CN114529194A - Method and device for evaluating quality of public space - Google Patents

Method and device for evaluating quality of public space Download PDF

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CN114529194A
CN114529194A CN202210152944.5A CN202210152944A CN114529194A CN 114529194 A CN114529194 A CN 114529194A CN 202210152944 A CN202210152944 A CN 202210152944A CN 114529194 A CN114529194 A CN 114529194A
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李方方
贾慧彤
杨杰
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Beijing Digsur Science And Technology Co ltd
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Abstract

The invention provides a method and a device for evaluating quality of a public space. The method comprises the steps of obtaining index factor data, and determining an index factor set and an evaluation grade set of a target object; determining a fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors; carrying out statistical normalization on the quantitative index factor data to obtain a fuzzy relation matrix of the quantitative index factors, and synthesizing a comprehensive fuzzy relation matrix; calculating the weight of the index factors to obtain a weight vector; synthesizing the weight vector and the comprehensive fuzzy relation matrix to obtain an evaluation value of the target object; and carrying out single-valued processing on the evaluation value, and evaluating the public space quality of the target object through the obtained evaluation single value of the target object. In this way, qualitative and quantitative comprehensive quantitative evaluation of the public space quality is realized, and the evaluation accuracy of the public space quality can be effectively improved.

Description

Method and device for evaluating quality of public space
Technical Field
The present invention relates generally to the field of data analysis, and more particularly to a method and apparatus for evaluating quality of a common space.
Background
The third united nations house and the city sustainable development general meeting (abbreviated as 'human residence III') aims to construct a 'safe, inclusive, usable, green and high-quality' public space through a 'new city agenda' resolution, and further expands the connotation of the quality of the public space of the city in the new period. The new urban agenda also states that public spaces including streets, sidewalks and bicycle lanes, squares, waterfront areas, gardens, parks and the like are multifunctional areas for promoting social interaction and accommodation among the masses of people and among various cultures, health and welfare of people, economic communication, cultural expression and conversation, and the design and management of the multifunctional areas aim to ensure the human development, build peaceful, inclusive and participatory society and promote the co-location, interconnection and social accommodation.
In conclusion, the high-quality construction of public spaces has great significance for improving the quality of human life, and is a necessary trend of urban development. At present, the quality of urban public spaces is uneven, and the quality of the public spaces needs to be evaluated scientifically and comprehensively before modification, so that an effective promotion strategy is adopted. However, no consensus and operable evaluation index system and evaluation method has been established at home and abroad.
Disclosure of Invention
According to an embodiment of the present invention, an evaluation scheme of common spatial quality is provided. According to the scheme, various index factors can be comprehensively considered, and qualitative and quantitative comprehensive evaluation on the quality of the public space is realized.
In a first aspect of the invention, a method for estimating quality of a common space is provided. The method comprises the following steps:
acquiring index factor data for determining the quality of the public space, and determining an index factor set and an evaluation grade set of a target object according to the index factor data; the index factor set of the target object comprises qualitative index factors and quantitative index factors;
determining a fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors; carrying out statistical normalization on quantitative index factor data in the index factor data determining the public space quality to obtain a fuzzy relation matrix of the quantitative index factors; synthesizing the fuzzy relation matrix of the qualitative index factors and the fuzzy relation matrix of the quantitative index factors into a comprehensive fuzzy relation matrix;
calculating the weight of the index factors in the index factor set by using a grey level evaluation method to obtain a weight vector;
selecting a fuzzy operator, and synthesizing the weight vector and the fuzzy relation matrix to obtain an evaluation value of the target object;
and carrying out single-valued processing on the evaluation value of the target object, and evaluating the public space quality of the target object through the obtained evaluation single value of the target object.
Further, the index factor set is:
U＝{U1,U2,...,Ui,...,Un}
Ui＝{ui1,ui2,,...,uij,...,uim}
wherein U is an index factor set of the public space quality of the target object; u shapeiAn ith primary index factor of the common spatial quality of the target object; u. ofijA jth secondary index factor of the ith primary index factors of the common spatial quality of the target object; m is the number of secondary index factors in the ith primary index factor of the public space quality of the target object; n is the number of primary index factors of the public space quality of the target object;
the evaluation grade set is as follows:
V＝{v1,v2,...,vi,...,vx}
wherein V is an evaluation level set of the quality of the public space of the target object; v. ofiAn ith evaluation level of the common spatial quality of the target object; x is the number of evaluation levels.
