CN112948750A - Intelligent room selection method and device based on human body comfort level requirement and related components - Google Patents

Intelligent room selection method and device based on human body comfort level requirement and related components Download PDF

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CN112948750A
CN112948750A CN202110240206.1A CN202110240206A CN112948750A CN 112948750 A CN112948750 A CN 112948750A CN 202110240206 A CN202110240206 A CN 202110240206A CN 112948750 A CN112948750 A CN 112948750A
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廖龙辉
全丽蓉
梁逸飞
廖奎安
杨川
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Abstract

The invention discloses an intelligent room selection method, an intelligent room selection device and relevant components based on human body comfort level requirements, wherein the method comprises the following steps: constructing a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; wherein, the second level is a plurality of first factors which have influence on the comfort of the room, and the third level is a second factor which is subordinate to the first factors; acquiring a comparison result and a scoring result of each factor of a user, and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result; calculating each first weight and each second weight by using the fuzzy complementary judgment matrix; acquiring a factor score corresponding to the second factor; calculating the score of the room comfort degree by combining the first weight, the second weight and the factor score, and feeding back the calculation result to the user; and obtaining the decision feedback of the user on the calculation result, and executing the corresponding decision. The invention can more accurately and comprehensively evaluate the housing by the fuzzy chromatography analysis method.

Description

Intelligent room selection method and device based on human body comfort level requirement and related components
Technical Field
The invention relates to the technical field of building living environment evaluation, in particular to an intelligent room selection method and system based on human body comfort level requirements.
Background
With the development of society, the requirements of people on living standard are higher and higher. Housing is a place for providing rest space for people, and the living comfort is very important. When buying a house, most house source information acquired by people comes from the explanation of the salesman of the house selling department, the house selection of the user is greatly influenced by the subjectivity of the salesman in the mode, so that the house cannot be accurately, reasonably and comprehensively evaluated, and the finally selected house cannot meet the personal comfort requirement.
Disclosure of Invention
The embodiment of the invention provides an intelligent house selecting method and device based on human body comfort level requirements, computer equipment and a storage medium, and aims to improve the accuracy and comprehensiveness of house evaluation.
In a first aspect, an embodiment of the present invention provides an intelligent room selection method based on human comfort requirements, including:
constructing a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
obtaining a comparison result and a scoring result of a user for each factor in the second level and the third level, and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
calculating a first weight corresponding to each first factor and a second weight corresponding to each second factor by using the fuzzy complementary judgment matrix;
acquiring a factor score corresponding to each second factor;
calculating the score of the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back the calculation result to the user;
and obtaining the decision feedback of the user on the calculation result, and executing the corresponding decision.
In a second aspect, an embodiment of the present invention provides an intelligent room selection device based on a human comfort requirement, including:
the model building unit is used for building a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
the result acquisition unit is used for acquiring a comparison result and a scoring result of each factor in the second level and the third level of the user and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
a first weight calculation unit, configured to calculate, by using the fuzzy complementary judging matrix, a first weight corresponding to each of the first factors and a second weight corresponding to each of the second factors;
the score acquisition unit is used for acquiring the factor score corresponding to each second factor;
the combination calculation unit is used for performing score calculation on the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back a calculation result to a user;
and the decision execution unit is used for acquiring the decision feedback of the user on the calculation result and executing the corresponding decision.
In a third aspect, an embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the intelligent room selection method based on human comfort requirement according to the first aspect is implemented.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the intelligent room selection method based on human comfort requirement according to the first aspect.
The embodiment of the invention provides an intelligent room selection method and device based on human body comfort level requirements, computer equipment and a storage medium, wherein the method comprises the following steps: constructing a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor; obtaining a comparison result and a scoring result of a user for each factor in the second level and the third level, and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result; calculating a first weight corresponding to each first factor and a second weight corresponding to each second factor by using the fuzzy complementary judgment matrix; acquiring a factor score corresponding to each second factor; calculating the score of the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back the calculation result to the user; and obtaining the decision feedback of the user on the calculation result, and executing the corresponding decision. According to the embodiment of the invention, the house can be more accurately and comprehensively evaluated by the fuzzy chromatography analysis method, so that a user can select a house meeting the personalized comfort requirement.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent room selection method based on human comfort requirements according to an embodiment of the present invention;
fig. 2 is a network schematic diagram of a fuzzy hierarchical analysis structure model in an intelligent room selection method based on human comfort requirements according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of an intelligent room selection device based on human comfort requirements according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a diagram illustrating an intelligent room selection method based on a human comfort requirement according to an embodiment of the present invention, which specifically includes: steps S101 to S106.
S101, constructing a fuzzy hierarchical analysis structure model which takes room comfort as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
s102, obtaining a comparison result and a scoring result of a user for each factor in a second level and a third level, and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
s103, calculating a first weight corresponding to each first factor and a second weight corresponding to each second factor by using the fuzzy complementary judging matrix;
s104, acquiring a factor score corresponding to each second factor;
s105, calculating the score of the comfort level of the room by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back the calculation result to the user;
and S106, obtaining the decision feedback of the user on the calculation result, and executing a corresponding decision.
In this embodiment, a fuzzy hierarchical analysis structure model including a plurality of levels is first constructed, and each level includes a plurality of different factors, that is, the second level includes a plurality of first factors, and the third level includes a plurality of second factors. And aiming at any housing, obtaining a comparison result and a scoring result of a first factor and a second factor corresponding to the housing by a user, and constructing the fuzzy complementary judgment matrix according to the comparison result and the scoring result. The weight corresponding to each factor, namely the first weight and the second weight, can be calculated through the fuzzy complementary judgment matrix, and the room comfort degree score of the house can be calculated by combining the factor score obtained by pre-calculation. And sending the room comfort degree scores of the houses to the user, so that the user can select the houses which are satisfied by the user according to different room comfort degree scores.
The intelligent house selecting method can evaluate houses more accurately and comprehensively based on the requirement of human comfort level, further recommend houses meeting the requirement of personalized comfort level for users accurately and objectively, reduce subjective influence of sales personnel in providing sales service, comprehensively consider the comfort requirement of the users on the living environment of buildings under the influence of various factors, and facilitate the house selecting decision of the users based on the personalized comfort level requirement.
