CN108984830A - A kind of building efficiency evaluation method and device based on FUZZY NETWORK analysis - Google Patents
A kind of building efficiency evaluation method and device based on FUZZY NETWORK analysis Download PDFInfo
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Abstract
The invention discloses a kind of building efficiency evaluation methods based on FUZZY NETWORK analysis, it include: the input that processing unit receives architectural entity information, and different types of building efficiency parameter is obtained by more granularity efficiency evaluation modeling methods, the parameter is that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes, each described level-one building index includes that multiple second levels build index；The processing unit is compared by the matching two-by-two that the api interface that FUZZY NETWORK analyzes FANP carries out the building efficiency parameter, and the comparison result is stored to comparison data library；In conjunction with the comparison result, the relative weighting of the building efficiency parameter is calculated by network analysis ANP algorithm；In conjunction with the multiple building energy efficiency indexes and relative weighting, scored by all building efficiencies of the ranking operation to the architectural entity.
Description
Technical field
The invention belongs to information technology fields, and in particular, to a kind of building efficiency evaluation based on FUZZY NETWORK analysis
Method and device.
Background technique
In the case where energy crisis increasingly sharpens the dual background that gets worse with environmental disruption, energy conservation and environmental protection becomes 21 century generation
One of the High-Interest Object of various countries of boundary development.Building energy consumption has become current the first rich and influential family of energy consumption, such as the ratio in the U.S. is
37%, European ratio is 41%, and Chinese ratio is 35%, and most buildings possess more low efficiency table
It is existing.In order to promote building efficiency, China promulgated " green building assessment standard " (GB/T50378-2014), January 1 in 2015
It rises day and implements.The optimization for building efficiency will reduce energy substance consumption, and alleviating energy crisis improves problem of environmental pollution, push
Socio-economic development.
In recent years, how domestic and foreign scholars will improve always building efficiency as one of research hotspot.According to existing research,
Building not energy efficient reason can sum up are as follows: building design stage factor, construction stage factor, the constructing operation stage because
Element.With the above problem, the limitation of traditional architecture industry is gradually highlighted.
Existing research exists following insufficient: A) energy efficiency indexes weight is overly dependent upon expert's priori knowledge, and calculated result lacks
Weary objectivity and accuracy；B it) is only completed the whole efficiency evaluation of building, does not complete the local efficiency of the components such as room, air-conditioning equipment
Evaluation；C) efficiency evaluation model structure is fixed, and is only applicable to certain types of building, and existing evaluation result can not be disclosed really
Build not energy efficient origin mechanism.
Summary of the invention
In view of this, the present invention provides a kind of building efficiency evaluation method and device based on FUZZY NETWORK analysis, it will
Building efficiency overall merit is abstracted as decision-making problem of multi-objective, calculates energy efficiency indexes relative weighting using fuzzy analytic net process,
That multi objective, the building efficiency evaluation model of more granularities and weight calculation result will provide will be more objective, accurately build efficiency evaluation
As a result, profound disclose builds the not energy efficient origin cause of formation, good practical basis is provided to build the subsequent optimization of efficiency.
The embodiment of the present invention provides a kind of building efficiency evaluation method based on FUZZY NETWORK analysis, comprising:
Processing unit receives the input of architectural entity information, and obtains inhomogeneity by more granularity efficiency evaluation modeling methods
The building efficiency parameter of type, the parameter are that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes, wherein institute
The relationship stated between level-one building index and second level building index is tree form data structure, each described level-one building refers to
Mark builds index comprising multiple second levels；
The processing unit by the api interface that FUZZY NETWORK analyzes FANP carry out the building efficiency parameter two-by-two
With comparing, and the comparison result is stored to comparison data library；
The processing unit calculates the building efficiency parameter in conjunction with the comparison result, by network analysis ANP algorithm
Relative weighting；
The processing unit is in conjunction with the building energy efficiency indexes and relative weighting, by ranking operation to the architectural entity
All building efficiencies score.
Optionally, the processing unit carries out the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Matching two-by-two compare, and the comparison result is stored to comparing database, comprising:
The semantic weight set of building efficiency parameter is obtained, the semantic weight set is for indicating the building efficiency ginseng
Several important levels；
Triangular Fuzzy Number function is constructed, it is by the Triangular Fuzzy Number function that semantic weight set progress is important etc.
Grade quantization operation determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building is selected in the building efficiency parameter
Energy efficiency indexes are comparison reference, and remaining all building energy efficiency indexes of same level are carried out with the building energy efficiency indexes respectively
Matching is compared two-by-two, and acquisition is described to match comparison result two-by-two；
To successively select remaining construction energy efficiency indexes for comparison reference in the building efficiency parameter, repeat it is described two-by-two
With comparison procedure, obtain using different building energy efficiency indexes as the matching comparison result two-by-two of comparison reference,
All comparison results of matching two-by-two are stored with a matrix type to comparing database.
Optionally, the processing unit calculates the building energy by network analysis ANP algorithm in conjunction with the comparison result
Imitate the relative weighting of parameter, comprising:
The comparison result two-by-two is extracted, the part that each described level-one builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the level-one building index in conjunction with the partial weight of all level-one building indexs；
The comparison result two-by-two is extracted, the part that each described second level builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the second level building index in conjunction with the partial weight of all second level building indexs；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation,
Hypermatrix after obtaining operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is institute
State the relative weighting of second level building index.
