CN106327019A - Resource environmental bearing capacity early-warning method and system - Google Patents
Resource environmental bearing capacity early-warning method and system Download PDFInfo
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- CN106327019A CN106327019A CN201610766005.4A CN201610766005A CN106327019A CN 106327019 A CN106327019 A CN 106327019A CN 201610766005 A CN201610766005 A CN 201610766005A CN 106327019 A CN106327019 A CN 106327019A
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Abstract
The invention relates to a resource environmental bearing capacity early-warning method and system, and the method comprises the following steps: determining a comprehensive index early-warning level; determining a restrictive index early-warning level; comparing the restrictive index early-warning level with the comprehensive index early-warning level: determining that the comprehensive index early-warning level serves as the evaluation result of the resource environmental bearing capacity if the restrictive index early-warning level is less than the comprehensive index early-warning level, or else, determining that the restrictive index early-warning level serves as the evaluation result of the resource environmental bearing capacity. According to the embodiment of the invention, the method and system give consideration to the multi-index comprehensive early warning, have the restrictive index early warning for the strong resource environment quality instruction, finally integrate the comprehensive multi-index early warning and the single-index early warning, take the highest early warning level as the final early warning result, is higher in accuracy and reliability, and plays a better guide role in the formulating of economic and social development plans.
Description
Technical field
The present invention relates to ecological resources assessment technique field, particularly to a kind of resosurces environment loading capacity method for early warning and be
System.
Background technology
At present, urbanization at a high speed makes the finiteness of resource and the vulnerability of environment more highlight with industrialization how
In the face of resource scarcity, environmental pollution are serious, the current situation of ecosystem degradation, in strict accordance with resource environment in regional development
Capacity, it is achieved the scientific development that Population, Resources, And Environment equalizes mutually, economic society ecological benefits are mutually unified, is that everybody makes great efforts always
Target.
Resosurces environment loading capacity is studied, provides resosurces environment loading capacity evaluation or early warning, worker can be instructed
Preferably solve ecological problem and socioeconomic problem.Have multiple for evaluating the index of resosurces environment loading capacity, as environment holds
Amount opinion rating, per capita water resource potentiality, Forest and sod coverage rate etc..Generally use resosurces environment loading capacity at present comprehensive
Early warning, i.e. considers the impact of each index, provides a comprehensive early warning result.Finding in research, comprehensive pre-warning is permissible
Reach certain early warning, but still there is certain unreliability, therefore, find a kind of more structurally sound resource environment to hold
Load power method for early warning is current problem demanding prompt solution.
Summary of the invention
It is an object of the invention to provide a kind of resosurces environment loading capacity method for early warning and system, compared to prior art,
There is more preferable reliability.
In order to realize foregoing invention purpose, embodiments provide techniques below scheme:
A kind of resosurces environment loading capacity method for early warning, comprises the following steps:
Determine aggregative indicator advanced warning grade；
Determine restricted forewarning index grade；
Relatively described restricted forewarning index grade and the height of described aggregative indicator advanced warning grade, if described restricted
Forewarning index grade is less than described aggregative indicator advanced warning grade, then provide described aggregative indicator advanced warning grade and hold as resource environment
The evaluation result of load power, otherwise provides the restricted forewarning index grade evaluation result as resosurces environment loading capacity.
Including aggregative indicator advanced warning grade, a kind of resosurces environment loading capacity early warning system, determines that module, restricted index are pre-
Alert level determination module, comparison module；
Described aggregative indicator advanced warning grade determines that module is for determining aggregative indicator advanced warning grade；
Described restricted forewarning index level determination module is used for determining restricted forewarning index grade；
Described comparison module is for the height of relatively described restricted forewarning index grade with described aggregative indicator advanced warning grade
Low, if described restricted forewarning index grade is less than described aggregative indicator advanced warning grade, then provide described aggregative indicator early warning
Grade, as the evaluation result of resosurces environment loading capacity, otherwise provides restricted forewarning index grade as resosurces environment loading capacity
Evaluation result.
Compared with prior art, beneficial effects of the present invention: the method and system that the embodiment of the present invention provides is many in consideration
In the case of index comprehensive early warning, simultaneously to have the good and bad tell-tale index of strong resource environment, as restricted index, enter
Row single index early warning, last comprehensive multi objective early warning and single index early warning result, using advanced warning grade the highest as final early warning
As a result, there is higher accuracy and reliability, serve preferably directiveness effect for formulating plans for economic and social development.