In a particular embodiment, the room comfort scores for each set of rooms are ranked as the results of the calculations are fed back to the user; and constructing a building three-dimensional model with score information based on the room comfort score. The user can clearly and definitely know the conditions of each house.
In another embodiment, the user makes a decision based on the room comfort score in combination with the three-dimensional model of the building. After obtaining the decision feedback of the user, executing a corresponding decision, specifically comprising: locking the corresponding housing information according to the decision feedback of the user, ensuring that the corresponding housing cannot be called in subsequent operation, and avoiding being locked again by other users; and canceling the locked housing information according to the decision feedback of the user, so that the corresponding housing can be normally called in the subsequent operation to participate in the calculation sequencing.
In one embodiment, the first factors comprise sound factors, light factors, wind factors and heat factors, the subordinate second factors of the sound factors comprise a main noise source distance factor, a material sound insulation performance factor and a floor height sound factor, the subordinate second factors of the light factors comprise a door and window opening area factor, a door and window light transmittance factor, a floor height light factor and a sunshine time factor, the subordinate second factors of the wind factors comprise a door and window opening area factor and a floor height wind factor, and the heat factors comprise a building orientation factor, an air flow speed factor and a wall door and window heat transfer coefficient factor.
In this embodiment, different first factors belong to different second factors, for example, the second factors belonging to the first factors include a distance factor between a main noise source, a sound insulation performance factor of a material, and a floor height sound factor, and the second factors belonging to the first factors include a door and window opening area factor, a door and window light transmittance factor, a floor height light factor, and a sunshine duration factor. Of course, in other embodiments, the first factor may also be subordinate to more second factors to further improve the accuracy of the room comfort evaluation. As can be seen from fig. 2, when the fuzzy hierarchical analysis structure model is constructed, the target of the model is the room comfort level a, and the first factor in the second hierarchy is: acoustic factor (B1), optical factor (B2), wind factor (B3), and thermal factor (B4), the second factor in the third level being: the method comprises the following steps of (1) a sub-factor main noise source distance factor (C1) under a sound factor (B1), a material sound insulation performance factor (C2), a floor height sound factor (C3), a sub-factor door and window hole area factor (C4) under a light factor (B2), a door and window light transmittance factor (C5), a floor height light factor (C6), a sunshine time factor (C7), a sub-factor door and window opening area factor (C8) under a wind factor (B3), a floor height wind factor (C9), (4), a sub-factor building orientation factor (C10) under a heat factor (B4), an air flow speed factor (C11) and a wall door and window heat transfer coefficient (C12).
In one embodiment, the step S102 includes:
aiming at a second level, acquiring a first comparison result and a first grading result of pairwise comparison of a first factor by a user, and constructing a first fuzzy judgment matrix based on the first comparison result and the first grading result;
aiming at the third level, acquiring a second comparison result and a second scoring result of pairwise comparison of a second factor subordinate to the sound factor by the user, and constructing a second fuzzy judgment matrix based on the second comparison result and the second scoring result;
aiming at a third level, acquiring a third comparison result and a third scoring result of pairwise comparison of a second factor subordinate to the optical factor by a user, and constructing a third fuzzy judgment matrix based on the third comparison result and the third scoring result;
aiming at the third level, acquiring a fourth comparison result and a fourth scoring result of pairwise comparison of the second factor subordinate to the wind factor of the user, and constructing a fourth fuzzy judgment matrix based on the fourth comparison result and the fourth scoring result;
aiming at the third level, acquiring a fifth comparison result and a fifth scoring result of pairwise comparison of the user on a second factor subordinate to the thermal factor, and constructing a fifth fuzzy judgment matrix based on the fifth comparison result and the fifth scoring result;
and taking the first fuzzy judgment matrix, the second fuzzy judgment matrix, the third fuzzy judgment matrix, the fourth fuzzy judgment matrix and the fifth fuzzy judgment matrix as the fuzzy complementary judgment matrix.
In the embodiment, when the fuzzy complementary judgment matrix is constructed, scoring needs to be performed according to the personalized comfort level requirement of the user. The user compares the factors of the same level pairwise, determines the relative importance degree according to the evaluation scale, and establishes a corresponding fuzzy judgment matrix, for example, when comparing the first factor of the second level pairwise, the sound factor and the light factor, the sound factor and the wind factor, the sound factor and the heat factor, the light factor and the heat factor, and the like need to be compared. In fuzzy hierarchical analysis (FAHP), when pairwise comparison judgment between factors is carried out, the importance degree of one factor to the importance degree of the other factor is quantitatively expressed, and thus a fuzzy judgment matrix A is obtained (a is equal toij) n × n, the fuzzy judgment matrix has the following properties: a isii＝0.5，i＝1，2，…，n；aij+aji＝1，i,j＝1，2，…，n。
Meanwhile, the relative importance between the two factors is generally given to a quantitative scale by using a 0.1-0.9 scale method, for example:
0.5 (equally important) means: comparing the two factors, wherein the two factors are equally important, for example, the comparison score of the acoustic factor and the optical factor is 0.5, which indicates that the acoustic factor and the optical factor are equally important;
0.6 (slightly important) indicates: comparing the two factors, wherein one factor is slightly more important than the other factor, for example, the comparison score of the acoustic factor and the optical factor is 0.6, which indicates that the acoustic factor is slightly more important than the optical factor;
0.7 (obviously important) means: comparing the two factors, wherein one factor is obviously more important than the other factor, for example, the comparison score of the acoustic factor and the optical factor is 0.7, which indicates that the acoustic factor is obviously more important than the optical factor;
0.8 (much more important) represents: comparing the two factors, one factor is more important than the other factor, for example, the comparison score of the acoustic factor and the optical factor is 0.8, which indicates that the acoustic factor is more important than the optical factor;
0.9 (extremely important) means: comparing the two factors, wherein one factor is more important than the other factor, for example, the comparison score of the acoustic factor and the optical factor is 0.9, which indicates that the acoustic factor is more important than the optical factor;
further, if a in the matrix is determined to be fuzzyii0.5, this means that the factor is as important as itself; if aijE [0.1, 0.5)), the factor x is representedjRatio xiImportance; if aij∈[0.5，0.9]Then, the factor x is representediRatio xjIt is important.