Optionally, the processing unit is in conjunction with the building energy efficiency indexes and relative weighting, by ranking operation to described
All building efficiencies of architectural entity score, comprising:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, described in acquisition
Second level builds the scoring of architectural entity belonging to energy efficiency indexes.
The embodiment of the present invention also provides a kind of building efficiency evaluation device based on FUZZY NETWORK analysis, comprising:
Modeling unit for receiving the input of architectural entity information, and is modeled by more granularity efficiency evaluations and obtains difference
The building efficiency parameter of type, the parameter are that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes, wherein
Relationship between the level-one building index and second level building index is tree form data structure, each described level-one building
Index includes that multiple second levels build index；
Comparing unit, the api interface for analyzing FANP by FUZZY NETWORK carry out the building efficiency parameter two-by-two
Matching is compared, and the comparison result is stored to comparing database；
Weight calculation unit, for calculating the building efficiency by network analysis ANP algorithm in conjunction with the comparison result
The relative weighting of parameter；
Score unit, in conjunction with it is described building energy efficiency indexes evaluation result and the evaluation result relative weighting,
It is scored by all building efficiencies of the ranking operation to the architectural entity.
Optionally, the comparing unit carries out the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Matching two-by-two compare, and the comparison result is stored to comparing database, comprising:
The semantic weight set of building efficiency parameter is obtained, the semantic weight set is for indicating the building efficiency ginseng
Several important levels；
Triangular Fuzzy Number function is constructed, it is by the Triangular Fuzzy Number function that semantic weight set progress is important etc.
Grade quantization operation determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building is selected in the building efficiency parameter
Energy efficiency indexes are comparison reference, and remaining all building energy efficiency indexes of same level are carried out with the building energy efficiency indexes respectively
Matching is compared two-by-two, and acquisition is described to match comparison result two-by-two；
To successively select remaining construction energy efficiency indexes for comparison reference in the building efficiency parameter, repeat it is described two-by-two
With comparison procedure, obtain using different building energy efficiency indexes as the matching comparison result two-by-two of comparison reference,
All comparison results of matching two-by-two are stored with a matrix type to comparing database.
Optionally, the weight calculation unit is in conjunction with the comparison result, by building described in the calculating of network analysis ANP algorithm
Build the relative weighting of efficiency parameter, comprising:
The comparison result two-by-two is extracted, the part that each described level-one builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the level-one building index in conjunction with the partial weight of all level-one building indexs；
The comparison result two-by-two is extracted, the part that each described second level builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the second level building index in conjunction with the partial weight of all second level building indexs；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation,
Hypermatrix after obtaining operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is institute
State the relative weighting of second level building index.
Optionally, the scoring unit is in conjunction with the building energy efficiency indexes and relative weighting, by ranking operation to described
All building efficiencies of architectural entity score, comprising:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, described in acquisition
Second level builds the scoring of architectural entity belonging to energy efficiency indexes.
The embodiment of the present invention also provides a kind of building efficiency evaluation device based on FUZZY NETWORK analysis, described device packet
It includes: processor and the memory for storing the computer program that can be run on a processor；Wherein, the processor is used for
When running the computer program, the above-mentioned building efficiency evaluation method based on FUZZY NETWORK analysis is executed.
The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer program, the meter
It is realized when calculation machine program is executed by processor such as the step of the above-mentioned building efficiency evaluation method based on FUZZY NETWORK analysis.
The method and device of the embodiment of the present invention has the advantage that
The conversion method and device for the energy simulation model that the embodiment of the present invention discloses, the essence of model conversion is returned
It receives and solves the problems, such as that current simulation of energy consumption model construction is inaccurate, life with polygon operation to support for geometric operation problem
At more accurate energy simulation model, more real objective simulation of energy consumption data are provided for building efficiency evaluation.
Detailed description of the invention
Fig. 1 is to build Energy Efficiency Analysis flow diagram in the prior art；
Fig. 2 is the building efficiency evaluation method flow schematic diagram based on FUZZY NETWORK analysis in the embodiment of the present invention；
Fig. 3 is another flow diagram of building efficiency evaluation method based on FUZZY NETWORK analysis in the embodiment of the present invention；
Fig. 4 is the building efficiency evaluation apparatus structure schematic diagram based on FUZZY NETWORK analysis in the embodiment of the present invention.
Specific embodiment
In order to keep the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, to this hair
It is bright to be further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and do not have to
It is of the invention in limiting.In addition, as long as technical characteristic involved in the various embodiments of the present invention described below is each other
Between do not constitute conflict and can be combined with each other.
Efficiency evaluation is built as a kind of method for assessing energy for building efficiency, will be played the part of in terms of building energy efficiency increasingly
Important role (the green building standard in the China e.g. and external LEED, BREEAM and GreenStar).Influence building efficiency
Factor it is very much, comprising many aspects such as design, construction, operational management, there are also in Different climate region energy for building difference,
Service object's difference of different building types.In this regard, engineers design goes out different energy efficiency indexes, accurately quantization building is in body
The performance of type design, building enclosure, Architectural Equipment, indoor comfortable and health etc..Building efficiency evaluation result can help
Designer and building manager analyze the key element of green building efficiency and the conductive suggestion of building efficiency, improve building energy
Source utilization efficiency reduces energy waste.
