CN105447257A - Evidence reasoning analysis algorithm and entropy weight based air conditioner starting temperature limit value simulation method - Google Patents

Abstract

The invention discloses an evidence reasoning analysis algorithm and entropy weight based air conditioner starting temperature limit value simulation method. The method is implemented by the following steps of: 1) determining an air conditioner starting temperature limit value range and dividing the air conditioner starting temperature limit value range into a finite number of intervals; 2) identifying factors influencing an air conditioner starting temperature limit value; 3) constructing an air conditioner starting temperature limit value interval credibility matrix; 4) calculating weights of the factors influencing the air conditioner starting temperature limit value according to an entropy weight principle; 5) performing air conditioner starting temperature limit value interval comprehensive credibility synthesis with an evidence reasoning analysis algorithm; 6) determining an air conditioner starting temperature limit value interval at a simulation moment and taking a median of the interval as the air conditioner starting temperature limit value at the simulation moment; and 7) repeating the steps 3) to 6) to perform simulation calculation on simulation time periods hour by hour. According to the method, objective factors, subjective factors, quantitative factors and qualitative factors in the air conditioner starting temperature limit value simulation can be processed and incomplete information in the simulation also can be quantitatively processed.

Description

A kind of Income level limit value emulation mode weighed based on evidential reasoning analytical algorithm and entropy

Technical field

The invention belongs to that architectural behavior is energy-conservation, architectural environment and simulation of energy consumption field, relate to a kind of Income level limit value emulation mode based on evidential reasoning analytical algorithm and entropy power.

Background technology

Along with China's expanding economy, air-conditioning equipment uses one of widely used measure improving thermal environment of Yi Shi China building.In building the building air-conditioning usage behavior of user such as the time of air-conditioning opening of device, the temperature of setting and building energy consumption relation very close.Zhou Xin [Zhou Xin etc. the definition of people's behavioral standard and the HVAC annual meeting of the case analysis .2010 whole nation. China, Hangzhou, 2010.11.) etc. research show, the behavior of resident's using air-condition has significant impact to building energy consumption, under operating mode opened by different air-conditioning, energy consumption of air conditioning in summer difference can reach 5 times more than.ReinhardHaas (ReinhardHaas, HansAuer, the research such as show in conjunction with building thermal technique performance and user behavior carry out building energy-saving renovation, and its energy-saving potential of reducing building heating energy consumption can reach 15% ~ 30% PeterBiermayr.Theimpactofconsumerbehavioronresidentialen ergydemandforspaceheating.EnergyandBuildings27 (1998): 195-205).

Current architectural environment and simulation of energy consumption technology relative maturity, and in building energy conservation, play very important effect.Air-conditioning usage behavior is the basic data of architectural environment and simulation of energy consumption software, has appreciable impact to analog result.But the building user air-conditioning usage behavior Consideration that current architectural environment and simulation of energy consumption instrument provide is comparatively single, and there is not little difference with actual conditions.Income level limit value refers to the critical temperature value that air-conditioning is opened, and when indoor temperature brings into operation higher than Income level higher limit or lower than Income level lower limit space-time tune, is the important parameter of air-conditioning equipment use behavior in building.For widely used architectural environment and simulation of energy consumption software DeST, the room air conditioner start-up temperature upper lower limit value of this type of bedroom is all set to 29 DEG C and 16 DEG C the whole year.But, research shows that in building, air-conditioning usage behavior is really not so single, ChihyeBaeandChungyoonChun (ChihyeBae, ChungyoonChun.Researchonseasonalindoorthermalenvironment andresidents'controlbehaviorofcoolingandheatingsystemsin Korea.BuildingandEnvironment, 2009,44 (11): 2300 ~ 2307) research finds that people namely indoorly just can open air conditioner refrigerating higher than when 30 DEG C exceeding summer comfort zone temperature.Yu Yang etc., by summer air-conditioning usage behavior test result analysis, show that local summer air-conditioning open temp higher limit is 28.7 DEG C of (Yu Yang; Yang Yulan, office building is studied with energy performance testing summer. environmental engineering the 33rd volume, the 5th phase, 2015).The general experience of life also tells us, and hot-summer and cold-winter area residential housing user wears the clothes thicker than the north in indoor in winter, even if indoor temperature is lower than the air-conditioning open temp lower limit 16 DEG C set by DeST, a lot of resident family also can not open air-conditioning equipment and carry out heating.In addition, the multifactorial impact of building air conditioning usage behavior audient, GeunYoungYun and KoenSteemers (GeunYoungYun, research show the factors such as building user behavioral trait, physical qualification and economic society on building energy consumption for cooling impact very remarkable KoenSteemers.Behavioural, physicalandsocio-economicfactorsinhouseholdcoolingenergy consumption.AppliedEnergy88 (2011): 2191-2200.).