Further, the fuzzy relation matrix of the qualitative index factors is as follows:
Figure BDA0003511319300000031
wherein R' is a fuzzy relation matrix of qualitative index factors; r'ijThe membership of the ith qualitative index factor in the index factor set corresponding to the jth evaluation level in the evaluation level set; p is the number of qualitative index factors; x is the number of evaluation grades;
the fuzzy relation matrix of the quantitative index factors is as follows:
Figure BDA0003511319300000032
wherein, R' is a fuzzy relation matrix of quantitative index factors; rijThe membership relation of the ith quantitative index factor in the index factor set corresponding to the jth evaluation interval in the evaluation interval set is obtained; q is the number of quantitative index factors, p + q is equal to n, and n is the number of first-level index factors of the public space quality of the target object; x 'is the number of the evaluation intervals, and the number x of the evaluation grades is equal to the number x' of the evaluation intervals;
the comprehensive fuzzy relation matrix is as follows:
Figure BDA0003511319300000033
wherein, R is a fuzzy relation matrix of the comprehensive index factors; r isijAnd the membership relation of the ith index factor in the index factor set corresponding to the jth evaluation level in the evaluation level set is obtained.
Further, the calculating the weight of the index factors in the index factor set by using a gray level evaluation method to obtain a weight vector includes:
firstly, presetting the grade number of index factors of the public space quality, the gray number of the index factors and a whitening function of the gray number;
secondly, respectively calculating a gray evaluation coefficient of each index factor according to the number of grades of the index factors and a whitening function of the gray number, and respectively calculating a total gray evaluation coefficient of each index factor for each gray number;
then, calculating the grey evaluation weight of each index factor belonging to the grey number, and obtaining the weight vector by calculating the weights of different index factors;
the weight vector is:
Figure BDA0003511319300000041
ai＝{ai1,ai2,...,aij,...,aiy}T
wherein A is a weight vector; a isiThe weight of the ith primary index factor in the index factor set is obtained; a isijThe weight of the jth secondary index factor in the ith primary index factor in the index factor set; n is the number of primary index factors of the public space quality of the target object; y represents aiThe number of the included secondary index factors; t denotes transposition.
Further, the evaluation value of the target object is:
Figure BDA0003511319300000042
wherein B is an evaluation value of the common spatial quality of the target object; biAn evaluation value of an i-th index factor that is a common spatial quality of the target object; n is the number of primary index factors of the public space quality of the target object; a is a weight vector; r is a comprehensive fuzzy relation matrix;
Figure BDA0003511319300000043
representing the selected blurring operator.
Further, the performing univocal processing on the evaluation value of the target object includes:
B′＝BCT
wherein B' is an evaluation unit of the common spatial quality of the target object; b is an evaluation value of the common spatial quality of the target object; cTIs a levelized vector.
Further, the evaluating the common spatial quality of the target object by the obtained evaluation single value of the target object includes:
if the evaluation unit value of the target object is larger, the public space quality of the target object is higher;
and if the evaluation unit value of the target object is smaller, the public space quality of the target object is poorer.
Further, still include:
carrying out sensitivity analysis on the evaluation single value of the target object to obtain the contribution degree of the factor index;
and sorting the contribution degrees of the factor indexes from large to small, wherein the larger the contribution degree is, the larger the effect of the factor indexes in the evaluation of the quality of the public space is.