In conclusion playing most important effect to building efficiency optimization based on the efficiency evaluation of energy simulation.It
Advantage be embodied in effect: (1) in the design phase, building designers pass through simulation of energy consumption evaluation of result architectural design model
Efficiency optimizes the design of buildings model and the use of construction material；(2) it is utilized in operation phase, building manager and engineer
The efficiency of energy simulation interpretation of result distinct device control strategy and building renovation strategy reaches optimal efficiency optimization knot
Fruit.
Efficiency Optimizing Flow based on energy simulation and efficiency evaluation is as shown in Figure 1.In the simulation of energy consumption stage, engineering
Building Information Model is converted to energy simulation model by teacher, generates energy consumption mould using corresponding kernel (e.g.EnergyPlus)
Quasi- result.In the efficiency evaluation stage, computer not only needs to complete the calculating of single energy efficiency indexes, also needs that multiple efficiencies is combined to refer to
Mark completes the overall merit of building efficiency.The present Research of two key points is as follows:
As shown in Figure 1, the overall merit of building efficiency need to use multiple relevant energy efficiency indexes, point of energy efficiency indexes weight
Analysis and calculating are key point and difficult point.Domestic and foreign scholars have carried out correlative study and have obtained certain achievement, and the LEED in the U.S. is commented
Valence system completes green building overall merit using 6 energy efficiency indexes (the e.g. energy and atmosphere, water-use efficiency etc.), Britain
BREEAM appraisement system completes evaluation using 9 energy efficiency indexes, and Australian Green Star system uses 8 energy efficiency indexes
Evaluation is completed, the Green Mark system of Singapore completes evaluation using 5 energy efficiency indexes.
In addition, multi-objective decision algorithm (Multiple Criteria Decision Making) is also by domestic and foreign scholars
For building the analysis and calculating of energy efficiency indexes weight, the scholars such as Endong are based on TOPSIS method and analyze multiple building energy efficiency indexes
The weight of (e.g.EUI, CDDE, HDDE etc.) completes building efficiency overall merit.The scholars such as Geng use analytic hierarchy process (AHP)
(Analytic Hierarchy Process, AHP) calculates the weight of office's Energy Saving Strategy, mixed economy, environment, technology etc.
The index optimization building energy conservation effect of aspect.The scholars such as Kabak use Network Analysis Method (Analytic Network
Process, ANP) evaluation building efficiency, which includes 7 indexs such as weather, architectural design, construction material.
In view of this, the embodiment of the invention provides a kind of new building efficiency evaluation sides based on FUZZY NETWORK analysis
Method is as follows:
Embodiment one
Scene modeling (Scenario Modelling) is also known as more granularity efficiency evaluation modeling methods, is taught by Finland
A kind of mathematical model for novel building efficiency evaluation that ODonnell is proposed, scene modeling, which provides a kind of entirety, to carry out building and comments
(building function index, energy consumption index, building load index, device efficiency index and laws and regulations refer to the 5 class indexs estimated
Mark), and define and be related to the relevant criterion of building energy consumption, such as correlation, buildings, building index and the number between index
Definition and framework according to stream etc..Its specific related introduction is see correlative theses introduction (Scenario modelling:A
holistic environmental and energy management method for building operation
Optimization, Energy and Buildings), it is described again here.
However, there is no solve the problems, such as associated weight for scene modeling method.Therefore, by combination field in the embodiment of the present invention
The problem of method of scape modeling and FUZZY NETWORK analysis calculates associated weight jointly.
As shown in Fig. 2, the embodiment of the present invention provides a kind of building efficiency evaluation method based on FUZZY NETWORK analysis, packet
It includes:
S201, processing unit receive the input of architectural entity information, and are obtained by more granularity efficiency evaluation modeling methods
Different types of building efficiency parameter, the parameter are that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes,
Wherein, the relationship between the level-one building index and second level building index is tree form data structure, each described one
Grade building index includes that multiple second levels build index；
Architectural entity information includes but is not limited to all types of building data, such as Building Information Model BIM data, building
The data such as the real time datas such as interior temperature, the humidity captured by respective sensor, acquisition data, Architecural Physics area, size.
Wherein, level-one building energy efficiency indexes may include 5 classes, be building function index, energy consumption index, building respectively
Load index, device efficiency index and laws and regulations index, every one kind level-one building energy efficiency indexes can correspond to multiple second levels again
Build energy efficiency indexes, such as humidity, temperature and illumination index, body-sensing comfort level index, overall power consumption index, renewable energy
Multiple indexs such as source index, heating load index, cooling load index, AHU section heating index, gas discharge index.Relative indicatrix
Framework is as shown in Figure 3.
S202, the processing unit carry out the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Matching is compared two-by-two, and the comparison result is stored to comparing database；
Wherein, the processing unit carries out the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Matching is compared two-by-two, and the comparison result is stored to database is compared, and is specifically as follows:
The semantic weight set of building efficiency parameter is obtained, the semantic weight set is for indicating the building efficiency ginseng
Several important levels；
Triangular Fuzzy Number function is constructed, it is by the Triangular Fuzzy Number function that semantic weight set progress is important etc.