Visible, owing to lacking the air-conditioning usage behavior theoretical model and method that can consider the factors such as local climate characteristic, architecture indoor external environment, building user behavioral trait, physical qualification and economic society, to greatly have influence on architectural environment and simulation of energy consumption instrument plays larger effect in building energy conservation, and be difficult to for architectural behavior Energy Conservation is for the theoretical foundation of science.

The present invention is directed to above-mentioned deficiency, a kind of Income level limit value emulation mode weighed based on evidential reasoning analytical algorithm and entropy is provided.This method can consider local climate characteristic, architecture indoor external environment, factor such as building user's physical qualification and economic society etc. to the impact of air-conditioning usage behavior, build Income level limit value simulation theory models and methods, export in calculation interval by time building air conditioning start-up temperature limit value emulated data, calculation interval can be set as the coldest moon, the hottest moon, summer, winter and even the whole year as required.The building air conditioning start-up temperature limit value emulated data exported provides the air-conditioning usage behavior data of more science for architectural environment and simulation of energy consumption software, thus will greatly improve the computational science of architectural environment and simulation of energy consumption software.Constructed building air conditioning start-up temperature limit value simulation theory models and methods can for architectural behavior Energy Conservation be for theoretical foundation.This method emulates based on evidential reasoning and entropy power theory, can process the subjective factor in the emulation of Income level limit value and objective factor, quantitative factor and qualitative factor, and, the imperfect information existed in simulation process can also be processed quantitatively.

Summary of the invention

The present invention is directed to the building user air-conditioning usage behavior Consideration that current architectural environment and simulation of energy consumption instrument provide single, the deficiencies such as the imperfect information of simulation process are not considered in the emulation of Income level limit value, provide a kind of Income level limit value emulation mode weighed based on evidential reasoning analytical algorithm and entropy.

The present invention is based on Evidential reasoning algorithm (EvidentialReasoningApproach is called for short ER method) and entropy power theory, build building air conditioning start-up temperature limit value simulation theory model and method.ER method by Jian ?BoYang and MadanG.Singh (Jian ?BoYang, M.G.S., Anevidentialreasoningapproachformultipleattributedecisio ndecisionmakingwithuncertainty.IEEEtransactionsonsystem, manandcybernetic, 1994.24 (1) .) proposed in 1994, can be used for uncertain information be mixed with quantitatively and qualitative question carries out theoretical modeling.Entropy (Entropy) (C.E.Shannon.Amathematicaltheoryofcommunication.BellSyste mTechnicalJournal, 1948,27 (3): 379 ?423; Wang Bin. entropy and information. publishing house of Northwestern Polytechnical University, 1994) originally thermodynamic (al) concept is belonged to, after due to Shannon introduce information theory, current entropy is the powerful of the uncertainty measure of stochastic system, and entropy is introduced and is used for determining Income level limit value influence factor weight allocation by this method.

Building air conditioning start-up temperature limit value simulation theory model and method constructed by the present invention, the subjective factor in the emulation of Income level limit value and objective factor can be processed, quantitative factor and qualitative factor, and, the imperfect information in process emulation that can also be quantitative.

Based on the Income level limit value emulation mode that evidential reasoning analytical algorithm and entropy are weighed, implementation step is as follows:

1) Income level limit value span is determined, and Income level limits is divided into the interval of finite number, suppose that Income level limits is divided into N number of interval, then the set of Income level limit value interval is expressed as H (H ₁, H ₂..., H _n);

2) identify the factor affecting Income level limit value, influence factor can comprise quantitative and qualitative analysis factor, and suppose to determine that the number of influence factor is L, influence factor set can be expressed as E (E ₁, E ₂..., E _l);

