CN113935656A - Method for evaluating reclamation of bulk solid wastes in non-waste urban area - Google Patents
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Abstract
The invention belongs to the technical field of resource utilization of bulk solid wastes. The method is characterized in that in a non-waste urban area, according to the design requirements of non-waste urban planning, when a large solid waste resource utilization technical model of an evaluation area is established, a multi-standard decision evaluation model which considers the characteristic characteristics of different indexes and eliminates subjective interference as much as possible is established. Compared with the similar technologies at home and abroad at present, the method can provide a basis for planning and constructing the bulk solid waste resource in the non-waste urban area by evaluating different utilization technical model schemes of the bulk solid waste resource in the non-waste urban area; the evaluation of the bulk solid waste recycling degree of each region of the non-waste city provides a basis for evaluating the bulk solid waste recycling degree of different town regions of the non-waste city.
Description
Technical Field
The invention belongs to the technical field of recycling of bulk solid wastes, and particularly relates to a recycling evaluation method of bulk solid wastes in a waste-free urban area.
Background
The 'non-waste city' is an advanced city management concept, and is a city development mode which is led by a new development concept of innovation, coordination, green, openness and sharing, continuously promotes the reduction of the source of bulk solid wastes and the resource utilization by promoting the formation of a green development mode and a life mode, reduces the landfill amount to the maximum extent, and reduces the environmental impact of the bulk solid wastes to the minimum. At present, in most areas of most provinces and cities, in the aspects of city planning, industrial layout and infrastructure construction, the problems of reduction, recovery, utilization and disposal of bulk solid wastes are not emphasized sufficiently and considered insufficiently, and the sustainable development of the city economy and the society is seriously influenced. Therefore, research on various technologies for recycling treatment of massive solid wastes in non-waste urban areas has important functions and significance, and particularly, an industrial base and a park are constructed by constructing centralized massive solid waste resources to recycle industrial resources, so that an industrial park symbiotic system is imperative. The method has the advantages that the method generates emerging economic growth points while realizing the cooperative emission reduction of bulk solid wastes such as organic wastes, inorganic wastes and composite wastes, and forms an economic society green high-quality development technical mode, such as an industrial source bulk solid waste closed-loop type full-coverage resource technical mode, a smart platform for intelligently managing wastes to construct a refined overall resource technical management mode, and the like. With the development of green and high quality of economic society, different kinds of technical modes based on different concepts and different emphasis points are more and more, and although the different kinds of technical modes have the advantages and characteristics, the method plays a certain role in providing a stereoscopic and precise resource technical mode for the whole process of generation source-collection-transportation-treatment of a large amount of solid wastes. However, in the case of various recycling technical modes for recycling a large amount of solid wastes, it is often difficult to determine which recycling technical mode is the best choice in planning and constructing a "non-waste city". Actually, in order to make a reasonable selection, many factors such as social economic sustainable development, operational economic indicators, ecological environmental indicators, technical maturity and the like should be considered at the same time, and it is a systematic research and evaluation work. However, the current research is often not only single but also has great subjectivity. The reason is mainly because in most cases, multiple factors or indexes in various resource technology modes have both objective indexes and subjective indexes, and have both quantitative indexes and qualitative indexes, which brings certain difficulties and challenges to the traditional evaluation technology method. Therefore, when a technical model for utilization of bulk solid wastes in an evaluation area is established, it is necessary to establish a multi-standard decision evaluation model which considers the characteristics of different indexes and eliminates subjectivity as much as possible.
Disclosure of Invention
The invention aims to provide a method for evaluating the utilization of bulk solid wastes in a non-waste urban area aiming at the defects existing in the establishment and evaluation of a technical model for utilizing the bulk solid wastes in the non-waste urban area in China.