Grade quantization operation determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building is selected in the building efficiency parameter
Energy efficiency indexes are comparison reference, and remaining all building energy efficiency indexes of same level are carried out with the building energy efficiency indexes respectively
Matching is compared two-by-two, and acquisition is described to match comparison result two-by-two；
To successively select remaining construction energy efficiency indexes for matching reference in the building efficiency parameter, repeat it is described two-by-two
With process, obtaining with different building energy efficiency indexes be matching comparison result two-by-two that matching refers to, by it is described it is all two-by-two
It is stored with a matrix type with comparison result to comparing database.
Network Analysis Method (ANP, the Analytic Network Process) is analytic hierarchy process (AHP) (AHP, the
Analytic Hierarchy Process) rely on and feedback problem in extension, be it is a kind of can be used to handle have rely on
With the quantitative relationship of the complicated decision-making problems of feedback relationship.
Fuzzy analytic net process (F-ANP, the Fuzzy Analytic Network Process) is Network Analysis Method
Extension in uncertain and ambiquity problem is a kind of energy processing uncertain (Uncertainty) and ambiquity
(Vagueness) quantitative method of challenge.Building energy consumption overall merit is a sufficiently complex system problem again, right
Can the evaluation of one complex object accurate, not only by the expert group selected and the index system for being evaluated characteristics of objects
Influence, also influenced by selected evaluation method, to same group objects using distinct methods evaluate its conclusion there may be
Larger difference, so, for these reasons, in view of the advantage and disadvantage of various evaluation methods, the embodiment of the present invention is attempted to propose fuzzy
Network Analysis Method is applied in fuzzy comprehensive evoluation by the concept of Network Analysis Method using the theory of Triangular Fuzzy Number, to having
The complicated structure problem for relying on feedback carries out assigning power evaluation, and fuzzy comprehensive evoluation and Network Analysis Method are organically combined.
When carrying out decision using AHP, 4 steps can be divided into:
(1) relationship in analysis system between each factor establishes the recursive hierarchy structure of system；
(2) importance to each element of same level about a certain criterion in a upper level is compared two-by-two, construction
Multilevel iudge matrix two-by-two；
(3) it is calculated by comparison element by judgment matrix for the relative weighting of the criterion；
(4) each layer element is calculated to the synthetic weight of aims of systems, and is ranked up.
The decision principle of ANP and analytic hierarchy process (AHP) are essentially identical, it is unique unlike the former establishes is network structure mould
Type, and what the latter established is hierarchy Model.Since network structure model will weighed more than hierarchy Model complexity
It is overlapped into aspect, Network Analysis Method has been applied to more advanced mathematical knowledge, wherein important concept is hypermatrix.
The network that ANP is used is by the influence between ingredient (component, or referred to as level) and coordinator
(influence) form, ingredient therein indicates with O, mutual influence with → indicate, ingredient is again by constituent
Element (element) composition, there may also be influencing each other between element, the element of an ingredient can with another at
Point element between influence each other relationship, it is various influence each other relationship with → indicate, and A → B expression composition (or
Element) A is influenced by ingredient (perhaps element) B or ingredient (or element) B influences ingredient A.Here so-called ingredient A shadow
Ingredient B is rung, refers to that each element of ingredient A makes a difference contribution to each element of ingredient B.Wherein ingredient itself is to certainly
Oneself old influence relationship is feedback relationship (feedback).
Broadly, ANP includes two stages: first is the construction of network, and second is the calculating of element weights.For structure
Make institute's correlate between the structure consideration element of problem.When the element Y in an ingredient is relied in another ingredient
Element X indicates this relationship with from an arrow from ingredient X to Y.The calculating of all these relationships compared with honouring and
Hypermatrix, hypermatrix are the influence matrixes between element.Hypermatrix transfinites power to calculate whole weight.
Fuzzy analytic net process FANP is extension of the Network Analysis Method in uncertain and ambiquity problem, is a kind of energy
Handle the quantitative method of uncertain (Uncertainty) and ambiquity (Vagueness) challenge.FUZZY NETWORK analysis
The decision principle of method is the decision principle of Excavation Cluster Based on Network Analysis method and fuzzy overall evaluation, is by traditional Network Analysis Method and mould
Paste overall merit combines the new systematic analytic method of one kind to be formed.Its basic thought is:
1. the form for the Triangular Fuzzy Number of judgment matrix two-by-two that computer obtains is synthesized, one fuzzy two is formed
Two judgment matrixs；
2. according to the property of Triangular Fuzzy Number and certain operation method, the operation of Excavation Cluster Based on Network Analysis method hypermatrix,
The weight vectors for determining fuzzy judgment matrix handle fuzzy weight vector according to the thought of decision, form a friendship
The weight vectors decision analysis process of mutual formula.
S203, the processing unit calculate the building efficiency by network analysis ANP algorithm in conjunction with the comparison result
The relative weighting of parameter；
Wherein, the processing unit calculates the building efficiency by network analysis ANP algorithm in conjunction with the comparison result
The relative weighting of parameter, is specifically as follows:
The comparison result two-by-two is extracted, the part that each described level-one builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the level-one building index in conjunction with the partial weight of all level-one building indexs；
The comparison result two-by-two is extracted, the part that each described second level builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the second level building index in conjunction with the partial weight of all second level building indexs；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation,
Hypermatrix after obtaining operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is institute
State the relative weighting of second level building index.