3) the interval reliability matrix of Income level limit value is built, reliability β _n,irepresent according to influence factor E _ithe information provided, the interval H of Income level limit value _nreliability, reliability β _n,imeet following formula: β _n,i>=0 and $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}\&le;1,n=1,...N,i=1,...L,\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}=1$ Represent that simulation process information is complete, $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}<1$ Represent that simulation process exists INFORMATION OF INCOMPLETE, n represents the interval sequence number of Income level limit value, and i represents influence factor sequence number;

4) Income level limit value influence factor weight is determined, influence factor E _iweight ω _irepresent, calculate ω according to entropy power principle _i;

Described step 4) comprise the following steps:

(41) influence factor E _ientropy S _irepresent, S _ias shown in the formula calculating: , wherein,

$f_{n,i}={\mathrm{\&beta;}}_{n,i}/\underset{i=1}{\overset{L}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i},$ K＝1/(logN)

K, f _n,ifor the intermediate parameters of entropy computation process;

(42) according to the property determination of entropy, entropy is larger, and the significance level of corresponding factor is less, influence factor E _iweights omega _iby following formulae discovery:

5) carry out the interval comprehensive brief combination of Income level limit value by the analytical algorithm of evidential reasoning, use β _n(n=1,2 ..., N) represent and consider the interval H of Income level limit value after all influence factors _ncomprehensive reliability, β _hwhat expression caused due to INFORMATION OF INCOMPLETE can not distribute reliability,

Described step 5) brief combination comprises the following steps:

(51) in conjunction with factor weight and reliability matrix, set up the basic brief inference function in evidence theory according to formula 1 ~ formula 5, occur in formula being conducive to the physical significance clearly expressing variable by the variable that two implications are identical; .

M _n,i=m _i(H _n)=ω _iβ _n,in=1 ..., N; I=1 ... L, (formula 1)

$m_{H,i}=m_i\left(H\right)=1-\underset{n=1}{\overset{N}{\&Sigma;}}{m}_{n,i}=1-{\mathrm{\&omega;}}_i\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i},i=1,...,L,$ (formula 2)

${\stackrel{\&OverBar;}{m}}_{H,i}={\stackrel{\&OverBar;}{m}}_i\left(H\right)=1-{\mathrm{\&omega;}}_i,i=1,...,L,$ (formula 3)

${\tilde{m}}_{H,i}={\tilde{m}}_i\left(H\right)={\mathrm{\&omega;}}_i(1-\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}),i=1,...,L,$ (formula 4)

And

$m_{H,i}={\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i}$ (formula 5)

In formula: $\underset{i=1}{\overset{L}{\&Sigma;}}{\mathrm{\&omega;}}_i=1$

M _n.i, m _i(H _n)--represent from factor E _ithe information that provides of angle, the interval H of Income level limit value _nbasic reliability;

M _h.i, m _i(H)--represent from factor E _ithe whole simulation process of angle in be assigned to Income level limit value interval set H outside reliability, by with two parts form;

--represent E _iother influence factor outside this influence factor is to the effect of Income level limit value;

--represent E _ithis influence factor carries out the degree of the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation, if from E _ithe artificial intelligence of this influence factor is completely, then

(52) according to evidential reasoning analytical algorithm, brief combination is carried out according to formula 6 ~ formula 11:

$\left\{H_n\right\}:m_n=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;,n=1,...,N,$ (formula 6)

$\left\{H\right\}:{\tilde{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;,$ (formula 7)

$\left\{H\right\}:{\stackrel{\&OverBar;}{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;$ (formula 8)

$k={\&lsqb;\underset{n=1}{\overset{N}{\&Sigma;}}\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-(N-1)\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;}^{-1},$ (formula 9)

$\left\{H_n\right\}:{\mathrm{\&beta;}}_n=\frac{m_n}{1-{\stackrel{\&OverBar;}{m}}_H},n=1,...,N,$ (formula 10)

$\left\{H\right\}:{\mathrm{\&beta;}}_H=\frac{{\tilde{m}}_n}{1-{\stackrel{\&OverBar;}{m}}_H}$ (formula 11)

In formula:

M _n--representative considers the interval H of Income level limit value after influence factor set E _nbasic reliability;

--represent other influence factor outside influence factor set E to the effect of Income level limit value;

--representative considers the degree that influence factor set E carries out the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation;

The intermediate variable introduced in k--brief combination computation process;

6) according to β _n(n=1,2 ..., N) in maximal value, determine that emulation moment Income level limit value is interval, and get the Income level limit value that this interval median is the emulation moment, provide cause due to INFORMATION OF INCOMPLETE can not distribute reliability β _h;

7) repeat step 3) ~ step 6) and to emulation the period by time calculate, then obtain emulate the period air-conditioning open temp limit value by time value list.