According to the digital scale, the factors a are divided1，a2，…，anComparing the two matrixes with each other, the following fuzzy judgment matrix can be obtained:
Figure BDA0002961910260000071
that is, when comparing the first factor in the second level, a fourth-order fuzzy judgment matrix can be obtained, when comparing the second factor subordinate to the acoustic factor, a third-order fuzzy judgment matrix can be obtained, and similarly, when comparing the second factors subordinate to the optical factor, the wind factor and the thermal factor, respectively, a corresponding fourth-order fuzzy judgment matrix, a corresponding second-order fuzzy judgment matrix and a corresponding third-order fuzzy judgment matrix can be obtained.
In one embodiment, the step S103 includes:
calculating each of the first weight and the second weight according to:
Figure BDA0002961910260000072
in the formula, WiIs the weight of the ith factor, αijAnd judging the jth element of the ith row in the fuzzy complementary judgment matrix.
In this embodiment, the weights corresponding to the factors in the fuzzy complementary judging matrix can be calculated by using the weight calculation formula. Further, the weight of each factor is normalized, so that the sum of the first weights corresponding to the normalized first factor is 1, and the sum of the second weights corresponding to the normalized second factor is 1. As shown in the following formula:
Figure BDA0002961910260000073
in the formula: w1、2、3、4First weights respectively corresponding to four first factors of an acoustic factor (B1), a light factor (B2), a wind factor (B3) and a heat factor (B4) in the second level; omega1、2、3、…、1212 second factors C in the third level1、C2、C3、…、C12Respectively corresponding second weights.
In an embodiment, the intelligent room selection method based on the human comfort requirement further includes:
carrying out consistency definition on the fuzzy complementary judgment matrix by utilizing additive definition or multiplicative definition;
performing consistency check on the fuzzy complementation judgment matrix based on sufficient necessary conditions of the fuzzy complementation judgment matrix, wherein the sufficient necessary conditions are as follows: in the fuzzy complementary judging matrix, the difference between corresponding elements of any appointed row and other rows is a constant.
In this embodiment, consistency check is performed on whether the weights calculated by using the fuzzy complementary determination matrix are reasonable. Specifically, firstly, an additive definition or a multiplicative definition is used to perform consistency definition on the fuzzy complementary judging matrix, where the additive definition is: a isij＝aik-ajk+0.5，
Figure BDA0002961910260000081
An equivalent definition may also be: a isij+ajk+aki＝aji+akj+aik1.5; the multiplicative definition refers to: a isijajkaki＝ajiakiaik，
Figure BDA0002961910260000082
j，k∈N，i≠j≠k。
Then, consistency check is carried out on the fuzzy complementary judging matrix through a preset check rule, namely the fuzzy complementary judging matrix is a consistency matrix, and the essential conditions are as follows: the difference between corresponding elements of any given line and other lines is a constant.
In one embodiment, the step S104 includes:
calculating the factor score of the primary noise source distance factor according to the following formula:
Figure BDA0002961910260000083
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000084
is a factor score, NL, of the distance factor of the main noise source of the ith suite in a cellmaxThe noise of the room with the largest noise in each set of houses in the same community is obtained;
in this step, the main noise source distance factor is understood as the maximum indoor noise level, that is, the noise level of a room with the largest noise in a certain set of houses in a cell. The noise level is a grade classification describing the noise magnitude, for example, a normal quiet environment with a noise level of 30-40 dB is provided; more than 50 decibels can affect sleep and rest; more than 70 decibels interfere conversation, affect working efficiency and even cause accidents; a noisy environment, working for a long time or living above 90 db, can seriously affect hearing and cause other diseases. This step thus provides the maximum indoor noise level NL for each set of housing for each building in the communitymaxMonitoring is carried out and the monitored data is converted into [0, 10]]And (5) score values are stored.
Calculating the factor value of the sound insulation performance factor of the material according to the following formula:
Figure BDA0002961910260000085
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000091
is the factor score, SRI, of the sound insulation performance factor of the ith suite of materials in a communityiIs the material sound insulation index, SRI, of the ith suite in a communitymaxIs the maximum value of the material sound insulation index, SRI, of all dwellings in a communityminThe minimum value of the sound insulation index of the materials of all the houses in a certain cell;
the sound insulation performance factor of the material in the step specifically refers to the sound insulation performance of the material used for the building. That is, the factor score of the material sound insulation performance factor is calculated according to the sound insulation index of the material. Specifically, when the sound insulation index of the material is calculated, a sound insulation characteristic curve corresponding to the material is drawn, and the standard curve of the material is utilized to move up and down along the vertical direction until the following two conditions are met:
a. the difference value between the sound insulation quantity of any 1/3 times frequency band below the standard curve and the standard curve cannot exceed 8 decibels;
b. the sum of the differences between the 1/3 times frequency bands below the standard curve and the standard curve should not exceed 32 db.
Wherein, the sound insulation I corresponding to the central frequency of the 1/3-times frequency band of 500 Hz is the reading of the sound insulation index. Further, the sound insulation index of the material used by each housing in the cell is recorded as SRI, and the SRI is converted into a [0, 10] score for storage.
Calculating the factor score of the floor height acoustic factor according to the following formula:
Figure BDA0002961910260000092
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000093
is the factor score, HV, of the acoustic factors of the ith suite floor height in the celliIs the ith suite of buildings in a communityA sound score of the layer height; h is the building height of the single building where the ith suite is located in the cell;
in this step, the floor height sound factor means that, for the same single building, the house noise changes along with the change of the floor height. Generally, for the same building, the higher the floor, the greater the noise. When the floor height sound factor of each set of housing is calculated, the floor height (sound) factor of each set of housing is calculated from the ground elevation of the first floor of each single building to the floor elevation of the upper floor of the floor. Likewise, the calculation results are converted to [0, 10] scores and stored.
Calculating the factor value of the door and window opening area factor according to the following formula:
Figure BDA0002961910260000094
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000095
is the factor score, SD, of the ith suite door and window opening area factor in the communityiIs the area of the door and window opening, SD, of the ith suite of rooms in the communitymaxIs the maximum value of the door and window opening area, SD, of all houses in the residential areaminThe minimum value of the door and window opening areas of all houses in the community;
in this step, the area factor of the door and window opening refers to the area of the door and window opening on the main lighting surface in each set of housing. The area of the door and window openings influences the indoor luminous environment. Similarly, the calculation results of this step are converted into [0, 10] scores and stored.