S204, the processing unit are built by ranking operation to described in conjunction with the building energy efficiency indexes and relative weighting
All building efficiencies for building entity score.
Wherein, the processing unit is built by ranking operation to described in conjunction with the building energy efficiency indexes and relative weighting
All building efficiencies for building entity score, and are specifically as follows:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, described in acquisition
Second level builds the scoring of architectural entity belonging to energy efficiency indexes.
In the embodiment of the present invention, building efficiency evaluation is a multi objective, more granularity problems, and the embodiment of the present invention combines more
Granularity builds the network structure of energy efficiency model (scenario modelling) and FUZZY NETWORK analysis, and building multi objective efficiency is commented
The mathematical model of valence problem.According to the two-level configuration of more granularities building energy efficiency model, 5 first class index of the model specification are each
A first class index includes multiple second level energy efficiency indexes, and based on software platforms such as matlab, according to practical building demand building one
The second level energy efficiency indexes (such as temperature and humidity, illumination index and body-sensing comfort level index) of series, and establish they and first class index
Relationship.To realize the common evaluation for building whole efficiency and local efficiency, the embodiment of the present invention need to be associated with second level energy efficiency indexes with
The architectural object of more granularities, such as: the general comfort degree of whole building and the local comfort degree in each room are evaluated.Meanwhile the present invention
Embodiment Excavation Cluster Based on Network Analysis method ANP comparison of design table (pair-wise) is established with probability for main criterion, with one of energy
Imitating index is time criterion, and the relative Link Importance for carrying out other energy efficiency indexes compares, i.e., other energy efficiency indexes are to this energy efficiency indexes
The influence degree size of probability of happening carries out different degree comparison.The purpose of Pair-wise contrast table be each energy efficiency indexes of quantization or
Influencing each other between adjacent layer time completes the table for auxiliary efficiency expert, and the embodiment of the present invention uses fuzzy logic theory
It realizes priori knowledge accurately digitized description, and calculates hypermatrix, weight matrix, weighting hypermatrix, by weighting hypermatrix
Solution obtain the relative weighting of building efficiency, solve that current simulation of energy consumption model construction is inaccurate, evaluation result is not objective enough
The technical issues of sight, generates more accurate energy simulation model, provides more real objective energy for building efficiency evaluation
Analogue data is consumed, meanwhile, the method for realizing the embodiment of the present invention by computer program improves the effect of building efficiency modeling
Rate enables building efficiency evaluation algorithm to be promptly adapted to a variety of different building energy efficiency evaluation systems, solves needs
Multiple stage computers carry out the technical issues of building efficiency evaluation of the modeling of different modes to solve different buildings, improve meter
Calculation machine treatment effeciency, reduces computer disposal resource, and improves the levels of precision of building energy efficiency model.
Embodiment two
The embodiment of the invention provides the building efficiency evaluation methods that another kind is analyzed based on FUZZY NETWORK.
As shown in figure 3, the method flow of the embodiment of the present invention is as follows:
S301, scene index evaluation is carried out using multinomial criterion (criteria)；
By the calculation method of scene modeling, architectural evaluation is broken down into a kind of index (performance aspects
In the first level) and two class indexs (performance objectives in the second level).?
Scape modeling provides a kind of index of above-mentioned five referred to kind, which can different demands and active traffic based on building
Dynamic adjusts.In ANP model, evaluation index is criterion, and buildings are then considered as sub- criterion.Criterion numeral is up to
5, such as U=﹛ U1,U2,U3,U4,U5﹜, U1-U5Building function index, energy consumption index, building load is respectively defined as to refer to
Mark, device efficiency index and laws and regulations index.Each criterion is made of multiple sub- criterion again, such as Ui=﹛ Ui1,Ui2,
Ui3,…,Uij﹜ [j=1,2,3 ..., n].ANP model establishes criterion and sub- criterion according to different complexity and important level
Correlation.The correlation can be used for calculating the weight of sub- criterion.It should be noted that in embodiments of the present invention,
Those skilled in the art can be clearly understood that the criterion and sub- criterion are not artificial criterion in general sense, but can be by
Data flow and/or data information that computer obtains after modeling technique is handled, for subsequent progress weight processing, can also
To be referred to as to build energy efficiency indexes, technical spirit is the processing of data, obtains objective data for subsequent building expert with this
It is analyzed, and non-artificial operation.As shown in Fig. 2, correlation can be divided into two classes:
1. the sub- criterion of criterion Ui and another criterion UjSub- criterion carry out interaction；
2. the interaction between the sub- criterion of the same criterion Ui.