It is single that this method overcomes the building user air-conditioning usage behavior mode Consideration that current architectural environment and simulation of energy consumption instrument provide, and the deficiencies such as the imperfect information of simulation process are not considered in the emulation of Income level limit value.This method can consider local climate characteristic, architecture indoor external environment, factor such as building user's physical qualification and economic society etc. to the impact of air-conditioning usage behavior, build Income level limit value simulation theory models and methods, can export in calculation interval by time building air conditioning start-up temperature limit value emulated data, calculation interval can be set as the coldest moon, the hottest moon, summer, winter and even the whole year as required.The building air conditioning start-up temperature limit value emulated data exported provides the air-conditioning usage behavior data of more science for architectural environment and simulation of energy consumption software, thus will greatly improve the computational science of architectural environment and simulation of energy consumption software.Constructed building air conditioning start-up temperature limit value simulation theory models and methods can for architectural behavior Energy Conservation be for theoretical foundation.This method emulates based on evidential reasoning and entropy power theory, can process the subjective factor in the emulation of Income level limit value and objective factor, quantitative factor and qualitative factor, and, the imperfect information existed in simulation process can also be processed quantitatively.

Accompanying drawing illustrates:

Fig. 1 is method flow diagram of the present invention

Embodiment

As shown in Figure 1, a kind of Income level limit value emulation mode schematic diagram weighed based on evidential reasoning analytical algorithm and entropy, implementation step is as follows:

1) determine Income level limit value span, and Income level limit value is divided into the interval of finite number, suppose that Income level limits is divided into N number of interval, then the set of starting of air conditioner limit value interval is expressed as H (H ₁, H ₂..., H _n);

2) identify the factor affecting Income level limit value, influence factor can comprise quantitative and qualitative analysis factor, and suppose to determine that the number of influence factor is L, influence factor set can be expressed as E (E ₁, E ₂..., E _l);

3) the interval reliability matrix of Income level limit value is built, reliability β _n,irepresent according to influence factor E _ithe information provided, the interval H of Income level limit value _nreliability, reliability β _n,imeet following formula: β _n,i>=0 and $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}\&le;1,n=1,...N,i=1,...L,\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}=1$ Represent that simulation process information is complete, $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}<1$ Represent that simulation process exists INFORMATION OF INCOMPLETE, n represents the interval sequence number of Income level limit value, and i represents influence factor sequence number;

Described step 3) specifically comprise following steps:

(31) the brief inference function in each factor and Income level limit value interval is studied by modes such as long-term measurement, survey, observed and recorded, theoretical analysises;

(32) for the emulation moment, the interval reliability matrix of Income level limit value as shown in table 1 is constructed;

Table 1: the interval reliability matrix of Income level limit value

	H 1	H 2	…	H N
					E 1	β 11	β 21	…	β N1
E 2	β 12	β 22	…	β N2
					…	…	…	…	…
E L	β 1L	β 2L	…	β NL

4) Income level limit value influence factor weight is determined, influence factor E _iweight ω _irepresent, calculate ω according to entropy power principle _i;

Described step 4) comprise the following steps:

(41) influence factor E _ientropy S _irepresent, S _ias shown in the formula calculating: $S_i=-K\underset{n=1}{\overset{N}{\&Sigma;}}{f}_{n,i}\ln f_{n,i},i=1,...,L,$ , wherein,

$f_{n,i}={\mathrm{\&beta;}}_{n,i}/\underset{i=1}{\overset{L}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i},$ K＝1/(logN)

K, f _n,ifor the intermediate parameters of entropy computation process;

(42) according to the property determination of entropy, entropy is larger, and the importance degree of corresponding factor is less, influence factor E _iweights omega _iby following formulae discovery:

5) carry out the interval comprehensive brief combination of Income level limit value by the analytical algorithm of evidential reasoning, use β _n(n=1,2 ..., N) represent and consider the interval H of Income level limit value after all influence factors _ncomprehensive reliability, β _hwhat expression caused due to INFORMATION OF INCOMPLETE can not distribute reliability,

Described step 5) brief combination comprises the following steps:

(51) in conjunction with factor weight and reliability matrix, set up the basic brief inference function in evidence theory according to formula 1 ~ formula 5, occur in formula being conducive to the physical significance clearly expressing variable by the variable that two implications are identical; .