In a second aspect of the present invention, an apparatus for evaluating quality of a common space is provided. The device includes:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring index factor data for determining the quality of public space and determining an index factor set and an evaluation grade set of a target object according to the index factor data; the index factor set of the target object comprises qualitative index factors and quantitative index factors;
the first synthesis module is used for determining the fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors; carrying out statistical normalization on quantitative index factor data in the index factor data determining the public space quality to obtain a fuzzy relation matrix of the quantitative index factors, and synthesizing a comprehensive fuzzy relation matrix according to the fuzzy relation matrix of the qualitative index factors and the fuzzy relation matrix of the quantitative index factors;
the calculation module is used for calculating the weight of the index factors in the index factor set by using a grey level evaluation method to obtain a weight vector;
the second synthesis module is used for selecting a fuzzy operator, and synthesizing the weight vector and the fuzzy relation matrix to obtain an evaluation value of the target object;
and the evaluation module is used for carrying out single-valued processing on the evaluation value of the target object and evaluating the public space quality of the target object through the obtained evaluation single value of the target object.
In a third aspect of the invention, an electronic device is provided. The electronic device at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect of the invention.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of any embodiment of the invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
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The above and other features, advantages and aspects of various embodiments of the present invention will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 shows a flow diagram of a method of assessment of common spatial quality according to an embodiment of the invention;
FIG. 2 shows a block diagram of an apparatus for estimating common spatial quality according to an embodiment of the invention;
FIG. 3 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present invention;
of these, 300 is an electronic device, 301 is a CPU, 302 is a ROM, 303 is a RAM, 304 is a bus, 305 is an I/O interface, 306 is an input unit, 307 is an output unit, 308 is a storage unit, and 309 is a communication unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
In the invention, various index factors are comprehensively considered, quantitative and qualitative classification is carried out, algorithms such as quantitative statistical calculation and fuzzy comprehensive analysis model are respectively adopted, the comprehensive evaluation of the social quality of the public space is realized, the social value of the public space is reflected, and scientific basis is provided for public space design, resident suitability evaluation, community treatment measure control and the like.
FIG. 1 shows a flow diagram of the evaluation of common spatial quality for an embodiment of the present invention.
S101, acquiring index factor data determining the quality of the public space, and determining an index factor set and an evaluation grade set of a target object according to the index factor data. The set of indicator factors for the target object includes qualitative indicator factors and quantitative indicator factors.
As an embodiment of the present invention, the index factor data determining the quality of the public space includes a primary index and a secondary index; and the first-level index covers the second-level index. For example, the first-level indicators include accessibility, containment, quality, safety, extent of greening, cultural transmission; wherein, the second level index of the accessibility of the first level index comprises an external communication degree, an internal convenience degree, a regional vitality degree and the like; the secondary indexes of the primary containment comprise activity types, user numbers, characteristics and the like; the secondary indexes of the primary index quality comprise infrastructure quality, space quality, noise condition and the like; the secondary indexes of the primary index safety comprise lighting monitoring facilities, crime rate and the like; the secondary indexes of the greening degree of the primary indexes comprise park green land indexes, vegetation growth conditions, vegetation coverage rate and the like; the primary index is a secondary index of cultural transmissibility and comprises cultural factors, cultural facilities and the like. Wherein, the first-level index factors are divided into quantifiable evaluation index factors and quantifiable evaluation index factors. For example, the accessibility, the greening degree and other first-level index factors belong to quantifiable evaluation index factors; the first-level index factors such as inclusion, quality, safety, cultural transmission and the like belong to qualitative assessment factors.
Specifically, index factor data determining the quality of the public space is obtained by two different methods: and the index factor data of the qualitative evaluation is obtained by adopting a questionnaire survey mode, and the index factor data of the quantitative evaluation is obtained by adopting a survey statistic mode.
In order to realize scientific, reasonable and efficient questionnaire survey, a designed questionnaire can be uploaded to a system in an on-line investigation mode, data such as the position, scale, environment, public facility use, noise and the like of a public space are recorded in real time, and a result is output from a background and recorded into a database after screening.
As an embodiment of the present invention, determining an index factor set of a target object according to the index factor data includes:
U＝{U1,U2,...,Ui,...,Un}
Ui＝{ui1,ui2,,...,uij,...,uim}
wherein U is an index factor set of the public space quality of the target object; u shapeiAn ith primary index factor of the common spatial quality of the target object; u. ofijA jth secondary index factor of the ith primary index factors of the common spatial quality of the target object; m is a secondary index factor in the ith primary index factor of the common space quality of the target objectAnd (4) the number.