S302, the matching operation two-by-two for carrying out criterion index；
Compared with traditional ANP carries out the matching operation of criterion index, criterion index pairing provided in an embodiment of the present invention
Operating method can reduce artificial influence.In method provided in an embodiment of the present invention, criterion index matching operation only needs to build
It builds expert and assesses another criterion of a criterion/sub- criterion impression/sub- criterion degree.For example, E (Ui→Uj)or E(Uik→
Ujk).E indicates the mutual influence/relationship of the two.The five effect level tables 1 designed for building expert:
Wherein, E1And E5With clearly boundary.E1Indicate UiWith UjWill not have an impact each other (as building closing isolation is empty
Between and outside air)；E5Indicate the influence (100% influence) of oneself and oneself, such as E (Ui→Ui)。
It matches matrix and uses FUZZY NETWORK theory.FUZZY NETWORK theory is a kind of for solving not knowing in engineer application
Property and ambiguous problem.FUZZY NETWORK theory can classify the function etc. of member, and assign opposite numerical value (between
Between 0-1).
Has Triangular Fuzzy Number in FUZZY NETWORK theory.Triangular Fuzzy Number can be expressed asSuch as formula
(1):
What l≤m here≤u, l and u were indicated is the lower bound of M support and the upper bound, m are the intermediate values of M.In Triangular Fuzzy Number
In, l and u illustrate the fog-level of judgement, and u-l is bigger, and expression fog-level is higher, and the smaller mark fog-level of u-l is lower,
As l=m=u, M is usually non-fuzzy number, and also explanation judges between right and wrong fuzzy.
The embodiment of the present invention is provided with 5 kinds of different verbal descriptions and corresponding fuzzy number grade, as shown in table 4:
Table 4
Assuming that policymaker is with linguistic weight set W,
W=﹛ ALI；VSLI；SLI；WLI；EI；WMI；SMI,VSMI；AMI ﹜, ALI (absolutely less here
Important) indicate absolutely inessential, VSLI (very strongly lessimportant) indicates strong inessential, SLI
(strongly less important) indicates strong inessential, and WLI (weakly less important) is indicated slightly not
Important, EI (equally important) indicates (such as E of equal importance1vs E1), WMI (weakly more important)
Indicate slightly important (such as E2vs E1), SMI (strongly more important) indicates strong important (such as E3vs
E1), VSMVI (very strongly more important) indicates strongly important (such as E3vs E1), AMI
(absolutely more important) indicates absolutely essential (such as E5vs E1)。
One typical pairing matrix is as shown in table 5:
Table 5
Table 5 is with U1To refer to, by U1-UnSuccessively with U1Compared the matrix obtained two-by-two.Wherein, l11Identify U1With U1
The l value being compared, l21Indicate U2With U1The l value compared, and so on, with different UnValue refers to, and can obtain n pairing
Matrix.
S303, the relative weighting for calculating different criterion；
The relative weighting of different criterion is calculated in this step using ANP model, specific as follows:
Vector can be used for all pairing matrixes of table 5
W=(w1, w2... ..., wn)TTo indicate.And relevant ratio wi/wjMeet the inequality of formula (2) expression:
Variable x in formula (1) can use wi/wjTo substitute (such as formula (3)):
Wherein, wiOr wjThat is UiOr UjPartial weight.
Calculate the Maximum characteristic root (such as formula (4)) of judgment matrix A:
In ANP model method, need to solve whole weights of all level-one criterion, the whole weight is with judgment matrix
A is indicated, and Maximum characteristic root λ is denoted as the element (i.e. weight vectors) of judgment matrix A after normalization, for level-one criterion
Total weight matrix A (i.e. judgment matrix A) for, can be indicated by formula (5):
Correspondingly, the matrix W of second level criterionijIt can also carry out solving by method as above and obtain, and second level criterion is total
Weight matrix WijIt for A, paired comparisons and is asked two-by-two by second level criterion (sub-criteria) and second level criterion
Solution weight can obtain, and element accordingly expands for the total weight matrix A of level-one criterion.As formula (6) indicate:
Dot product will be carried out between the total weight matrix A of level-one criterion and the total weight B of second level criterion, hypermatrix can be obtainedW, such as public
Shown in formula (7):
Hypermatrix is subjected to Limit Operation (such as formula (8)), can be obtained the relative weighting of the sub- criterion of each second level:
Wherein, c1-cmIt is corresponding in turn to (U11,U12,…U1n,U21,U22,…U2n…Umn) relative weighting.
S304, the final score that different level-one criterion are calculated using relative weighting.
Level-one criterion final score D is the weighted value of the sub- criterion of different second levels and weight, as shown in formula (9):
Wherein, siFor sub- criterion score value, ciFor the relative weighting of sub- criterion.
By calculating the final score of level-one criterion, all kinds of indexs of architectural entity can be objectively evaluated.
Embodiment three
As shown in figure 4, the embodiment of the invention discloses a kind of building efficiency devices based on FUZZY NETWORK analysis, comprising:
Modeling unit 41 obtains not for receiving the input of architectural entity information, and by the modeling of more granularity efficiency evaluations
The building efficiency parameter of same type, the parameter are that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes,
In, the relationship between the level-one building index and second level building index is tree form data structure, each described level-one
Building index includes that multiple second levels build index；
Comparing unit 42, the api interface for analyzing FANP by FUZZY NETWORK carry out the two of the building efficiency parameter
Two matchings are compared, and the comparison result is stored to comparing database；
Wherein, the comparing unit 42 carries out the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Matching two-by-two compare, and the comparison result is stored to comparing database, can be with are as follows:
The semantic weight set of building efficiency parameter is obtained, the semantic weight set is for indicating the building efficiency ginseng
Several important levels；
Triangular Fuzzy Number function is constructed, it is by the Triangular Fuzzy Number function that semantic weight set progress is important etc.