Accompanying drawing explanation
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, below by embodiment required use attached
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, and it is right to be therefore not construed as
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to according to this
A little accompanying drawings obtain other relevant accompanying drawings.
The flow chart of the resosurces environment loading capacity method for early warning that Fig. 1 present pre-ferred embodiments provides.
Fig. 2 present pre-ferred embodiments determines the flow chart of aggregative indicator advanced warning grade.
Fig. 3 is the high-level schematic functional block diagram of the resosurces environment loading capacity early warning system that present pre-ferred embodiments provides.
Detailed description of the invention
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Generally exist
Can arrange and design with various different configurations with the assembly of the embodiment of the present invention that illustrates described in accompanying drawing herein.Cause
This, be not intended to limit claimed invention to the detailed description of the embodiments of the invention provided in the accompanying drawings below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on embodiments of the invention, those skilled in the art are not doing
The every other embodiment obtained on the premise of going out creative work, broadly falls into the scope of protection of the invention.
Resosurces environment loading capacity early warning can be divided into two types: (1) certain timing node, a certain region, sends out in particular social
Under exhibition level, the consumption of existence resource, and the live discharge producing refuse and the nearness of ecological environmenies at different levels harm, can claim
Present situation early warning for resosurces environment loading capacity；(2) by resosurces environment loading capacity historical data, it was predicted that a certain region, in future
Node sometime, may consuming of existence resource, and life produces the anticipated discharge of refuse and the lifes at different levels being likely to result in
The nearness of state environmental hazard, can be described as the trending early warning of resosurces environment loading capacity.The resource environment provided in the present embodiment holds
Load power method for early warning and system, belong to the present situation early warning of resosurces environment loading capacity.
Fig. 1 shows the flow process of resosurces environment loading capacity method for early warning described in the present embodiment, refers to Fig. 1, below by right
Idiographic flow shown in Fig. 1 is described in detail.
Step S101, determines aggregative indicator advanced warning grade.
Have multiple for evaluating the index of resosurces environment loading capacity, in the present embodiment, respectively from resource, environment, society's warp
The aspects such as Ji be provided with 21 kinds for the index evaluating resosurces environment loading capacity, aggregative indicator advanced warning grade i.e. refers to be commented by multiple
The advanced warning grade that valency index comprehensive obtains.Advanced warning grade is provided with 5 grade standards, be respectively safety, slight early warning, moderate early warning,
Severe early warning and danger.General early warning index numerical value is the least, illustrates that advanced warning grade is the lowest, now the carrying of resosurces environment loading capacity
State is the best, and the ability of its afforded mankind's Activities is the strongest, more can be better achieved Region Sustainable Development and
Safeguard the stability of Eco-Environment System.Otherwise, early warning index numerical value is the biggest, then advanced warning grade is the highest, resosurces environment loading capacity
Loaded state the poorest.Evaluation index and advanced warning grade are as shown in table 1.
Table 1
It should be noted that in the present embodiment, evaluation index has 21 kinds, whole 21 kinds of evaluation indexes can be selected to be evaluated
The resosurces environment loading capacity in valency region is evaluated, it is also possible to the zones of different for each region to be evaluated is arranged, Cong Zhongxuan
Take the Certain Evaluation Guideline determination for comprehensive evaluation index advanced warning grade.Such as emphasis eco-functional regionalization, can be selected for table 2
Shown in evaluation index；For the main production districts off farm products, can be selected for the evaluation index shown in table 3；For key zones for development and
Districts under city administration, can be selected for the evaluation index shown in table 4；For development for poverty relief district, can be selected for the evaluation index shown in table 5.Pass through
Selected part evaluation index for the determination of aggregative indicator advanced warning grade, is not affecting in the case of advanced warning grade determines accuracy
The operand of aggregative indicator advanced warning grade can be alleviated, reduce the requirement to hardware device.