M _n,i=m _i(H _n)=ω _iβ _n,in=1 ..., N; I=1 ... L, (formula 1)

$m_{H,i}=m_i\left(H\right)=1-\underset{n=1}{\overset{N}{\&Sigma;}}{m}_{n,i}=1-{\mathrm{\&omega;}}_i\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i},i=1,...,L,$ (formula 2)

${\stackrel{\&OverBar;}{m}}_{H,i}={\stackrel{\&OverBar;}{m}}_i\left(H\right)=1-{\mathrm{\&omega;}}_i,i=1,...,L,$ (formula 3)

${\tilde{m}}_{H,i}={\tilde{m}}_i\left(H\right)={\mathrm{\&omega;}}_i(1-\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}),i=1,...,L,$ (formula 4)

And

$m_{H,i}={\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i}$ (formula 5)

In formula: $\underset{i=1}{\overset{L}{\&Sigma;}}{\mathrm{\&omega;}}_i=1$

M _n.i, m _i(H _n)--represent from factor E _ithe information that provides of angle, the interval H of Income level limit value _nbasic reliability;

M _h.i, m _i(H)--represent from factor E _ithe whole simulation process of angle in be assigned to Income level limit value interval set H outside reliability, by with two parts form;

--represent E _iother influence factor outside this influence factor is to the effect of Income level limit value;

--represent E _ithis influence factor carries out the degree of the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation, if from E _ithe artificial intelligence of this influence factor is completely, then

(52) according to evidential reasoning analytical algorithm, brief combination is carried out according to formula 6 ~ formula 11:

$\left\{H_n\right\}:m_n=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;,n=1,...,N,$ (formula 6)

$\left\{H\right\}:{\tilde{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;,$ (formula 7)

$\left\{H\right\}:{\stackrel{\&OverBar;}{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;$ (formula 8)

$k={\&lsqb;\underset{n=1}{\overset{N}{\&Sigma;}}\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-(N-1)\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;}^{-1},$ (formula 9)

$\left\{H_n\right\}:{\mathrm{\&beta;}}_n=\frac{m_n}{1-{\stackrel{\&OverBar;}{m}}_H},n=1,...,N,$ (formula 10)

$\left\{H\right\}:{\mathrm{\&beta;}}_H=\frac{{\tilde{m}}_n}{1-{\stackrel{\&OverBar;}{m}}_H}$ (formula 11)

In formula:

M _n--representative considers the interval H of Income level limit value after influence factor set E _nbasic reliability;

--represent other influence factor outside influence factor set E to the effect of Income level limit value;

--representative considers the degree that influence factor set E carries out the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation;

The intermediate variable introduced in k--brief combination computation process;

6) according to β _n(n=1,2 ..., N) in maximal value, determine that emulation moment Income level limit value is interval, and get the Income level limit value that this interval median is the emulation moment, provide cause due to INFORMATION OF INCOMPLETE can not distribute reliability β _h;

7) repeat step 3) ~ step 6) and to emulation the period by time calculate, then obtain emulate the period air-conditioning open temp limit value by time value list.

Case is demonstrated

The building summer air-conditioning start-up temperature upper limit emulation case simplified by one, specific embodiment of the invention is described, the emulation of case building air conditioning start-up temperature higher limit is implemented as follows:

1) simplify in case, Income level higher limit scope is defined as [27.0 DEG C, 32.0 DEG C], and be divided into 5 intervals, Income level limit value Interval Set is combined into H (H ₁, H ₂, H ₃, H ₄, H ₅), it is ([27.0 DEG C, 27.8 DEG C) that the element in H represents Income level limit value interval respectively, [27.8 DEG C, 28.6 DEG C), [and 28.6 DEG C, 29.4 DEG C), [29.4 DEG C, 31.2 DEG C), [31.2 DEG C, 32.0 DEG C];