Grade quantization operation determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building is selected in the building efficiency parameter
Energy efficiency indexes are comparison reference, and remaining all building energy efficiency indexes of same level are carried out with the building energy efficiency indexes respectively
Matching is compared two-by-two, and acquisition is described to match comparison result two-by-two；
To successively select remaining construction energy efficiency indexes for matching reference in the building efficiency parameter, repeat it is described two-by-two
With process, obtaining with different building energy efficiency indexes is the matching comparison result two-by-two for matching reference,
All comparison results of matching two-by-two are stored with a matrix type to comparing database.
Weight calculation unit 43, for calculating the building energy by network analysis ANP algorithm in conjunction with the comparison result
Imitate the relative weighting of parameter；
Wherein, the weight calculation unit 43 is in conjunction with the comparison result, by building described in the calculating of network analysis ANP algorithm
The relative weighting of efficiency parameter is built, it can be with are as follows:
The comparison result two-by-two is extracted, the part that each described level-one builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the level-one building index in conjunction with the partial weight of all level-one building indexs；
The comparison result two-by-two is extracted, the part that each described second level builds index is calculated by ANP algorithm
Weight constructs the weight matrix of the second level building index in conjunction with the partial weight of all second level building indexs；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation,
Hypermatrix after obtaining operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is institute
State the relative weighting of second level building index.
Score unit 44, the opposite power for evaluation result and the evaluation result in conjunction with the building energy efficiency indexes
Weight, is scored by all building efficiencies of the ranking operation to the architectural entity.
Wherein, the scoring unit 44 is in conjunction with the building energy efficiency indexes and relative weighting, by ranking operation to described
All building efficiencies of architectural entity score, comprising:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, described in acquisition
Second level builds the scoring of architectural entity belonging to energy efficiency indexes.
The embodiment of the invention also provides a kind of building efficiency device based on FUZZY NETWORK analysis, described device includes:
Processor and memory for storing the computer program that can be run on a processor；Wherein, the processor is for transporting
When the row computer program, the above-mentioned building efficiency evaluation method based on FUZZY NETWORK analysis is executed.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with the executable finger of computer
It enables, which is used to execute the above-mentioned building efficiency evaluation method based on FUZZY NETWORK analysis.
It should be understood that the size of the serial number of each process is not meant to execution sequence in the various embodiments of the application
Successively, the execution sequence of each process should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present application
Constitute any restriction.
Those of ordinary skill in the art may be aware that mould described in conjunction with the examples disclosed in the embodiments of the present disclosure
Block and method and step can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
Scope of the present application.
It is apparent to those skilled in the art that for convenience and simplicity of description, the device of foregoing description,
The specific work process of device and module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
The various pieces of this specification are all made of progressive mode and are described, same and similar portion between each embodiment
Dividing may refer to each other, and what each embodiment introduced is and other embodiments difference.Especially for device and dress
For setting embodiment, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to method reality
Apply the explanation of example part.
Finally, it should be understood that being not intended to the foregoing is merely the preferred embodiment of technical scheme
Limit the protection scope of the application.Obviously, those skilled in the art can carry out various modification and variations without de- to the application
From scope of the present application.If these modifications and variations of the application belong to the range of the claim of this application and its equivalent technologies
Within, then any modification, equivalent replacement, improvement and so on, should be included within the scope of protection of this application.
Claims (10)
1. a kind of building efficiency evaluation method based on FUZZY NETWORK analysis characterized by comprising
Processing unit receives the input of architectural entity information, and different types of by the acquisition of more granularity efficiency evaluation modeling methods
Efficiency parameter is built, the parameter is that multiple level-ones build energy efficiency indexes and multiple second levels build energy efficiency indexes, wherein described one
Relationship between grade building index and second level building index is tree form data structure, each described level-one builds index packet
Index is built containing multiple second levels；
The processing unit carries out the ratio of matching two-by-two of the building efficiency parameter by the api interface that FUZZY NETWORK analyzes FANP
Compared with, and the comparison result is stored to comparing database；
The processing unit calculates the phase of the building efficiency parameter by network analysis ANP algorithm in conjunction with the comparison result
To weight；
The processing unit is in conjunction with the building energy efficiency indexes and relative weighting, by ranking operation to the institute of the architectural entity
There is building efficiency to score.
2. the method according to claim 1, wherein the processing unit analyzes FANP's by FUZZY NETWORK
The matching two-by-two that api interface carries out the building efficiency parameter is compared, and the comparison result is stored to database is compared, and is wrapped
It includes:
Determine the semantic weight set of building efficiency parameter, the semantic weight set is for indicating the building efficiency parameter
Important level；
Triangular Fuzzy Number function is constructed, the semantic weight set is carried out by important level amount by the Triangular Fuzzy Number function
Change operation, determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building efficiency is selected in the building efficiency parameter
Index is comparison reference, by remaining all building energy efficiency indexes at the same level respectively with building energy efficiency indexes progress two-by-two
With comparing, acquisition is described to match comparison result two-by-two；
Successively select remaining construction energy efficiency indexes for comparison reference in the building efficiency parameter, repetition is described to match ratio two-by-two
Compared with process, obtain using different building energy efficiency indexes as the matching comparison result two-by-two of comparison reference,
All comparison results of matching two-by-two are stored with a matrix type to comparing database.