In the above embodiment, the set of index factors of the target object is:
U＝{U1,U2,U3,U4,U5,U6}
U1＝{u11,u12,u13,}
U2＝{u21,u22}
U3＝{u31,u32,u33}
U4＝{u41,u42}
U5＝{u51,u52,u53}
U6＝{u61,u62}
wherein, U1,U2,U3,U4,U5,U6Respectively corresponding to accessibility, inclusion, quality, safety, greening degree and cultural transmission in the first-level indexes; wherein u is11,u12,u13And (3) respectively corresponding to the second-level indexes of the reachability of the first-level indexes: external communication degree, internal convenience degree, regional vitality degree and the like; u. of21,u22Respectively corresponding to the second-level indexes of the first-level index containment: activity type, number and characteristics of users, etc.; u. u31,u32,u33And secondary indexes corresponding to the quality of the primary indexes respectively: infrastructure quality, space quality, noise conditions, etc.; u. of41,u42And the second-level indexes respectively corresponding to the safety of the first-level indexes are as follows: lighting monitoring facilities, crime rates, etc.; u. of51,u52,u53Respectively corresponding to the second-level indexes of the greening degree of the first-level indexes: park green land indexes, vegetation growth conditions, vegetation coverage and the like; u. of61,u62Respectively corresponding to the second-level indexes of the first-level indexes and the cultural transmissibility: cultural factors, cultural facilities, etc.
As an embodiment of the present invention, the evaluation level set is:
V＝{v1,v2,...,vi,...,vm}
wherein V is an evaluation level set of the quality of the public space of the target object; v. ofmAn ith evaluation level of quality of a common space of the target object; m is the number of evaluation grades. For example, the number m of evaluation levels is 5, v1Representing a low grade, v2Representing a lower rank, v3Representing a general grade, v4Representing a higher rank, v5Representing a high level. The number of evaluation levels may be 3 or 7, and different evaluation levels may be set as necessary.
S102, determining a fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors.
For each alternative, a fuzzy relation R from the set of indicator factors U to the set of evaluation levels V may be determined. The fuzzy relation R' is a single-factor evaluation result of the fuzzy comprehensive evaluation of the qualitative index factors of the quality, and can be expressed in a matrix form, namely a fuzzy relation matrix of the qualitative index factors, as follows:
Figure BDA0003511319300000101
wherein R' is a fuzzy relation matrix of qualitative index factors; r'ijThe membership of the ith qualitative index factor in the index factor set corresponding to the jth evaluation level in the evaluation level set; p is the number of qualitative index factors; x is the number of evaluation levels.
The fuzzy relation R' is a single-factor evaluation result of the fuzzy comprehensive evaluation of the quality quantitative index factors, and is also expressed in a matrix form, namely a fuzzy relation matrix of the quantitative index factors, and comprises the following steps:
Figure BDA0003511319300000102
wherein, R' is a fuzzy relation matrix of quantitative index factors; rijIs the index factor setThe ith quantitative index factor in the evaluation interval set corresponds to the membership of the jth evaluation interval in the evaluation interval set; q is the number of quantitative index factors; x is the number of evaluation intervals. And p + q is n, the evaluation grade is consistent with the number of the evaluation intervals, and the evaluation grade is x.
According to the fuzzy relation matrix R 'of the qualitative index factors and the fuzzy relation matrix R' of the quantitative index factors, the comprehensive fuzzy relation matrix R is obtained through synthesis and calculation, and the following steps are carried out:
Figure BDA0003511319300000103
wherein, R is a fuzzy relation matrix of the comprehensive index factors; r isijThe membership of the ith index factor in the index factor set corresponding to the jth evaluation level in the evaluation level set; n is the number of index factors; x is the number of evaluation levels.
S103, calculating the weight of the index factors in the index factor set by using a gray level evaluation method to obtain a weight vector.
Step 1: the method comprises the steps of presetting the grade number of index factors of the public space quality, the gray number of the index factors and a whitening function of the gray number.