2) factor affecting building air conditioning start-up temperature higher limit is identified, building air conditioning start-up temperature higher limit influence factor is numerous, be to demonstrate specific embodiment of the invention herein, building air conditioning start-up temperature higher limit influence factor quantity is decided to be 6 by this simplification case, and influence factor set is E (E ₁, E ₂, E ₃, E ₄, E ₅, E ₆), in E, element represents following influence factor respectively: (building location climate characteristic, indoor occupant active situation, outdoor temperature, air-conditioning equipment adjusting function, building energy use way of paying, building user's age);

3) process that the interval reliability matrix of building air conditioning start-up temperature higher limit is more complicated is built, adoptable mode has the methods such as the test of long-term building air conditioning start-up temperature higher limit, survey, long-term observation and theoretical analysis, be the concrete enforcement demonstrating this method herein, for simplification case, build the interval reliability matrix of emulation moment building air conditioning start-up temperature higher limit as shown in table 2, due to the indoor occupant activity factor E in this moment ₂data are sufficiently complete, so the brief inference of this factor exists imperfect information, namely all there is not imperfect information in all the other factors;

Table 2: case building is at the interval reliability matrix of the building air conditioning start-up temperature upper limit in emulation moment

	H 1	H 2	H 3	H 4	H 5
						E 1	0.31	0.23	0.22	0.10	0.14
E 2	0.63	0.10	0.08	0.02	0.01
						E 3	0.40	0.20	0.11	0.19	0.10
E 4	0.34	0.21	0.12	0.08	0.25
						E 5	0.81	0.08	0.03	0.04	0.04
E 6	0.32	0.23	0.34	0.04	0.07

4) factor weight calculated in this simplification case according to entropy assessment is (0.23,0.07,0.21,0.21,0.09,0.18);

5) by brief combination analytical algorithm, the comprehensive reliability calculating this simplification case building air conditioning start-up temperature upper limit interval is as shown in table 3, and as can be seen from Table 3, simulation process exists the indistributable reliability β because INFORMATION OF INCOMPLETE causes _hbe 0.0087, can inference this be because the INFORMATION OF INCOMPLETE of factor 2 causes;

Table 3: the interval integrated information degree of the case building air conditioning start-up temperature upper limit

β 1	β 2	β 3	β 4	β 5	β H
						0.4309	0.1926	0.1638	0.0866	0.1174	0.0087

6) according to β _n(n=1,2 ..., 5) in maximal value, determine this case in emulation moment building air conditioning start-up temperature upper limit interval for H ₁, interval H ₁median, namely emulating the moment building air conditioning start-up temperature upper limit is 27.4 DEG C, and provides the indistributable reliability β because INFORMATION OF INCOMPLETE causes _hbe 0.0087;

Repeat step 3) ~ step 6) and to emulation the period by time calculate, obtain emulate the period the air-conditioning open temp upper limit by time value list.

Claims (1)

1., based on the Income level limit value emulation mode that evidential reasoning analytical algorithm and entropy are weighed, step is as follows:

1) Income level limit value span is determined, and Income level limits is divided into the interval of finite number, suppose that Income level limits is divided into N number of interval, then the set of Income level limit value interval is expressed as H (H ₁, H ₂..., H _n);

2) identify the factor affecting Income level limit value, influence factor can comprise quantitative and qualitative analysis factor, and suppose to determine that the number of influence factor is L, influence factor set can be expressed as E (E ₁, E ₂..., E _l);

3) the interval reliability matrix of Income level limit value is built, reliability β _n,irepresent according to influence factor E _ithe information provided, the interval H of Income level limit value _nreliability, reliability β _n,imeet following formula: β _n,i>=0 and $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}\&le;1,n=1,...N,i=1,...L,\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}=1$ Represent that simulation process information is complete, $\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}<1$ Represent that simulation process exists INFORMATION OF INCOMPLETE, n represents the interval sequence number of Income level limit value, and i represents influence factor sequence number;

4) Income level limit value influence factor weight is determined, influence factor E _iweight ω _irepresent, calculate ω according to entropy power principle _i;

Described step 4) comprise the following steps:

(41) influence factor E _ientropy S _irepresent, S _ias shown in the formula calculating: , wherein, , K=1/ (logN) K, f _{n, i}for the intermediate parameters of entropy computation process;