3. according to the method described in claim 2, it is characterized in that, the processing unit passes through net in conjunction with the comparison result
Network analysis ANP algorithm calculates the relative weighting of the building efficiency parameter, comprising:
The comparison result two-by-two is extracted, the partial weight that each described level-one builds index is calculated by ANP algorithm,
In conjunction with the partial weight of all level-one building indexs, the weight matrix of the level-one building index is constructed；
The comparison result two-by-two is extracted, the partial weight that each described second level builds index is calculated by ANP algorithm,
In conjunction with the partial weight of all second level building indexs, the weight matrix of the second level building index is constructed；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation, is obtained
Hypermatrix after operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is described two
The relative weighting of grade building index.
4. the method according to claim 1, wherein the processing unit is in conjunction with the building energy efficiency indexes and phase
To weight, scored by all building efficiencies of the ranking operation to the architectural entity, comprising:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, the second level is obtained
Build the scoring of architectural entity belonging to energy efficiency indexes.
5. a kind of building efficiency evaluation device based on FUZZY NETWORK analysis characterized by comprising
Modeling unit for receiving the input of architectural entity information, and is modeled by more granularity efficiency evaluations and obtains different type
Building efficiency parameter, the parameter is that multiple level-ones build energy efficiency indexes and multiple second levels and build energy efficiency indexes, wherein described
The relationship that level-one is built between index and second level building index is tree form data structure, each described level-one builds index
Index is built comprising multiple second levels；
Comparing unit, the api interface for analyzing FANP by FUZZY NETWORK carry out the matching two-by-two of the building efficiency parameter
Compare, and the comparison result is stored to comparing database；
Weight calculation unit, for calculating the building efficiency parameter by network analysis ANP algorithm in conjunction with the comparison result
Relative weighting；
Score unit, for the relative weighting of evaluation result and the evaluation result in conjunction with the building energy efficiency indexes, passes through
Ranking operation scores to all building efficiencies of the architectural entity.
6. device according to claim 5, which is characterized in that the comparing unit analyzes FANP's by FUZZY NETWORK
The matching two-by-two that api interface carries out the building efficiency parameter is compared, and the comparison result is stored to database is compared, and is wrapped
It includes:
Determine that the semantic weight set of building efficiency parameter, the semantic weight set are used to indicate the building efficiency parameter
Important level；
Triangular Fuzzy Number function is constructed, the semantic weight set is carried out by important level amount by the Triangular Fuzzy Number function
Change operation, determines the corresponding fuzzy quantization value of difference important level in the semantic weight set；
Establish the quantification levels being compared between the different building efficiency parameters；
In conjunction with the fuzzy quantization value and the quantification levels, one of building efficiency is selected in the building efficiency parameter
Index is comparison reference, and remaining all building energy efficiency indexes of same level are carried out two-by-two with the building energy efficiency indexes respectively
Matching is compared, and acquisition is described to match comparison result two-by-two；
It will successively select remaining construction energy efficiency indexes for matching reference in the building efficiency parameter, repetition is described to be matched two-by-two
Journey, obtaining with different building energy efficiency indexes is the matching comparison result two-by-two for matching reference,
All comparison results of matching two-by-two are stored with a matrix type to comparing database.
7. device according to claim 6, which is characterized in that the weight calculation unit is led in conjunction with the comparison result
Cross the relative weighting that network analysis ANP algorithm calculates the building efficiency parameter, comprising:
The comparison result two-by-two is extracted, the partial weight that each described level-one builds index is calculated by ANP algorithm,
In conjunction with the partial weight of all level-one building indexs, the weight matrix of the level-one building index is constructed；
The comparison result two-by-two is extracted, the partial weight that each described second level builds index is calculated by ANP algorithm,
In conjunction with the partial weight of all second level building indexs, the weight matrix of the second level building index is constructed；
The weight matrix of the weight matrix of level-one building index and second level building index is subjected to point multiplication operation, is obtained
Hypermatrix after operation；
The hypermatrix is subjected to power Limit Operation, takes out any one column in the hypermatrix, the column element is described two
The relative weighting of grade building index.
8. device according to claim 5, which is characterized in that the scoring unit is in conjunction with the building energy efficiency indexes and phase
To weight, scored by all building efficiencies of the ranking operation to the architectural entity, comprising:
Obtain each described corresponding evaluation result of two-level index grade；
Each two-level index is corresponded into score value multiplied by the corresponding relative weighting of the two-level index and is summed, the second level is obtained
Build the scoring of architectural entity belonging to energy efficiency indexes.
9. it is a kind of based on FUZZY NETWORK analysis building efficiency evaluation device, which is characterized in that described device include: processor and
For storing the memory for the computer program that can be run on a processor；Wherein, the processor by run it is described based on
When calculation machine program, perform claim requires 1 to 4 described in any item building efficiency evaluation methods based on FUZZY NETWORK analysis.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
It is realized when being executed by processor such as the building efficiency evaluation side of any of claims 1-4 based on FUZZY NETWORK analysis
The step of method.
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