast priceAnd determine optimal case coal resources mining right
Collection, wherein, PlFor the set of forecast price corresponding to the case coal resources mining right of selection, D (Pl) provided for optimal case coal
Source mining right subsetIn between each forecast price variance-covariance matrix and For quasi-optimal case coal resources mining right collection CbIn the 1st case coal resources mining right forecast price,It is defined most
Excellent case coal resources mining right collection CbIn the 2nd case coal resources mining right forecast price,For quasi-optimal case coal
Charcoal resource mining right collection CbThe forecast price of middle m-th case coal resources mining right, SlFor optimal case coal resources mining right
SubsetIn each case coal resources mining right composition similarity vector, SfFor f-th of Similarity value in similarity vector；
It should be noted that the quasi-optimal case coal resources mining right collection C to 63 typesbCarry out each forecast price it
Between minimum varianceCalculate, it is different for i value, quasi-optimal case coal resources under varying number are calculated respectively
The similarity vector and minimum variance of mining right collection, it is as a result as follows：
It should be noted that when the quantity i of the case coal resources mining right of selection is 1, quasi-optimal case coal money
Source mining right collection CbIncluding 6 types, wherein, when the case coal resources mining right of selection is adopted for the 3rd case coal resources
During mineral rights, quasi-optimal case coal resources mining right collection CbCorresponding minimum variance is 0.0212；According to upper form with such
Push away, acquisition minimum variance is respectively calculated to the quasi-optimal case coal resources mining right collection of 63 types.When the case of selection
When the quantity i of example coal resources mining right is 4, quasi-optimal case coal resources mining right collection CbThe case coal resources of selection are adopted
Mineral rights is the 3rd case coal resources mining right, the 4th case coal resources mining right, the 5th case coal resources mining right
During with the 7th case coal resources mining right, quasi-optimal case coal resources mining right collection CbCorresponding minimum variance is
0.0165, and 0.0165 be 63 types quasi-optimal case coal resources mining right collection variance minimum value, therefore, optimal case
Coal resources mining right subsetFor with by the 3rd case coal resources mining right, the 4th case coal resources mining right, the 5th
The set of individual case coal resources mining right and the 7th case coal resources mining right composition.
Step 8: assess coal resources value of mining property to be assessed：According to formulaComputer 5 is calculated and treated
Coal resources value of mining property V is assessed, and the estimated value of coal resources mining right to be assessed is shown by display 6, wherein,
Z is the coal resources reserves of coal resources mining right to be assessed.
It should be noted that the final estimated price of coal resources mining right to be assessed isCoal money to be assessed
The coal resources reserves Z of source mining right is in units of ton, coal resources value of mining property V=10.76Z (Yuan) to be assessed, this
Invention sets optimal case coal resources mining right collection Criterion of Selecting and determines similarity vector, obtains coal resources to be assessed and adopts
Mineral rights is worth, and the theoretical support with method is provided for coal resources reasonable disposition and the construction of mining right trade market.
It is described above, only it is presently preferred embodiments of the present invention, not the present invention is imposed any restrictions, it is every according to the present invention
Any simple modification, change and the equivalent structure change that technical spirit is made to above example, still fall within skill of the present invention
In the protection domain of art scheme.
Claims (4)
1. coal resources mining right valuation methods known to an attribute intensity function, it is characterised in that this method includes following
Step：
Step 1: determine the ATTRIBUTE INDEX of coal resources mining right to be assessed and determine the evaluation of estimate of ATTRIBUTE INDEX：First, give
The ATTRIBUTE INDEX of coal resources mining right to be assessed, the ATTRIBUTE INDEX include coal seam thickness, regularity of coal seam, ash content, heating
Amount, mining depth, coal price and transportation range, wherein, the coal seam thickness and institute are measured using detector for measuring depth of coal bed (1)
Mining depth is stated, measuring regular coal seam thickness statistic using detector for measuring depth of coal bed (1) obtains the regularity of coal seam, uses
Coal ash measures 1kg raw coal combustions with raw coal quality than obtaining the ash content using calorimeter (2) after weighing instrument (2) measurement burning
The heat of release obtains the caloric value, manually gives the coal price and is stored in memory (7), using navigator
(4) obtain the distance between coal original position and obtain the transportation range；Then, it is determined that coal resources mining right to be assessed
The evaluation of estimate y of ATTRIBUTE INDEXsjAnd ysj≤ η, wherein, η is the upper limit threshold of ATTRIBUTE INDEX, and j is ATTRIBUTE INDEX numbering and j is not
Nonnegative integer less than 3, i.e. j=1,2 ..., n, ysjValue is determined using expert point rating method；
Step 2: storage case coal resources mining right：The coal resources mining right merchandised is adopted as case coal resources
Mineral rights, the ATTRIBUTE INDEX of the case coal resources mining right is consistent with coal resources mining right ATTRIBUTE INDEX to be assessed, is depositing
M case coal resources mining right of storage in reservoir (7), m is positive integer and m is more than ATTRIBUTE INDEX numbering j；
Step 3: obtain attribute intensity function coefficient：According to attribute intensity functionComputer (5) uses back
Analytic approach is returned to calculate regression coefficientWith the attribute coefficients of j-th of ATTRIBUTE INDEXWherein, ycjFor c-th of case coal resources
The evaluation of estimate of j-th of ATTRIBUTE INDEX of mining right, c is positive integer and c is not more than m；