Table 2
Table 3
| ID | Evaluation index |
| 1 | May utilize land resource area per capita |
| 2 | Available water resources per capita |
| 3 | Forest and sod coverage rate |
| 4 | Per capita net income |
| 8 | Achilles tendon tear index |
| 9 | Trend yield |
| 13 | Transportation network density |
| 17 | Effect of Natural Disaster |
| 18 | Environmental carrying capacity |
| 19 | Population density |
Table 4
| ID | Evaluation index |
| 1 | May utilize land resource area per capita |
| 2 | Water resource potentiality per capita |
| 3 | Forest and sod coverage rate |
| 4 | Per capita net income |
| 10 | Transport advantages degree |
| 11 | Urbanization rate |
| 12 | Economic density |
| 13 | Transportation network density |
| 17 | Effect of Natural Disaster |
| 18 | Environmental carrying capacity |
| 19 | Population density |
| 20 | Pollutants emission intensity |
Table 5
Step S102, determines restricted forewarning index grade.
In the above-mentioned evaluation index for evaluating resosurces environment loading capacity, some evaluation indexes have strong resource environment
Good and bad indicative, in the present embodiment, defining this kind of evaluation index is restricted index, i.e. has the instruction of strong resource environment quality
The evaluation index of property is referred to as restricted index.In the present embodiment, restricted index includes: environmental carrying capacity, per capita may utilize water money
Source, Forest and sod coverage rate, achilles tendon tear index, pollutants emission intensity, per capita net income, set according to the region in region to be evaluated
Putting difference, a region to be evaluated can relate to one or more restricted index, and in the present embodiment, each region to be evaluated is wrapped
Include environmental carrying capacity and may utilize these two basic indexs of land resource area per capita, for emphasis eco-functional regionalization, agricultural product
Main producing region, key zones for development and districts under city administration, development for poverty relief district are also respectively provided with other restricted indexs, as shown in table 6.
Table 6
| Index region is arranged | Evaluation index |
| Basic index | Environmental carrying capacity, may utilize land resource area per capita |
| Emphasis eco-functional regionalization | Forest and sod coverage rate |
| The main production districts off farm products | Achilles tendon tear index |
| Key zones for development and districts under city administration | Pollutants emission intensity |
| Development for poverty relief district | Per-capita net income in rural areas |
Step S103, relatively restricted forewarning index grade and the height of aggregative indicator advanced warning grade, if restricted finger
Mark advanced warning grade less than aggregative indicator advanced warning grade, then provides the evaluation as resosurces environment loading capacity of the aggregative indicator advanced warning grade
As a result, otherwise the evaluation result providing restricted forewarning index grade as resosurces environment loading capacity (it is more than or equal to).
Such as, the aggregative indicator advanced warning grade of region A to be evaluated is safety, and the restricted index of this region A to be evaluated is pre-
Alert grade is slight early warning, then the evaluation result of the resosurces environment loading capacity of this region A to be evaluated is slight early warning；And for example,
The aggregative indicator advanced warning grade of region B to be evaluated is moderate early warning, and the restricted forewarning index grade of this region B to be evaluated is light
Degree early warning, then the evaluation result of the resosurces environment loading capacity of this region B to be evaluated is moderate early warning.
Each can hold from each different angles reflection resource environment for the evaluation index evaluating resosurces environment loading capacity
Load power, the most restricted index, therefore restricted evaluation index is carried out advanced warning grade evaluation and be highly desirable to.The present embodiment
In described method, not only carry out aggregative indicator advanced warning grade evaluation, also carry out restricted forewarning index grade evaluation, finally
Evaluation result consider overall merit advanced warning grade and restricted forewarning index grade, compared to only considering that overall merit is pre-
Alert grade is compared, and the accuracy of method described in the present embodiment is higher, more reliable, serves for formulating plans for economic and social development
Preferably directiveness effect.
In step S101, determine that the mode of aggregative indicator advanced warning grade can have multiple, refering to Fig. 2, in the present embodiment, adopt
With the following method:
Step S1011, the overall merit data matrix of definition resosurces environment loading capacity is α, 5 grades of resosurces environment loading capacity
Early warning threshold limit value matrix is β, αijJth item evaluation index for i-th unit to be evaluated (corresponding to region to be evaluated) is sampled
Value (actual samples measured data values), βksThe s threshold value of warning for kth item evaluation index；I=1,2 ... m, j=1,2 ...
N, k=1,2 ... n, s=1,2 ... 6, m, n be natural number.