Calculating the factor value of the light transmittance factor of the door and window according to the following formula:
Figure BDA0002961910260000101
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000102
is the factor score, LA, of the light transmittance factor of the ith suite of doors and windows in a communityiIs the absorbance of the door and window of the ith suite in the community, LAmaxIs the maximum value of the absorbance of all housing doors and windows in a community, LAminThe minimum value of the absorbance of all housing doors and windows in the community;
in this step, the light transmittance factor of the door and window refers to the ability of light to penetrate through the building door and window. Specifically, when the incident light intensity l is0At a certain time, the medium absorbs the intensity l of lightaThe greater the intensity l of the transmitted lighttThe smaller. By at/l0Representing the ability of light to pass through the medium, called light transmittance, denoted by T, i.e. T ═ lt/l0. The light transmittance value is percentage and ranges from 0% to 100%. If the light is totally absorbed by the medium,/tT is 0. And if the light is totally transmitted, thentL0, T100%. The reciprocal of the transmittance reflects the degree of absorption of light by the medium. For the sake of calculation, the absorbance, expressed as LA, is the logarithm of the reciprocal of the transmittance, i.e.
Figure BDA0002961910260000103
Figure BDA0002961910260000104
Similarly, the calculation results of this step are converted into [0, 10]]And (5) score values are stored.
Calculating the factor value of the floor height light factor according to the following formula:
Figure BDA0002961910260000105
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000106
is the factor score, LH, of the light factor of the ith suite floor height in the celliThe light value of the floor height of the ith suite in the cell is shown, and H is the building height of the single building in which the ith suite is located in the cell;
in this step, the floor height lighting factor means that the lighting of the housing changes along with the change of the floor height for the same single building. Generally speaking, for the same building, the higher the floor is, the better the lighting effect is. The higher the floor height, the better the lighting, without taking into account other influencing factors. The floor height (light) of each set of housing is measured from the ground level of the first floor of each single building to the floor level of the upper floor of the single building. Similarly, the calculation results of this step are converted into [0, 10] scores and stored.
Calculating the factor score of the sunshine duration factor according to the following formula:
Figure BDA0002961910260000107
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000108
the factor score is the sunshine time factor of the ith set of rooms in the cell, and SD is the sunshine time of the ith set of rooms in the cell;
in this step, the sunshine duration factor is the sum of the time periods that the direct solar radiation degree of the house reaches or exceeds 120 watts per square meter within 24 hours a day, and one decimal number is taken in the unit of hour. Sunshine hours affect the indoor light environment of a building. And simulating and counting the day sunshine time of each set of rooms in the same building under normal climatic conditions by using a building information model and related software, selecting the day sunshine time with the shortest sunshine time as the sunshine time SD of the set of rooms, and converting the calculation result of the step into a value of [0, 10] and storing the value in the same way.
Calculating the factor value of the openable area factor of the door and window according to the following formula:
Figure BDA0002961910260000111
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000112
factor value of openable area factor of ith suite door and window in community, SOiFor openable area of door and window of ith suite of residential quarter, SOmaxIs the maximum value of the openable area of doors and windows in all houses in a community, SOminThe minimum value of the openable area of the doors and windows in all the houses in the community;
in this step, the openable area factor of the door and window means the area of the housing door and window which can be opened for indoor ventilation. The opening area of the door and the window affects the indoor wind environment. Similarly, the calculation results of this step are converted into [0, 10] scores and stored.
Calculating the factor score of the floor height wind factor according to the following formula:
Figure BDA0002961910260000113
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000114
is the factor score, WH, of the wind factor of the ith suite floor height in the communityiThe height (wind) of the floor of the ith suite of rooms in the community, and H is the building height of the single building where the ith suite of rooms is located in the community;
in this step, the floor height wind factor means that the ventilation of the housing changes along with the change of the floor height for the same single building. Generally speaking, for the same building, the higher the floor, the better the ventilation effect. The floor height and wind factor of each set of housing is measured from the ground elevation of the first floor of each single building to the floor elevation of the upper floor of the single building. Similarly, the calculation results of this step are converted into [0, 10] scores and stored.
Calculating the factor score of the building orientation factor according to the following formula:
Figure BDA0002961910260000115
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000116
is the factor score, theta, of the ith suite building orientation factor in the celliThe building orientation of the ith suite in the cell;
in this step, the building orientation factor refers to the orientation of the major sunlight receiving surface of each set of housing. The building orientation affects indoor thermal comfort, theoretically the best time and orientation of day-to-day sun exposure is in the true south direction at 12 pm, with the greater the angle to the east or west, the worse the sun exposure. And taking the orientation of the main sunlight receiving surface of each set of housing as the building orientation, recording the south orientation as 0 degrees and the north orientation as 180 degrees from the true south to the true north, calculating the building orientation angle of each set of housing in each building of the same community, and converting the calculation result of the step into a value of [0, 10] and storing the value in the same way.
Calculating a factor score for the air flow velocity factor according to:
Figure BDA0002961910260000121
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000122
the factor score is the air flow speed factor of the ith set of rooms in the cell, and AV is the indoor air flow speed of each set of rooms in the same cell;
in this step, the air flow velocity factor refers to the velocity of air flow in the housing. The air flow velocity is calculated by the formula:
Figure BDA0002961910260000123
wherein AV is the air flow speed and the unit is m/s; v is the volume flow rate in m3/s(1m3/h＝3600m3S); s is the air circulation area, and the unit is square meter; w is mass flow rate, and the unit is kg/s; rho is the gas density in kg/m3。
The air flow speed influences the thermal comfort of the indoor environment of the building, and in a specific application scene, the most comfortable indoor air flow speed meeting the requirement of human comfort is 0.1-0.7 m/s. And calculating the air flow speed AV of each set of houses in each building of the same community, and similarly, converting the calculation result of the step into a value of [0, 10] and storing the value.