Step 4: predict the price of coal resources mining right to be assessed：First, according to formulaCalculate
The Tuning function Δ P of machine (5) computation attribute indexc；Then, according to formulaComputer (5) is counted
Calculate after c-th of case coal resources mining right adjusts to the forecast price P of coal resources mining right to be assessedSc, wherein, PCcFor
Transaction value before c-th of case coal resources mining right adjustment；
Step 5: determine the estimate of the variance of coal resources mining right forecast price to be assessed：According to formulaComputer (5) calculates c-th of case coal
To the forecast price P of coal resources mining right to be assessed after the adjustment of charcoal resource mining rightScVariance estimation values sigma2(PSc), its
In, σ2(PCc) for the variance of c-th case coal resources mining right transaction value,For the attribute coefficients of k-th of ATTRIBUTE INDEX
And k is not more than n,For the attribute coefficients of j-th of ATTRIBUTE INDEXWith the attribute coefficients of k-th of ATTRIBUTE INDEX's
Covariance,For the attribute coefficients of c-th of case coal resources mining right transaction value and j-th of ATTRIBUTE INDEX
Covariance；
Step 6: structure quasi-optimal case coal resources mining right collection：First, computer (5) is to the m cases that are calculated in step 5
The estimate of the variance of the forecast price of coal resources mining right to be assessed is carried out from small after the mining right adjustment of example coal resources
To big sequence；Then, computer (5) sets the threshold xi of the estimate of variance in memory (7), according to formula σ2(PSc)≤
ξ, computer (5) structure quasi-optimal case coal resources mining right collection Cb；
Step 7: determining optimal case coal resources mining right collection, process is as follows：
Step 701, the optimal case coal resources mining right subset of structure：Computer (5) is dug up mine in quasi-optimal case coal resources
Power collection CbThe middle case coal resources mining right for choosing varying number forms optimal case coal resources mining right subsetIts
In,M is quasi-optimal case coal resources mining right collection CbThe number of middle case coal resources mining right
Amount, i are the quantity for the case coal resources mining right chosen, and l is optimal case corresponding to the case coal resources mining right chosen
Example coal resources mining right subsetNumbering；
Step 702, according to formulaComputer (5) calculates optimal case coal resources mining
Weigh subsetIn minimum variance between each forecast priceAnd optimal case coal resources mining right collection is determined, wherein,
PlFor the set of forecast price corresponding to the case coal resources mining right of selection, D (Pl) it is optimal case coal resources mining right
SubsetIn between each forecast price variance-covariance matrix and
For quasi-optimal case coal resources mining right collection CbIn the 1st case coal resources mining right forecast price,For quasi-optimal
Case coal resources mining right collection CbIn the 2nd case coal resources mining right forecast price,For quasi-optimal case coal
Resource mining right collection CbThe forecast price of middle m-th case coal resources mining right, SlFor optimal case coal resources mining right
CollectionIn each case coal resources mining right composition similarity vector, SfFor f-th of Similarity value in similarity vector；
Step 8: assess coal resources value of mining property to be assessed：According to formulaComputer (5) calculates to be evaluated
Estimate coal resources value of mining property V, and the estimated value of coal resources mining right to be assessed is shown by display (6), wherein,
Z is the coal resources reserves of coal resources mining right to be assessed.
2. according to coal resources mining right valuation methods, its feature known to the attribute intensity function described in claim 1
It is：The η values are 10；The evaluation of estimate of the coal seam thickness is ys1AndIts
In, thi is actual coal seam thickness；The evaluation of estimate of regularity of coal seam is ys2AndWherein,
Sta is the mass percent that regular coal seam accounts for full well coal amount；The evaluation of estimate of ash content is ys3AndIts
In, AdFor the dust burdening after coal burning；The evaluation of estimate of caloric value is ys4And
Wherein, Cal is heating value of coal；The evaluation of estimate of mining depth is ys5AndWherein, dep
For actual mining depth；The evaluation of estimate of coal price is ys6AndWherein, pri
For manually given coal price per ton；The evaluation of estimate of transportation range is ys7And
Wherein, dis is actual shipment distance.
3. according to coal resources mining right valuation methods, its feature known to the attribute intensity function described in claim 1
It is：The variances sigma of c-th of case coal resources mining right transaction value2(PCc), the attribute coefficients of j-th ATTRIBUTE INDEXWith the attribute coefficients of k-th of ATTRIBUTE INDEXCovarianceC-th of case coal resources mining right settlement price
The attribute coefficients of lattice and j-th of ATTRIBUTE INDEXCovarianceCalculated using the LS Returns Law and Statistics Method
Obtain.
4. according to coal resources mining right valuation methods, its feature known to the attribute intensity function described in claim 1
It is：The threshold xi value of the estimate of the variance meets：0.030≤ξ≤0.035.
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Citations (2)
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| US20070185750A1 (en) * | 2004-06-21 | 2007-08-09 | Merab Menabde | Method, apparatus and computer program for scheduling the extraction of a resource and for determining the net present value of an extraction schedule |
| CN103247005A (en) * | 2013-04-23 | 2013-08-14 | 山西潞安集团潞宁煤业有限公司 | Coal quality and coal price matching method and device |
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| US20070185750A1 (en) * | 2004-06-21 | 2007-08-09 | Merab Menabde | Method, apparatus and computer program for scheduling the extraction of a resource and for determining the net present value of an extraction schedule |
| CN103247005A (en) * | 2013-04-23 | 2013-08-14 | 山西潞安集团潞宁煤业有限公司 | Coal quality and coal price matching method and device |
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