Generally, the number of levels of index factors of the quality of the common space, the number of grays of the index factors, and the whitening function of the number of grays are determined by qualitative analysis for a specific object.
Assuming an index factor value matrix
Figure BDA0003511319300000111
And (4) an index factor value matrix which represents that the evaluator I gives the A-th index factor of the evaluated person J.
Figure BDA0003511319300000112
Wherein A represents a certain index factor, I represents the number of evaluators, and J represents the number of evaluators.
Let index factor number e, e 1, 2. I.e. there are g index factors. For example, the evaluable index factor takes five stages of "high", "higher", "medium", "lower" and "low", i.e., g is 5.
In order to describe the index factors, the gray number of the index factors and the whitening function of the gray number need to be determined. The dialect function is used for describing the possibility, preference degree or satisfaction degree and the like of whitening the gray number into a certain whitening value in a value range, namely whitening the gray system, namely reasonably processing limited survey information to form more information and making the gray system clearer.
As an embodiment of the present invention, when the evaluation gray class is in five grades of "high", "higher", "middle", "lower", "low", the whitening functions used are the following 5 types:
ash 1-th class "high" (e ═ 1), ash class
Figure BDA0003511319300000113
The whitening function is
Figure BDA0003511319300000114
Ash 2 "higher" (e ═ 2), let ash
Figure BDA0003511319300000121
The whitening function is
Figure BDA0003511319300000122
In the 3 rd ash class "(e ═ 3), ash class is defined
Figure BDA0003511319300000123
The whitening function is
Figure BDA0003511319300000124
Ash 4 class "lower"(e ═ 4), and ash is set
Figure BDA0003511319300000125
The whitening function is
Figure BDA0003511319300000126
Ash 5-th class "low" (e is 5), ash class
Figure BDA0003511319300000127
The whitening function is
Figure BDA0003511319300000128
In the above formulae, d1,d2,d3,d4,d5The value of the turning point of the whitening function is called a threshold parameter, and is usually a constraint value such as a maximum value, a minimum value or an impossible value. The maximum, minimum and median values are found from the evaluation sample matrix as the upper, lower and intermediate thresholds.
Step 2: and respectively calculating the grey evaluation coefficient of each index factor according to the grade number of the index factor and the whitening function of the grey number, and respectively calculating the total grey evaluation coefficient of each index factor for each grey number.
By
Figure BDA0003511319300000129
And
Figure BDA00035113193000001210
calculating the evaluation gray coefficient of the evaluated person u to the index factor A belonging to the K-th class, and recording the evaluation gray coefficient as
Figure BDA0003511319300000131
The calculation formula is as follows:
Figure BDA0003511319300000132
for the index factor A, the recruiter J belongs to the total grey evaluation coefficient of each index factor for each grey, and records the total grey evaluation coefficient
Figure BDA0003511319300000133
The calculation formula is as follows:
Figure BDA0003511319300000134
and step 3: and calculating a gray evaluation weight vector and a gray evaluation weight matrix.
By
Figure BDA0003511319300000135
And
Figure BDA0003511319300000136
the evaluation right of the index factor A and the J th evaluated person belonging to the K th gray class can be calculated
Figure BDA0003511319300000137
And relative weight vector
Figure BDA0003511319300000138
Namely:
Figure BDA0003511319300000139
considering K1, 2.. K, there is a gray evaluation weight row vector
Figure BDA00035113193000001310
Figure BDA00035113193000001311
Considering J1, 2.. times.j, there is a gray evaluation weight column vector
Figure BDA00035113193000001312
Figure BDA00035113193000001313
Further, the gray evaluation weight matrix of all the evaluated persons for the index factor A can be obtained
Figure BDA00035113193000001314
Namely:
Figure BDA00035113193000001315
and 4, step 4: from a to a(A)The following were obtained:
Figure BDA00035113193000001316
further, the index evaluation weight vector is obtained as follows:
Figure BDA0003511319300000141
ai＝{ai1,ai2,...,aij,...,ain}T
wherein A is a weight vector; a isiThe weight of the ith index factor in the index factor set; n is the number of index factors; t denotes transposition.