Calculating the factor value of the heat transfer coefficient factor of the wall door and window according to the following formula:
Figure BDA0002961910260000124
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000125
the factor value of the heat transfer coefficient factor of the ith suite of walls, doors and windows in a community, HTCiThe heat transfer coefficient of the wall, door and window of the ith suite of the residential quarter, HTCmaxThe maximum value of the heat transfer coefficient of the wall door and window in all the houses in the community, HTCminThe minimum value of the heat transfer coefficient of the wall door and window in all the houses in the community.
In this step, the heat transfer coefficient factors of the wall, the door and the window refer to the heat transfer coefficients of the wall and the door and the window of the housing, and reflect the thermal performance of the housing heat insulation system. Generally, a reduction in heat transfer coefficient may result in a reduction in energy consumption of a building. Specifically, under the condition that the outer wall is affected by the peripheral thermal bridge, the average heat transfer coefficient is calculated according to the following formula:
Figure BDA0002961910260000126
in the formula, KmIs the average heat transfer coefficient [ W/(m) of the outer wall2·k)]；KpThe heat transfer coefficient [ W/(m) of the main body part of the outer wall2·k)]；
Figure BDA0002961910260000127
The heat transfer coefficient [ W/(m) of the heat bridge part at the periphery of the outer wall2·k)]；FpIs the area of the main body part of the outer wall;
Figure BDA0002961910260000128
the area of the heat bridge part at the periphery of the outer wall;
calculating the heat transfer coefficient of the aluminum alloy door and window according to the following formula:
Uw＝(Af×Uf+Ag×Ug+Lg×ψg)/(Af+Ag)
in the formula of UwIs the heat transfer coefficient (W/m) of the whole window2·k)；UgHeat transfer coefficient (W/m) for glass2·k)；AgIs the area m of the glass2；UfIs the heat transfer coefficient (W/m) of the profile2·k)；AfIs the area m of the section bar2；LgIs the circumference m of the glass; psigLinear heat transfer coefficient (W/m) for glass periphery2K), field testing.
The window is composed of sash material and glass system, and if the heat transfer of the glass and sash is assumed to be strictly parallel, the total thermal insulation coefficient R of the window is:
Figure BDA0002961910260000131
in the formula, Rg0The total thermal insulation coefficient for the glass system (referring to the thermal insulation coefficient from the inside air to the outside air of the subject under consideration);
Figure BDA0002961910260000132
the total thermal insulation coefficient (the thermal insulation coefficient from the inside air to the outside air of the considered object) corresponding to the frame fan; fgIs the area of the glass; ffThe area of the window frame;
if the area ratio eta occupied by the frame fan is knownf：ηf＝Ff/(Fg+Ff) Then, using the corresponding heat transfer coefficient U value to represent, the following relation can be obtained:
U＝Ug+ηf×(Uf-Ug)
in the formula of UgThe heat transfer coefficient of glass; u shapefThe heat transfer coefficient of the window frame.
The larger the heat transfer coefficient, the worse the heat preservation effect of the enclosure structure is, for example, the heat transfer coefficient of a metal window with a single layer of glass with the thickness of 3mm is 6.4[ W/(m2 k) ], and the heat transfer coefficient of a brick wall with two plastered surfaces with the thickness of 370mm is 1.59[ W/(m2 k) ]. Generally, the heat transfer coefficient from gas to gas (normal pressure) is 10 to 30[ W/(m2 k) ].
After the heat transfer coefficients of the walls and the doors and the windows of each set of the housing are obtained through calculation, the average value of the heat transfer coefficients is calculated, namely the heat transfer coefficients HTC of the walls and the doors and the windows of each set of the housing, all measured data are converted into values of [0, 10] and stored, and the heat transfer coefficients HTC of the walls and the doors and the windows of each set of the housing are obtained according to the following formula:
Figure BDA0002961910260000133
in the formula, HTCiThe heat transfer coefficient of the wall, the door and the window of the ith set of rooms,
Figure BDA0002961910260000134
is the average heat transfer coefficient, U, of the j outer wall of the ith suite in the communityKThe heat transfer coefficient of the window at k of the ith suite in the cell.
In this embodiment, the factor score of each second factor is calculated to obtain 12 corresponding factor scores, so that the score of the room comfort level in the subsequent step can be calculated according to the 12 factor scores.
Further, the 12 factor scores obtained by the above calculation are normalized, and in a specific embodiment, a normalization method is used to normalize the 12 factor scores. In particular, for sequence x1，x2，……，xnAnd (3) carrying out transformation:
Figure BDA0002961910260000141
wherein the content of the first and second substances,
Figure BDA0002961910260000142
x is the factor score described in this embodiment, and n is 12, that is, 12 factor scores are referred to, then:
Figure BDA0002961910260000143
i.e. the new sequence y1，y2，……，ynHas a mean value of 0 and a variance of 1, and is dimensionless.
In one embodiment, the step S105 includes:
the room comfort score is calculated as follows:
Figure BDA0002961910260000144
Figure BDA0002961910260000145
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000146
respectively the second factor C of the ith set of rooms in a certain cell1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding factor score, ω1、2、3、…、12Respectively the second factor C1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding weight, SVi、Li、Wi、TiEach being a factor score, W, of a first factor of the ith set of rooms in a cell1、2、3、4Respectively, the weights corresponding to the first factors,
Figure BDA0002961910260000147
is a score of room comfort.
In this embodiment, the factor scores of the first factors, that is, the factor scores of the acoustic factors, the light factors, the wind factors, and the heat factors, are respectively calculated, and then the factor scores of the first factors are multiplied by the corresponding first weights, so that the final score of the room comfort level can be obtained.
Fig. 3 is a schematic block diagram of an intelligent room selection apparatus 300 based on human comfort requirement according to an embodiment of the present invention, where the apparatus 300 includes:
a model construction unit 301, configured to construct a fuzzy hierarchical analysis structure model including a second hierarchy and a third hierarchy, which is targeted at room comfort; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
a result obtaining unit 302, configured to obtain a comparison result and a scoring result of the user for each factor in the second hierarchy and the third hierarchy, and construct a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
a first weight calculating unit 303, configured to calculate, by using the fuzzy complementary judging matrix, a first weight corresponding to each of the first factors and a second weight corresponding to each of the second factors;
a score obtaining unit 304, configured to obtain a factor score corresponding to each second factor;
a combination calculation unit 305, configured to perform score calculation on the room comfort level by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor, and the factor score, and feed back a calculation result to the user;
a decision execution unit 306, configured to obtain a decision feedback of the user on the calculation result, and execute a corresponding decision.