(42) according to the property determination of entropy, entropy is larger, and the significance level of corresponding factor is less, influence factor E _iweights omega _iby following formulae discovery:

5) carry out the interval comprehensive brief combination of Income level limit value by the analytical algorithm of evidential reasoning, use β _n(n=1,2 ..., N) represent and consider the interval H of Income level limit value after all influence factors _ncomprehensive reliability, β _hwhat expression caused due to INFORMATION OF INCOMPLETE can not distribute reliability,

Described step 5) brief combination comprises the following steps:

(51) in conjunction with factor weight and reliability matrix, set up the basic brief inference function in evidence theory according to formula 1 ~ formula 5, occur in formula being conducive to the physical significance clearly expressing variable by the variable that two implications are identical; .

M _n,i=m _i(H _n)=ω _iβ _n,in=1 ..., N; I=1 ... L, (formula 1)

$m_{H,i}=m_i\left(H\right)=1-\underset{n=1}{\overset{N}{\&Sigma;}}{m}_{n,i}=1-{\mathrm{\&omega;}}_i\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i},i=1,...,L,$ (formula 2)

${\stackrel{\&OverBar;}{m}}_{H,i}={\stackrel{\&OverBar;}{m}}_i\left(H\right)=1-{\mathrm{\&omega;}}_i,i=1,...,L,$ (formula 3)

${\tilde{m}}_{H,i}={\tilde{m}}_i\left(H\right)={\mathrm{\&omega;}}_i(1-\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&beta;}}_{n,i}),i=1,...,L,$ (formula 4)

And

$m_{H,i}={\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i}$ (formula 5)

In formula: $\underset{i=1}{\overset{L}{\&Sigma;}}{\mathrm{\&omega;}}_i=1$

M _n.i, m _i(H _n)--represent from factor E _ithe information that provides of angle, the interval H of Income level limit value _nbasic reliability;

M _h.i, m _i(H)--represent from factor E _ithe whole simulation process of angle in be assigned to Income level limit value interval set H outside reliability, by with two parts form;

--represent E _iother influence factor outside this influence factor is to the effect of Income level limit value;

--represent E _ithis influence factor carries out the degree of the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation, if from E _ithe artificial intelligence of this influence factor is completely, then

(52) according to evidential reasoning analytical algorithm, brief combination is carried out according to formula 6 ~ formula 11:

$\left\{H_n\right\}:m_n=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;,n=1,...,N,$ (formula 6)

$\left\{H\right\}:{\tilde{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;,$ (formula 7)

$\left\{H\right\}:{\stackrel{\&OverBar;}{m}}_H=k\&lsqb;\underset{i=1}{\overset{L}{\&Pi;}}{\stackrel{\&OverBar;}{m}}_{H,i}\&rsqb;$ (formula 8)

$k={\&lsqb;\underset{n=1}{\overset{N}{\&Sigma;}}\underset{i=1}{\overset{L}{\&Pi;}}(m_{n,i}+{\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})-(N-1)\underset{i=1}{\overset{L}{\&Pi;}}({\stackrel{\&OverBar;}{m}}_{H,i}+{\tilde{m}}_{H,i})\&rsqb;}^{-1},$ (formula 9)

$\left\{H_n\right\}:{\mathrm{\&beta;}}_n=\frac{m_n}{1-{\stackrel{\&OverBar;}{m}}_H},n=1,...,N,$ (formula 10)

$\left\{H\right\}:{\mathrm{\&beta;}}_H=\frac{{\tilde{m}}_n}{1-{\stackrel{\&OverBar;}{m}}_H}$ (formula 11)

In formula:

M _n--representative considers the interval H of Income level limit value after influence factor set E _nbasic reliability;

--represent other influence factor outside influence factor set E to the effect of Income level limit value;

--representative considers the degree that influence factor set E carries out the INFORMATION OF INCOMPLETE of building air conditioning start-up temperature limit value emulation;

The intermediate variable introduced in k--brief combination computation process;

6) according to β _n(n=1,2 ..., N) in maximal value, determine that emulation moment Income level limit value is interval, and get the Income level limit value that this interval median is the emulation moment, provide cause due to INFORMATION OF INCOMPLETE can not distribute reliability β _h;

7) repeat step 3) ~ step 6) and to emulation the period by time calculate, then obtain emulate the period air-conditioning open temp limit value by time value list.