Step S1012, asks for the average value mu of all sampled values in overall merit data matrix α respectivelyαAnd standard deviation sigmaα, and
Ask for μαWith σαRatioAsk for the average value mu of all data in 5 grades of early warning threshold limit value matrix β respectivelyβStandard deviation sigmaβ,
And ask for μβWith σβRatio
Step S1013, by each sampled value in overall merit data matrix α withMake difference operation, using each difference as
Overall merit data matrix α ' after corresponding variable composition process, by each data in 5 grades of early warning threshold limit value matrix β
WithMake difference operation, 5 grades of early warning threshold limit value matrix β ' after processing as a corresponding variable composition using each difference.
Step S1014, asks for the transposed matrix α ' of the overall merit data matrix α ' after processing respectivelyTWith 5 after process
The transposed matrix β ' of level early warning threshold limit value matrix β 'T。
Step S1015, the transposed matrix α ' to the overall merit data matrix α ' after processingTIt is QR to decompose, obtains orthogonal
Matrix QαWith upper triangular matrix Rα, make Qα=α ' Qα, Rα=α ' Rα, then matrix α ' RαColumn vector be i.e. corresponding unit to be evaluated
Vector orthogonal coordinate system α ' QαUnder coordinate vector；Transposed matrix β ' to 5 grades of early warning threshold limit value matrix β ' after processingT
It is QR to decompose, obtains orthogonal matrix QβWith upper triangular matrix Rβ, make Qβ=β ' Qβ, Rβ=β ' Rβ, then matrix β ' RβColumn vector i.e.
Corresponding unit to be evaluated vector orthogonal coordinate system β ' QβUnder coordinate vector.
Step S1016, then utilizes formula P=α ' Qα -1·β'QβObtain by orthogonal basis α ' QαTo β ' QβTransition matrix P,
Recycling formula T=P-1·α'RαObtain coordinate α ' RαAt orthogonal basis β ' QβThe mapping matrix T of column space.
Step S1017, the column vector of mapping matrix T is unit to be evaluated vector, is designated as T', T'=(a1,a2,…am), ai
(i=1,2 ..., m) it is i-th unit to be evaluated vector；Matrix β ' QβColumn vector be threshold limit value vector, be designated as β ' Qβ', β '
Qβ'=(b1,b2,b3,b4,b5,b6), bs(s=1,2,3,4,5,6) it is the s threshold limit value vector.Use formula Dis=| | T'
(ai)-β'Qβ'(bs) | | i-th unit to be evaluated vector and the Euclidean distance of the s threshold limit value vector, make s=1,2,3,4,
5,6, obtain the Euclidean distance of i-th unit to be evaluated vector and six threshold limit value vectors respectively, and be designated as D respectivelyi1, Di2,
Di3, Di4, Di5, Di6。
Step S1018, calculates D respectivelyi1With Di2Difference, Di2With Di3Difference, Di3With Di4Difference, Di4With Di5's
Difference, Di5With Di6Difference, search the advanced warning grade preset and table be set, with minimum | Dis-Di(s+1)| corresponding advanced warning grade
As the advanced warning grade of i-th unit to be evaluated vector, i.e. with minimum | Dis-Di(s+1)| corresponding advanced warning grade is as i-th
The advanced warning grade in region to be evaluated.
Such as, the region a certain to be evaluated calculated is as shown in table 7 with the Euclidean distance of six threshold limit value vectors, faces
Advanced warning grade corresponding to boundary's threshold value is as shown in table 8, by can be calculated | S3-S4 |=| 3.33-3.37 |=0.04, minimum, thus,
The advanced warning grade in this region to be evaluated is moderate early warning.
Table 7
In the present embodiment, advanced warning grade is set to 5 grades, it is readily appreciated that ground, according to different demands, it is possibility to have other set
Putting, the present embodiment is without limitation.
Table 8
Determining aggregative indicator advanced warning grade by said method, reliability is high, and the simplest compared to other modes at present
Single.
In step S102, determine that the mode of restricted forewarning index grade can have multiple, in the present embodiment, use as follows
Method:
Sampled value according to restricted index and default restricted forewarning index classification standard, determine each restricted finger
Target advanced warning grade；The evaluation index advanced warning grade standard used in the present embodiment is as shown in table 7, and table 9 includes restricted finger
Mark advanced warning grade standard.