The weight vector a may be represented as:
Figure BDA0003511319300000142
ai＝{ai1,ai2,...,aij,...,ain}T
wherein A is a weight vector; a isiThe weight of the ith primary index factor in the index factor set is obtained; a isijFor the ith index factor in the index factor setThe weight of the jth secondary index factor in the primary index factors; n is the number of primary index factors of the public space quality of the target object; t denotes transposition.
In the above embodiment, the weight vector may be represented as:
Figure BDA0003511319300000143
wherein A is a weight vector; a isiIs the weight of the index factor in the index factor set, i.e.
a1＝{a11 a12 a13}T
a2＝{a21 a22}T
a3＝{a31 a32 a33}T
a4＝{a41 a42}T
a5＝{a51 a52 a53}T。
a6＝{a61 a62}T
And S104, selecting a fuzzy operator, and synthesizing the weight vector and the fuzzy relation matrix to obtain the evaluation value of the target object.
As an embodiment of the present invention, it is possible to select the weighted average type blurring operator "," which balances the weights for all index factors and is suitable for the case of quality requirement as a whole index.
As an embodiment of the present invention, the combining the weight vector and the fuzzy relation matrix, for example, combining a and R to obtain B:
Figure BDA0003511319300000151
in addition, the air conditioner is provided with a fan,
Figure BDA0003511319300000152
the following can be obtained:
Figure BDA0003511319300000153
finally, the evaluation value B of the target object is:
B＝{b1,b2,...,bi,...,bn}
wherein B is an evaluation value of the common spatial quality of the target object; biAn evaluation value of an i-th index factor that is a common spatial quality of the target object; n is the number of index factors; a is a weight vector; r is a fuzzy relation matrix;
Figure BDA0003511319300000154
representing the selected fuzzy operator; and R is a fuzzy relation matrix.
S105, performing single-valued processing on the evaluation value of the target object, and evaluating the public space quality of the target object through the obtained evaluation single value of the target object.
As an embodiment of the present invention, the single-valued processing of the evaluation value of the target object includes:
B′＝BCT
wherein B' is an evaluation unit of the common spatial quality of the target object; b is an evaluation value of the common spatial quality of the target object; cTIs a levelized vector.
Judging the level of the public space quality according to the evaluation value single value of the target object, and realizing quantitative evaluation on the public space quality; the contents of the main factors for evaluating the quality of the public space are comprehensively contrasted and analyzed, and instructive opinions are provided for the improvement measures of the quality of the public space.
As an embodiment of the present invention, the evaluating the common spatial quality of the target object by the obtained evaluation unit of the target object includes:
if the evaluation unit value of the target object is larger, the public space quality of the target object is stronger;
and if the evaluation unit value of the target object is smaller, the public space quality of the target object is weaker.
In some embodiments, a sensitivity principal factor analysis method may be further adopted to perform sensitivity analysis on the evaluation single value of the target object to obtain the contribution degree of the factor index; and sorting the contribution degrees of the factor indexes from large to small, wherein the larger the contribution degree is, the larger the effect of the factor indexes in the evaluation of the quality of the public space is.
The purpose of sensitivity analysis is to find out core elements in public space quality evaluation, sort according to the contribution of each index to the final efficiency value, find out an index set with a large contribution degree to the comprehensive efficiency, and further put the emphasis of analysis on the index sets.
Let the contribution of index factor i be θiAnd then:
Figure BDA0003511319300000161
wherein f is expressed as a synthesis function.
And solving the contribution degrees of the index factors, and sequencing according to the size to find out the index with larger contribution degree, namely the main factor for evaluating the quality of the public space. Finally, the main factors for determining the quality of the public space are determined, and a scientific and powerful basis is provided for the improvement of the public space.
The embodiment of the invention carries out public space assessment, aims to establish a scientific, complete and highly operable assessment index system and assessment method, adheres to the principle of human-oriented, realizes objective, accurate and comprehensive quantitative assessment of the quality of the public space under the current situation, and provides objective basis for scientifically and reasonably formulating urban public space quality promotion plans and carrying out construction activities in the next step.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules illustrated are not necessarily required to practice the invention.