In one embodiment, the first factors comprise sound factors, light factors, wind factors and heat factors, the subordinate second factors of the sound factors comprise a main noise source distance factor, a material sound insulation performance factor and a floor height sound factor, the subordinate second factors of the light factors comprise a door and window opening area factor, a door and window light transmittance factor, a floor height light factor and a sunshine time factor, the subordinate second factors of the wind factors comprise a door and window opening area factor and a floor height wind factor, and the heat factors comprise a building orientation factor, an air flow speed factor and a wall door and window heat transfer coefficient factor.
In an embodiment, the model building unit 301 comprises:
the first matrix construction unit is used for acquiring a first comparison result and a first scoring result of pairwise comparison of the first factors by the user aiming at the second level, and constructing a first fuzzy judgment matrix based on the first comparison result and the first scoring result;
the second matrix construction unit is used for acquiring a second comparison result and a second scoring result of pairwise comparison of the user on a second factor subordinate to the sound factor aiming at a third level, and constructing a second fuzzy judgment matrix based on the second comparison result and the second scoring result;
the third matrix construction unit is used for acquiring a third comparison result and a third scoring result of pairwise comparison of the second factors subordinate to the optical factors by the user aiming at a third level, and constructing a third fuzzy judgment matrix based on the third comparison result and the third scoring result;
the fourth matrix construction unit is used for acquiring a fourth comparison result and a fourth scoring result of pairwise comparison of the second factor subordinate to the wind factor by the user aiming at the third level, and constructing a fourth fuzzy judgment matrix based on the fourth comparison result and the fourth scoring result;
the fifth matrix construction unit is used for acquiring a fifth comparison result and a fifth scoring result of pairwise comparison of the user on a second factor subordinate to the thermal factor aiming at the third level, and constructing a fifth fuzzy judgment matrix based on the fifth comparison result and the fifth scoring result;
and the matrix setting unit is used for taking the first fuzzy judgment matrix, the second fuzzy judgment matrix, the third fuzzy judgment matrix, the fourth fuzzy judgment matrix and the fifth fuzzy judgment matrix as the fuzzy complementary judgment matrix.
In one embodiment, the first weight calculating unit 303 includes:
a second weight calculation unit configured to calculate each of the first weight and the second weight according to the following equation:
Figure BDA0002961910260000161
in the formula, WiIs the weight of the ith factor, αijAnd judging the jth element of the ith row in the fuzzy complementary judgment matrix.
In an embodiment, the intelligent room selection device 300 based on human comfort requirement further includes:
the definition unit is used for carrying out consistency definition on the fuzzy complementary judgment matrix by utilizing additive definition or multiplicative definition;
a checking unit, configured to perform consistency check on the fuzzy complementation judgment matrix based on sufficient requirements of the fuzzy complementation judgment matrix, where the sufficient requirements are: in the fuzzy complementary judging matrix, the difference between corresponding elements of any appointed row and other rows is a constant.
In one embodiment, the score obtaining unit 304 includes:
a main noise source distance factor calculating unit for calculating a factor score of the main noise source distance factor according to the following formula:
Figure BDA0002961910260000162
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000163
is the factor score, NL, of the wind factor for the ith suite floor height in a cellmaxThe noise of the room with the largest noise in each set of houses in the same community is obtained;
the material sound insulation performance factor calculating unit is used for calculating the factor value of the material sound insulation performance factor according to the following formula:
Figure BDA0002961910260000164
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000165
is the factor score, SRI, of the sound insulation performance factor of the ith suite of materials in a communityiIs the material sound insulation index, SRI, of the ith suite in a communitymaxIs the maximum value of the material sound insulation index, SRI, of all dwellings in a communityminThe minimum value of the sound insulation index of the materials of all the houses in a certain cell;
the floor height sound factor calculating unit is used for calculating the factor score of the floor height sound factor according to the following formula:
Figure BDA0002961910260000166
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000167
is the factor score, HV, of the acoustic factors of the ith suite floor height in the celliThe sound score of the floor height of the ith suite in the cell; h is the building height of the single building where the ith suite is located in the cell;
the door and window opening area factor calculating unit is used for calculating the factor value of the door and window opening area factor according to the following formula:
Figure BDA0002961910260000171
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000172
is the factor score, SD, of the ith suite door and window opening area factor in the communityiIs the area of the door and window opening, SD, of the ith suite of rooms in the communitymaxIs the maximum value of the door and window opening area, SD, of all houses in the residential areaminThe minimum value of the door and window opening areas of all houses in the community;
the door and window light transmittance factor calculating unit is used for calculating the factor value of the door and window light transmittance factor according to the following formula:
Figure BDA0002961910260000173
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000174
is the factor score, LA, of the light transmittance factor of the ith suite of doors and windows in a communityiIs the absorbance of the door and window of the ith suite in the community, LAmaxIs the maximum value of the absorbance of all housing doors and windows in a community, LAminThe minimum value of the absorbance of all housing doors and windows in the community;
the floor height light factor calculating unit is used for calculating the factor value of the floor height light factor according to the following formula:
Figure BDA0002961910260000175
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000176
is the factor score, LH, of the light factor of the ith suite floor height in the celliThe light value of the floor height of the ith suite in the cell is shown, and H is the building height of the single building in which the ith suite is located in the cell;
a sunshine time factor calculating unit for calculating a factor score of the sunshine time factor according to the following formula:
Figure BDA0002961910260000177
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000178
the factor score is the sunshine time factor of the ith set of rooms in the cell, and SD is the sunshine time of the ith set of rooms in the cell;
the door and window openable area factor calculating unit is used for calculating the factor value of the door and window openable area factor according to the following formula:
Figure BDA0002961910260000179
in the formula (I), the compound is shown in the specification,
Figure BDA00029619102600001710
factor value of openable area factor of ith suite door and window in community, SOiFor openable area of door and window of ith suite of residential quarter, SOmaxIs the maximum value of the openable area of doors and windows in all houses in a community, SOminThe minimum value of the openable area of the doors and windows in all the houses in the community;
the building height wind factor calculating unit is used for calculating the factor value of the building height wind factor according to the following formula:
Figure BDA0002961910260000181
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000182
is the factor score, WH, of the wind factor of the ith suite floor height in the communityiThe height (wind) of the floor of the ith suite of rooms in the community, and H is the building height of the single building where the ith suite of rooms is located in the community;
a building orientation factor calculating unit for calculating a factor score of the building orientation factor according to the following formula:
Figure BDA0002961910260000183
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000184
is the factor score, theta, of the ith suite building orientation factor in the celliThe building orientation of the ith suite in the cell;
an air flow velocity factor calculation unit for calculating a factor score of the air flow velocity factor according to:
Figure BDA0002961910260000185
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000186
the factor score is the air flow speed factor of the ith set of rooms in the cell, and AV is the indoor air flow speed of each set of rooms in the same cell;
the wall door and window heat transfer coefficient factor calculating unit is used for calculating the factor value of the wall door and window heat transfer coefficient factor according to the following formula:
Figure BDA0002961910260000187
in the formula (I), the compound is shown in the specification,
Figure BDA0002961910260000188
the factor value of the heat transfer coefficient factor of the ith suite of walls, doors and windows in a community, HTCiThe heat transfer coefficient of the wall, door and window of the ith suite of the residential quarter, HTCmaxThe maximum value of the heat transfer coefficient of the wall door and window in all the houses in the community, HTCminThe minimum value of the heat transfer coefficient of the wall door and window in all the houses in the community.