Table 9
Such as, may utilize land resource area per capita for restricted index, it is assumed that the sampled value of this index is 0.92, root
Advanced warning grade standard ((0.8,2] be slight early warning) according to this index shown in table 9, it may be determined that the advanced warning grade of this index is light
Degree early warning.
The number of the restricted index related to according to region to be evaluated determines restricted forewarning index grade: when restricted finger
When being designated as one, using the advanced warning grade of this restricted index as restricted forewarning index grade；When restricted index is two
And time above, using the advanced warning grade of the highest restricted index of advanced warning grade as restricted forewarning index grade.
Such as a kind of citing, it is assumed that the evaluation result that may utilize land resource area per capita is slight early warning, environment
The evaluation result of capacity is safety, the slight early warning of evaluation result of Forest and sod coverage rate, then restricted forewarning index grade is
Slight early warning.
Refer to Fig. 3, be that the functional module of the resosurces environment loading capacity early warning system that present pre-ferred embodiments provides is shown
It is intended to.Described resosurces environment loading capacity early warning system includes that aggregative indicator advanced warning grade determines module 301, restricted forewarning index
Level determination module 302, comparison module 303.
Described aggregative indicator advanced warning grade determine module 301 for determining aggregative indicator advanced warning grade, described aggregative indicator
Advanced warning grade i.e. refers to the advanced warning grade comprehensively obtained by multiple evaluation indexes.
Described restricted forewarning index level determination module 302 is used for determining restricted forewarning index grade.Have strong
The good and bad tell-tale evaluation index of resource environment is referred to as restricted index, and restricted forewarning index grade i.e. refers to by restricted finger
The advanced warning grade that mark obtains.
Described comparison module 303 is for relatively described restricted forewarning index grade and described aggregative indicator advanced warning grade
Just, if described restricted forewarning index grade is less than described aggregative indicator advanced warning grade, then described aggregative indicator is provided pre-
Alert grade, as the evaluation result of resosurces environment loading capacity, otherwise provides restricted forewarning index grade and carries as resource environment
The evaluation result of power.
In the present embodiment, described aggregative indicator advanced warning grade determine module 301 specifically for:
The overall merit data matrix of definition resosurces environment loading capacity is α, 5 grades of early warning Threshold extent of resosurces environment loading capacity
Value matrix is β, αijJth item evaluation index sampled value (actual samples for i-th unit to be evaluated (corresponding to region to be evaluated)
Measured data values), βksThe s threshold value of warning for kth item evaluation index；I=1,2 ... m, j=1,2 ... n, k=1,2 ...
N, s=1,2 ... 6, m, n be natural number.
Ask for the average value mu of all sampled values in overall merit data matrix α respectivelyαAnd standard deviation sigmaα, and ask for μαWith σα
RatioAsking for 5 grades of early warning threshold limit value matrixes respectively is the average value mu of all data in ββStandard deviation sigmaβ, and ask for μβ
With σβRatio
By each sampled value in overall merit data matrix α withMake difference operation, using each difference as corresponding one
Variable composition process after overall merit data matrix α ', by each data in 5 grades of early warning threshold limit value matrix β withDiffer from
Computing, 5 grades of early warning threshold limit value matrix β ' after processing using each difference as a corresponding variable composition.
Ask for the transposed matrix α ' of the overall merit data matrix α ' after processing respectivelyTCritical with 5 grades of early warning after processing
The transposed matrix β ' of threshold matrix β 'T。
Transposed matrix α ' to the overall merit data matrix α ' after processingTIt is QR to decompose, obtains orthogonal matrix QαWith upper three
Angular moment battle array Rα, make Qα=α ' Qα, Rα=α ' Rα, then matrix α ' RαColumn vector be i.e. that corresponding unit to be evaluated vector is at orthogonal seat
Mark system α ' QαUnder coordinate vector；Transposed matrix β ' to 5 grades of early warning threshold limit value matrix β ' after processingTIt is QR to decompose, obtains
Orthogonal matrix QβWith upper triangular matrix Rβ, make Qβ=β ' Qβ, Rβ=β ' Rβ, then matrix β ' RβColumn vector be i.e. corresponding to be evaluated
Unit vector orthogonal coordinate system β ' QβUnder coordinate vector.