The above is a description of method embodiments, and the embodiments of the present invention are further described below by way of apparatus embodiments.
As shown in fig. 2, the apparatus 200 includes:
the first determining module 210 is configured to obtain index factor data determining the quality of the public space, and determine an index factor set and an evaluation level set of a target object according to the index factor data;
the second determining module 220 is configured to determine a fuzzy relationship from the index factor set to the evaluation level set of the target object, so as to obtain a fuzzy relationship matrix;
the calculating module 230 is configured to calculate weights of the index factors in the index factor set by using an analytic hierarchy process to obtain a weight vector;
a synthesizing module 240, configured to select a fuzzy operator, and synthesize the weight vector and the fuzzy relation matrix to obtain an evaluation value of the target object;
and the evaluation module 250 is configured to perform single-valued processing on the evaluation value of the target object, and evaluate the public spatial quality of the target object according to the obtained evaluation single value of the target object.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
In the technical scheme of the invention, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations without violating the good customs of the public order.
The invention also provides an electronic device and a readable storage medium according to the embodiment of the invention.
FIG. 3 shows a schematic block diagram of an electronic device 300 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
The device 300 comprises a computing unit 301 which may perform various suitable actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Various components in device 300 are connected to I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, or the like; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
Computing unit 301 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 301 executes the respective methods and processes described above, such as the methods S101 to S105. For example, in some embodiments, methods S101-S105 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 300 via ROM 302 and/or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of methods S101-S105 described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the methods S101-S105 by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method for evaluating quality of a public space, comprising:
acquiring index factor data for determining the quality of a public space, and determining an index factor set and an evaluation grade set of a target object according to the index factor data; the index factor set of the target object comprises qualitative index factors and quantitative index factors;
determining a fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors; carrying out statistical normalization on quantitative index factor data in the index factor data determining the public space quality to obtain a fuzzy relation matrix of the quantitative index factors; synthesizing the fuzzy relation matrix of the qualitative index factors and the fuzzy relation matrix of the quantitative index factors into a comprehensive fuzzy relation matrix;
calculating the weight of the index factors in the index factor set by using a grey level evaluation method to obtain a weight vector;
selecting a fuzzy operator, and synthesizing the weight vector and the fuzzy relation matrix to obtain an evaluation value of the target object;
and carrying out single-valued processing on the evaluation value of the target object, and evaluating the public space quality of the target object through the obtained evaluation single value of the target object.
2. The method of claim 1, wherein the set of indicator factors is:
U＝{U1，U2，...，Ui，...，Un}
Ui＝{ui1，ui2，，...，uij，...，uim}
wherein U is an index factor set of the public space quality of the target object; u shapeiAn ith primary index factor of the common spatial quality of the target object; u. ofijA jth secondary index factor of the ith primary index factors of the common spatial quality of the target object; m is the number of secondary index factors in the ith primary index factor of the public space quality of the target object; n is the number of primary index factors of the public space quality of the target object;
the evaluation grade set is as follows:
V＝{v1，v2，...，vi，...，vx}
wherein V is a common space of the target objectA set of evaluation levels of the quality of (1); v. ofiAn ith evaluation level of the common spatial quality of the target object; x is the number of evaluation grades.
3. The method of claim 1, wherein the fuzzy relation matrix of qualitative indicator factors is:
Figure FDA0003511319290000021
wherein R' is a fuzzy relation matrix of qualitative index factors; r'ijThe membership of the ith qualitative index factor in the index factor set corresponding to the jth evaluation level in the evaluation level set; p is the number of qualitative index factors; x is the number of evaluation grades;
the fuzzy relation matrix of the quantitative index factors is as follows:
Figure FDA0003511319290000022
wherein, R' is a fuzzy relation matrix of quantitative index factors; rijThe membership relation of the ith quantitative index factor in the index factor set corresponding to the jth evaluation interval in the evaluation interval set is obtained; q is the number of quantitative index factors, p + q is equal to n, and n is the number of first-level index factors of the public space quality of the target object; x 'is the number of the evaluation intervals, and the number x of the evaluation grades is equal to the number x' of the evaluation intervals;
the comprehensive fuzzy relation matrix is as follows:
Figure FDA0003511319290000023
wherein, R is a fuzzy relation matrix of the comprehensive index factors; r isijThe evaluation grade set is corresponding to the ith index factor in the index factor setMembership of the jth rating in the portfolio.