In one embodiment, the combination calculating unit 305 includes:
a comfort score calculation unit for calculating a score of room comfort according to the following formula:
Figure BDA0002961910260000189
Figure BDA00029619102600001810
in the formula (I), the compound is shown in the specification,
Figure BDA00029619102600001811
respectively the second factor C of the ith set of rooms in a certain cell1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding factor score, ω1、2、3、…、12Respectively the second factor C1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding weight, SVi、Li、Wi、TiEach being a factor score, W, of a first factor of the ith set of rooms in a cell1、2、3、4Respectively, the weights corresponding to the first factors,
Figure BDA00029619102600001812
is a score of room comfort.
Since the embodiments of the apparatus portion and the method portion correspond to each other, please refer to the description of the embodiments of the method portion for the embodiments of the apparatus portion, which is not repeated here.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the steps provided by the above embodiments can be implemented. The storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The embodiment of the present invention further provides a computer device, which may include a memory and a processor, where the memory stores a computer program, and the processor may implement the steps provided in the above embodiments when calling the computer program in the memory. Of course, the computer device may also include various network interfaces, power supplies, and the like.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

Claims (10)

1. An intelligent room selection method based on human body comfort level requirements is characterized by comprising the following steps:
constructing a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
obtaining a comparison result and a scoring result of a user for each factor in the second level and the third level, and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
calculating a first weight corresponding to each first factor and a second weight corresponding to each second factor by using the fuzzy complementary judgment matrix;
acquiring a factor score corresponding to each second factor;
calculating the score of the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back the calculation result to the user;
and obtaining the decision feedback of the user on the calculation result, and executing the corresponding decision.
2. The intelligent room selection method based on the human body comfort requirement as claimed in claim 1, wherein the first factors comprise sound factors, light factors, wind factors and heat factors, the subordinate second factors of the sound factors comprise a main noise source distance factor, a material sound insulation performance factor and a floor height sound factor, the subordinate second factors of the light factors comprise a door and window opening area factor, a door and window light transmittance factor, a floor height light factor and a sunshine time factor, the subordinate second factors of the wind factors comprise a door and window opening area factor and a floor height wind factor, and the heat factors comprise a building orientation factor, an air flow speed factor and a wall door and window heat transfer coefficient factor.
3. The intelligent room selection method based on the human comfort requirement as claimed in claim 2, wherein the obtaining of the comparison result and the scoring result of the user for each factor in the second level and the third level, and the constructing of the fuzzy complementary judgment matrix based on the comparison result and the scoring result comprise:
aiming at a second level, acquiring a first comparison result and a first grading result of pairwise comparison of a first factor by a user, and constructing a first fuzzy judgment matrix based on the first comparison result and the first grading result;
aiming at the third level, acquiring a second comparison result and a second scoring result of pairwise comparison of a second factor subordinate to the sound factor by the user, and constructing a second fuzzy judgment matrix based on the second comparison result and the second scoring result;
aiming at a third level, acquiring a third comparison result and a third scoring result of pairwise comparison of a second factor subordinate to the optical factor by a user, and constructing a third fuzzy judgment matrix based on the third comparison result and the third scoring result;
aiming at the third level, acquiring a fourth comparison result and a fourth scoring result of pairwise comparison of the second factor subordinate to the wind factor of the user, and constructing a fourth fuzzy judgment matrix based on the fourth comparison result and the fourth scoring result;
aiming at the third level, acquiring a fifth comparison result and a fifth scoring result of pairwise comparison of the user on a second factor subordinate to the thermal factor, and constructing a fifth fuzzy judgment matrix based on the fifth comparison result and the fifth scoring result;
and taking the first fuzzy judgment matrix, the second fuzzy judgment matrix, the third fuzzy judgment matrix, the fourth fuzzy judgment matrix and the fifth fuzzy judgment matrix as the fuzzy complementary judgment matrix.
4. The intelligent room selection method based on human comfort requirement as claimed in claim 1, wherein the calculating a first weight corresponding to each of the first factors and a second weight corresponding to each of the second factors by using the fuzzy complementary judging matrix comprises:
calculating each of the first weight and the second weight according to:
Figure FDA0002961910250000021
in the formula, WiIs the weight of the ith factor, αijIs that it isAnd (4) blurring the jth element in the ith row in the complementary judgment matrix.
5. The intelligent room selection method based on the human comfort requirement as claimed in claim 3, further comprising:
carrying out consistency definition on the fuzzy complementary judgment matrix by utilizing additive definition or multiplicative definition;
performing consistency check on the fuzzy complementation judgment matrix based on sufficient necessary conditions of the fuzzy complementation judgment matrix, wherein the sufficient necessary conditions are as follows: in the fuzzy complementary judging matrix, the difference between corresponding elements of any appointed row and other rows is a constant.