Then formula P=α ' Q is utilizedα -1·β'QβObtain by orthogonal basis α ' QαTo β ' QβTransition matrix P, then utilize public affairs
Formula T=P-1·α'RαObtain coordinate α ' RαAt orthogonal basis β ' QβThe mapping matrix T of column space.
The column vector of mapping matrix T is unit to be evaluated vector, is designated as T', T'=(a1,a2,…am), ai(i=1,
2 ..., m) it is i-th unit to be evaluated vector；Matrix β ' QβColumn vector be threshold limit value vector, be designated as β ' Qβ', β ' Qβ'=
(b1,b2,b3,b4,b5,b6), bs(s=1,2,3,4,5,6) it is the s threshold limit value vector.Use formula Dis=| | T'(ai)-
β'Qβ'(bs) | | i-th unit to be evaluated vector and the Euclidean distance of the s threshold limit value vector, make s=1,2,3,4,5,6,
Obtain the Euclidean distance of i-th unit to be evaluated vector and six threshold limit value vectors respectively, and be designated as D respectivelyi1, Di2, Di3,
Di4, Di5, Di6, calculate D respectivelyi1With Di2Difference, Di2With Di3Difference, Di3With Di4Difference, Di4With Di5Difference, Di5With
Di6Difference, with minimum | Dis-Di(s+1)| corresponding advanced warning grade as the advanced warning grade of i-th unit to be evaluated vector,
I.e. with minimum | Dis-Di(s+1)| corresponding advanced warning grade is as the advanced warning grade in i-th region to be evaluated.
In the present embodiment, described restricted forewarning index level determination module 302, specifically for according to restricted index
Sampled value and default restricted forewarning index classification standard, determine the advanced warning grade of each restricted index；When restricted finger
When being designated as one, using the advanced warning grade of this restricted index as restricted forewarning index grade；When restricted index is two
And time above, using the advanced warning grade of the highest restricted index of advanced warning grade as restricted forewarning index grade.
Each functional module in embodiments of the present invention can integrate one independent part of formation, it is also possible to is
Modules individualism, it is also possible to two or more modules are integrated to form an independent part.
If described function is using the form realization of software function module and as independent production marketing or use, permissible
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is the most in other words
The part contributing prior art or the part of this technical scheme can embody with the form of software product, this meter
Calculation machine software product is stored in a storage medium, including some instructions with so that a computer equipment (can be individual
People's computer, server, or the network equipment etc.) perform all or part of step of method described in each embodiment of the present invention.
And aforesaid storage medium includes: USB flash disk, portable hard drive, read only memory (ROM, Read-Only Memory), random access memory are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.
It should be noted that in this article, term " includes ", " comprising " or its any other variant are intended to non-row
Comprising of his property, so that include that the process of a series of key element, method, article or equipment not only include those key elements, and
And also include other key elements being not expressly set out, or also include intrinsic for this process, method, article or equipment
Key element.In the case of there is no more restriction, statement " including ... " key element limited, it is not excluded that including
State and the process of key element, method, article or equipment there is also other identical element.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.All within the spirit and principles in the present invention, that is made any repaiies
Change, equivalent, improvement etc., should be included within the scope of the present invention.
Claims (6)
1. a resosurces environment loading capacity method for early warning, it is characterised in that comprise the following steps:
Determine aggregative indicator advanced warning grade；
Determine restricted forewarning index grade；
Relatively described restricted forewarning index grade and the height of described aggregative indicator advanced warning grade, if described restricted index
Advanced warning grade is less than described aggregative indicator advanced warning grade, then provide described aggregative indicator advanced warning grade as resosurces environment loading capacity
Evaluation result, otherwise provide the restricted forewarning index grade evaluation result as resosurces environment loading capacity.