4. The method according to claim 1, wherein the calculating the weight of the index factors in the index factor set by using a gray level evaluation method to obtain a weight vector comprises:
firstly, presetting the grade number of index factors of the public space quality, the gray number of the index factors and a whitening function of the gray number;
secondly, respectively calculating a gray evaluation coefficient of each index factor according to the number of grades of the index factors and a whitening function of the gray number, and respectively calculating a total gray evaluation coefficient of each index factor for each gray number;
then, calculating the grey evaluation weight of each index factor belonging to the grey number, and obtaining the weight vector by calculating the weights of different index factors;
the weight vector is:
Figure FDA0003511319290000031
ai＝{ai1，ai2，...，aij，...，aiy}T
wherein A is a weight vector; a isiThe weight of the ith primary index factor in the index factor set is obtained; a isijThe weight of the jth secondary index factor in the ith primary index factor in the index factor set is obtained; n is the number of primary index factors of the public space quality of the target object; y represents aiThe number of the included secondary index factors; t denotes transposition.
5. The method according to claim 1, wherein the evaluation value of the target object is:
Figure FDA0003511319290000032
wherein B is an evaluation value of the common spatial quality of the target object; biAn evaluation value of an i-th index factor that is a common spatial quality of the target object; the number of primary index factors of the public space quality of the target object is obtained; a is a weight vector; r is a comprehensive fuzzy relation matrix;
Figure FDA0003511319290000033
representing the selected blurring operator.
6. The method according to claim 1, wherein the subjecting the evaluation value of the target object to the univocal processing includes:
B′＝BCT
wherein B' is an evaluation unit of the common spatial quality of the target object; b is an evaluation value of the common spatial quality of the target object; cTIs a levelized vector.
7. The method of claim 1, wherein the evaluating the common spatial quality of the target object by the obtained evaluation unit value of the target object comprises:
if the evaluation unit value of the target object is larger, the public space quality of the target object is higher;
and if the evaluation unit value of the target object is smaller, the public space quality of the target object is poorer.
8. The method of claim 1, further comprising:
carrying out sensitivity analysis on the evaluation single value of the target object to obtain the contribution degree of the factor index;
and sorting the contribution degrees of the factor indexes from large to small, wherein the larger the contribution degree is, the larger the effect of the factor indexes in the evaluation of the quality of the public space is.
9. An apparatus for evaluating quality of a public space, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring index factor data for determining the quality of public space and determining an index factor set and an evaluation grade set of a target object according to the index factor data; the index factor set of the target object comprises qualitative index factors and quantitative index factors;
the first synthesis module is used for determining the fuzzy relation from the qualitative index factors to the evaluation grade set to obtain a fuzzy relation matrix of the qualitative index factors; carrying out statistical normalization on quantitative index factor data in the index factor data determining the public space quality to obtain a fuzzy relation matrix of the quantitative index factors, and synthesizing a comprehensive fuzzy relation matrix according to the fuzzy relation matrix of the qualitative index factors and the fuzzy relation matrix of the quantitative index factors;
the calculation module is used for calculating the weight of the index factors in the index factor set by using a grey level evaluation method to obtain a weight vector;
the second synthesis module is used for selecting a fuzzy operator, and synthesizing the weight vector and the fuzzy relation matrix to obtain an evaluation value of the target object;
and the evaluation module is used for carrying out univocal processing on the evaluation value of the target object and evaluating the public space quality of the target object through the obtained evaluation univocal value of the target object.
10. An electronic device comprising at least one processor; and
a memory communicatively coupled to the at least one processor; it is characterized in that the preparation method is characterized in that,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
CN202210152944.5A 2022-02-18 2022-02-18 Method and device for evaluating quality of public space Pending CN114529194A (en)

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