6. The intelligent room selection method based on the human comfort requirement as claimed in claim 1, wherein the obtaining of the factor score corresponding to each second factor comprises:
calculating the factor score of the primary noise source distance factor according to the following formula:
Figure FDA0002961910250000022
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000023
is a factor score, NL, of the distance factor of the main noise source of the ith suite in a cellmaxThe noise of the room with the largest noise in each set of houses in the same community is obtained;
calculating the factor value of the sound insulation performance factor of the material according to the following formula:
Figure FDA0002961910250000031
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000032
is the factor score, SRI, of the sound insulation performance factor of the ith suite of materials in a communityiIs the material sound insulation index, SRI, of the ith suite in a communitymaxIs the maximum value of the material sound insulation index, SRI, of all dwellings in a communityminThe minimum value of the sound insulation index of the materials of all the houses in a certain cell;
calculating the factor score of the floor height acoustic factor according to the following formula:
Figure FDA0002961910250000033
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000034
is the factor score, HV, of the acoustic factors of the ith suite floor height in the celliThe sound score of the floor height of the ith suite in the cell; h is the building height of the single building where the ith suite is located in the cell;
calculating the factor value of the door and window opening area factor according to the following formula:
Figure FDA0002961910250000035
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000036
is the factor score, SD, of the ith suite door and window opening area factor in the communityiIs the area of the door and window opening, SD, of the ith suite of rooms in the communitymaxIs the maximum value of the door and window opening area, SD, of all houses in the residential areaminThe minimum value of the door and window opening areas of all houses in the community;
calculating the factor value of the light transmittance factor of the door and window according to the following formula:
Figure FDA0002961910250000037
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000038
is the factor score, LA, of the light transmittance factor of the ith suite of doors and windows in a communityiIs the absorbance of the door and window of the ith suite in the community, LAmaxIs the maximum value of the absorbance of all housing doors and windows in a community, LAminThe minimum value of the absorbance of all housing doors and windows in the community;
calculating the factor value of the floor height light factor according to the following formula:
Figure FDA0002961910250000039
in the formula (I), the compound is shown in the specification,
Figure FDA00029619102500000310
is the factor score, LH, of the light factor of the ith suite floor height in the celliThe light value of the floor height of the ith suite in the cell is shown, and H is the building height of the single building in which the ith suite is located in the cell;
calculating the factor score of the sunshine duration factor according to the following formula:
Figure FDA00029619102500000311
in the formula (I), the compound is shown in the specification,
Figure FDA00029619102500000312
the factor score is the sunshine time factor of the ith set of rooms in the cell, and SD is the sunshine time of the ith set of rooms in the cell;
calculating the factor value of the openable area factor of the door and window according to the following formula:
Figure FDA00029619102500000313
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000041
factor value of openable area factor of ith suite door and window in community, SOiFor openable area of door and window of ith suite of residential quarter, SOmaxIs the maximum value of the openable area of doors and windows in all houses in a community, SOminThe minimum value of the openable area of the doors and windows in all the houses in the community;
calculating the factor score of the floor height wind factor according to the following formula:
Figure FDA0002961910250000042
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000043
is the factor score, WH, of the wind factor of the ith suite floor height in the communityiThe height (wind) of the floor of the ith suite of rooms in the community, and H is the building height of the single building where the ith suite of rooms is located in the community;
calculating the factor score of the building orientation factor according to the following formula:
Figure FDA0002961910250000044
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000045
is the factor score, theta, of the ith suite building orientation factor in the celliThe building orientation of the ith suite in the cell;
calculating a factor score for the air flow velocity factor according to:
Figure FDA0002961910250000046
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000047
the factor score is the air flow speed factor of the ith set of rooms in the cell, and AV is the indoor air flow speed of each set of rooms in the same cell;
calculating the factor value of the heat transfer coefficient factor of the wall door and window according to the following formula:
Figure FDA0002961910250000048
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000049
the factor value of the heat transfer coefficient factor of the ith suite strong door and window in the community, HTCiThe heat transfer coefficient of the wall, door and window of the ith suite of the residential quarter, HTCmaxThe maximum value of the heat transfer coefficient of the wall door and window in all the houses in the community, HTCminThe minimum value of the heat transfer coefficient of the wall door and window in all the houses in the community.
7. The intelligent room selection method based on human comfort degree demand according to claim 6, wherein the calculating of the scores of the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor scores and the feeding back of the calculation result to the user comprise:
the room comfort score is calculated as follows:
Figure FDA00029619102500000410
Figure FDA00029619102500000411
in the formula (I), the compound is shown in the specification,
Figure FDA0002961910250000051
respectively the second factor C of the ith set of rooms in a certain cell1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding factor score, ω1、2、3、…、12Respectively the second factor C1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12Corresponding weight, SVi、Li、Wi、TiEach being a factor score, W, of a first factor of the ith set of rooms in a cell1、2、3、4Respectively, the weights corresponding to the first factors,
Figure FDA0002961910250000052
is a score of room comfort.
8. The utility model provides an intelligence device of selecting a house based on human comfort level demand which characterized in that includes:
the model building unit is used for building a fuzzy hierarchical analysis structure model which takes the room comfort level as a target and comprises a second level and a third level; the second level is a plurality of first factors having influence on the comfort of the room, and the third level is a second factor subordinate to each first factor;
the result acquisition unit is used for acquiring a comparison result and a scoring result of each factor in the second level and the third level of the user and constructing a fuzzy complementary judgment matrix based on the comparison result and the scoring result;
a first weight calculation unit, configured to calculate, by using the fuzzy complementary judging matrix, a first weight corresponding to each of the first factors and a second weight corresponding to each of the second factors;
the score acquisition unit is used for acquiring the factor score corresponding to each second factor;
the combination calculation unit is used for performing score calculation on the room comfort degree by combining the first weight corresponding to the first factor, the second weight corresponding to the second factor and the factor score, and feeding back a calculation result to a user;
and the decision execution unit is used for acquiring the decision feedback of the user on the calculation result and executing the corresponding decision.
9. Computer device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the intelligent room selection method based on human comfort needs as claimed in any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which when executed by a processor implements the intelligent room selection method based on human comfort needs of any one of claims 1 to 7.
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