Method the most according to claim 1, it is characterised in that described determine aggregative indicator advanced warning grade, including:
The overall merit data matrix of definition resosurces environment loading capacity is α, 5 grades of early warning threshold limit value squares of resosurces environment loading capacity
Battle array is β, αijFor the jth item evaluation index sampled value of i-th unit to be evaluated, βksThe s early warning for kth item evaluation index
Threshold value；I=1,2 ... m, j=1,2 ... n, k=1,2 ... n, s=1,2 ... 6, m, n be natural number；
Ask for the average value mu of all sampled values in overall merit data matrix α respectivelyαAnd standard deviation sigmaα, and ask for μαWith σαRatio
ValueAsk for the average value mu of all data in 5 grades of early warning threshold limit value matrix β respectivelyβStandard deviation sigmaβ, and ask for μβWith σβ's
Ratio
By each sampled value in overall merit data matrix α withMake difference operation, form as corresponding variable using each difference
Overall merit data matrix α ' after process, by each data in 5 grades of early warning threshold limit value matrix β withMake difference operation, with often
Individual difference is as 5 grades of early warning threshold limit value matrix β ' after the process of corresponding variable composition；
Ask for the transposed matrix α ' of the overall merit data matrix α ' after processing respectivelyTWith 5 grades of early warning threshold limit value squares after process
The transposed matrix β ' of battle array β 'T；
Transposed matrix α ' to the overall merit data matrix α ' after processingTIt is QR to decompose, obtains orthogonal matrix QαWith upper three angular moments
Battle array Rα；Transposed matrix β ' to 5 grades of early warning threshold limit value matrix β ' after processingTIt is QR to decompose, obtains orthogonal matrix QβWith upper three
Angular moment battle array Rβ；
Make Qα=α ' Qα, make Qβ=β ' Qβ, utilize formula P=α ' Qα -1·β'QβObtain transition matrix P, recycle formula T=P-1·
α'RαObtain mapping matrix T；
Use formula Dis=| | T'(αi)-β'Qβ'(bs) | |, calculate s=1 respectively, 2 ... distance value D when 6is, wherein, T'
(αi) it is the i-th column vector of mapping matrix T, β ' Qβ'(bs) it is matrix β ' QβThe S column vector；
Calculate s=1,2 respectively ... difference when 5 | Dis-Di(s+1)|, search the advanced warning grade preset and table is set, with minimum
Advanced warning grade corresponding to difference is as described aggregative indicator advanced warning grade.
Method the most according to claim 1, it is characterised in that described determine restricted forewarning index grade, including:
Sampled value according to restricted index and default restricted forewarning index classification standard, determine each restricted index
Advanced warning grade；
When restricted index is one, using the advanced warning grade of this restricted index as restricted forewarning index grade；
When restricted index be two and above time, using the advanced warning grade of the highest restricted index of advanced warning grade as restricted
Forewarning index grade.
4. a resosurces environment loading capacity early warning system, it is characterised in that include that aggregative indicator advanced warning grade determines module, restriction
Property forewarning index level determination module, comparison module；
Described aggregative indicator advanced warning grade determines that module is for determining aggregative indicator advanced warning grade；
Described restricted forewarning index level determination module is used for determining restricted forewarning index grade；
Described comparison module is used for relatively described restricted forewarning index grade and the height of described aggregative indicator advanced warning grade, as
The most described restricted forewarning index grade is less than described aggregative indicator advanced warning grade, then provide described aggregative indicator advanced warning grade and make
For the evaluation result of resosurces environment loading capacity, otherwise provide the evaluation as resosurces environment loading capacity of the restricted forewarning index grade
Result.
System the most according to claim 4, it is characterised in that described aggregative indicator advanced warning grade determines that module is specifically used
In:
The overall merit data matrix of definition resosurces environment loading capacity is α, 5 grades of early warning threshold limit value squares of resosurces environment loading capacity
Battle array is β, αijFor the jth item evaluation index sampled value of i-th unit to be evaluated, βksThe s early warning for kth item evaluation index
Threshold value；I=1,2 ... m, j=1,2 ... n, k=1,2 ... n, s=1,2 ... 6, m, n be natural number；
Ask for the average value mu of all sampled values in overall merit data matrix α respectivelyαAnd standard deviation sigmaα, and ask for μαWith σαRatio
ValueAsk for the average value mu of all data in 5 grades of early warning threshold limit value matrix β respectivelyβStandard deviation sigmaβ, and ask for μβWith σβ's
Ratio
By each sampled value in overall merit data matrix α withMake difference operation, form as corresponding variable using each difference
Overall merit data matrix α ' after process, by each data in 5 grades of early warning threshold limit value matrix β withMake difference operation, with often
Individual difference is as 5 grades of early warning threshold limit value matrix β ' after the process of corresponding variable composition；
Ask for the transposed matrix α ' of the overall merit data matrix α ' after processing respectivelyTWith 5 grades of early warning threshold limit value squares after process
The transposed matrix β ' of battle array β 'T；
Transposed matrix α ' to the overall merit data matrix α ' after processingTIt is QR to decompose, obtains orthogonal matrix QαWith upper three angular moments
Battle array Rα；Transposed matrix β ' to 5 grades of early warning threshold limit value matrix β ' after processingTIt is QR to decompose, obtains orthogonal matrix QβWith upper three
Angular moment battle array Rβ；
Make Qα=α ' Qα, make Qβ=β ' Qβ, utilize formula P=α ' Qα -1·β'QβObtain transition matrix P, recycle formula T=P-1·
α'RαObtain mapping matrix T；
Use formula Dis=| | T'(αi)-β'Qβ'(bs) | |, calculate s=1 respectively, 2 ... distance value D when 6is, wherein, T'
(αi) it is the i-th column vector of mapping matrix T, β ' Qβ'(bs) it is matrix β ' QβThe S column vector；
Calculate s=1,2 respectively ... difference when 5 | Dis-Di(s+1)|, search the advanced warning grade preset and table is set, with minimum
Advanced warning grade corresponding to difference is as described aggregative indicator advanced warning grade.
System the most according to claim 4, it is characterised in that described restricted forewarning index level determination module is specifically used
In:
Sampled value according to restricted index and default restricted forewarning index classification standard, determine each restricted index
Advanced warning grade；
When restricted index is one, using the advanced warning grade of this restricted index as restricted forewarning index grade；Work as limit
Property index processed be two and above time, using the advanced warning grade of the highest restricted index of advanced warning grade as restricted forewarning index
Grade.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108875290A (en) * | 2017-05-09 | 2018-11-23 | 深圳市环境科学研究院 | Resosurces environment loading capacity method for early warning |
| CN109447363A (en) * | 2018-11-08 | 2019-03-08 | 青海大学 | Grassland ecology method for early warning and device |
| CN112183887A (en) * | 2020-10-22 | 2021-01-05 | 中国环境科学研究院 | Water environment bearing capacity early warning index threshold value and classification standard determination method |
| CN113487174A (en) * | 2021-07-02 | 2021-10-08 | 辽宁省生态环境保护科技中心 | Water environment bearing capacity assessment early warning regulation and control method |
| CN114862062A (en) * | 2022-06-30 | 2022-08-05 | 深圳市信润富联数字科技有限公司 | Early warning method and device for environmental bearing capacity, electronic equipment and readable storage medium |
| CN115203887A (en) * | 2022-05-26 | 2022-10-18 | 中色蓝图科技股份有限公司 | Resource environment bearing capacity temporal model based on service flow engine |
| CN115376291A (en) * | 2022-08-04 | 2022-11-22 | 武汉科瑞新电气自动化有限公司 | Early warning method and system for temperature of switch cabinet and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108875290A (en) * | 2017-05-09 | 2018-11-23 | 深圳市环境科学研究院 | Resosurces environment loading capacity method for early warning |
| CN109447363A (en) * | 2018-11-08 | 2019-03-08 | 青海大学 | Grassland ecology method for early warning and device |
| CN109447363B (en) * | 2018-11-08 | 2023-05-26 | 青海大学 | Grassland ecological early warning method and grassland ecological early warning device |
| CN112183887A (en) * | 2020-10-22 | 2021-01-05 | 中国环境科学研究院 | Water environment bearing capacity early warning index threshold value and classification standard determination method |
| CN113487174A (en) * | 2021-07-02 | 2021-10-08 | 辽宁省生态环境保护科技中心 | Water environment bearing capacity assessment early warning regulation and control method |
| CN113487174B (en) * | 2021-07-02 | 2024-05-07 | 辽宁省生态环境保护科技中心 | Early warning regulation and control method for water environment bearing capacity assessment |
| CN115203887A (en) * | 2022-05-26 | 2022-10-18 | 中色蓝图科技股份有限公司 | Resource environment bearing capacity temporal model based on service flow engine |
| CN114862062A (en) * | 2022-06-30 | 2022-08-05 | 深圳市信润富联数字科技有限公司 | Early warning method and device for environmental bearing capacity, electronic equipment and readable storage medium |
| CN115376291A (en) * | 2022-08-04 | 2022-11-22 | 武汉科瑞新电气自动化有限公司 | Early warning method and system for temperature of switch cabinet and storage medium |
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