The invention specifically comprises the following steps:
target value Eoi is provided for each index of each area, i is l,2,3
Wherein Rij (i ═ 1,2,3, - - - -, j ═ 1,2,3, - - - - -) is each index of each region; in order to comprehensively evaluate the quality degree of each region, fuzzy clustering evaluation is carried out on the target difference rate matrix; the fuzzy clustering evaluation is to classify areas which are relatively close (namely, have small Euclidean distance) in a difference rate matrix into one class according to a certain optimization criterion, and classify areas with larger differences into different classes, and express the areas with a plurality of grades such as quality; because the quality is a fuzzy concept and does not have an absolute clear boundary; therefore, a certain region can be considered as belonging degree muijFrom the best modeV1，V1(V11V 12V 13. cndot. V1n) with a degree of membership μijSubordinate to inferior mode samplesV2，V2(V21, V22, V23 · V2 n). Then there is a fuzzy clustering matrix U:
each type of mode sample is the core of all the regions of the type and comprehensively reflects the characteristic indexes of the regions of the type; therefore, the membership degree of each area to the good and bad mode samples is used as a basis for evaluating each area, and the method is a core problem for determining the good and bad areas; the fuzzy clustering matrix should satisfy the following constraints:
the constraint condition (2) indicates that the sum of the liveness of the patterns belonging to the good and bad patterns is 1, and the constraint condition (3) indicates that each type of fuzzy set is not an empty set;
now to determine the best classification from an infinite number of clustering matrices, according to the least square criterion, it can be considered that the weighted distance square sum of the target difference rates of the respective schemes and the target difference rates of the superior and inferior mode samples is the minimum as the objective function, and there are
The above formula is also understood to be expressed as muijThe sum of the squared distances, which is the weight, reaches a minimum;
according to the target function formula and constraint condition equation, constructing Lagrange function, and transforming equation constraint extremum into unconditional extremum problem
The formula is Lagrange multiplier, respectively corresponding to variable lambdae，μst(s 1, 2.. times, c, t 1, 2.. times, m) calculating the partial derivative of formula (1), and making the partial derivative equal to zero, then
Obtained by the formula (3):
from (2) and (4)
Then
(6) Substituting into formula (4) to obtain
Thus can obtain
Iterative formula for solving objective function formula (1) in time
The difference rate of each target corresponding to a certain type of mode sample is the weighted average of the difference rates of each scheme, and the same is used for muij 2As a weight, then
Can be calculated by equation (9);
the fuzzy soft partition evaluation step can be summarized as follows:
1) determining the target value of each index in each scheme and making a target difference rate matrix
2) Giving an initial clustering matrix mu satisfying a constraint condition0
3) According to μ0And a target difference rate matrix for each scheme, calculating pattern samples according to equation (9)
4) Calculating a new fuzzy clustering evaluation matrix mu from equation (6)
5) Comparison of mu0And μ, if max { | μ ij- μ 0ij | } < ε, the computation is stopped (ε is a small positive number that satisfies the computation accuracy), and the resulting μ and
the optimal soft partition matrix and the mode sample wood are obtained, otherwise, the steps (2), (3) and (4) are repeated until the precision requirement is met
6) And (3) solving the mu matrix according to the formula (8), finding out a scheme with the maximum membership degree belonging to the excellent mode sample, namely the optimal scheme, and sequencing according to the membership degree to further evaluate the advantages and disadvantages of the different utilization technical model schemes of the bulk solid wastes in the non-waste city region, so as to provide a basis for planning and construction of the bulk solid wastes in the region, or determining the recycling degree of the bulk solid wastes in each region of the non-waste city, so as to provide a basis for evaluating the recycling degree of the bulk solid wastes in different town regions. Each technical model scheme or each index in each area can be an objective index and can be a subjective index; the target value Eoi is provided for each index of each region, and is generally determined after being fully demonstrated by experts according to relevant national or provincial legislative policies and actual conditions.
The invention has certain practicability, and is particularly embodied in that the invention can be manufactured or used and can produce the following positive and beneficial effects:
(1) the method can efficiently treat and recycle a large amount of solid wastes in the planning and construction process of a waste-free urban area, can purify and improve the regional environment to the maximum extent, realizes the resource recycling of the large amount of regional solid wastes, and has very remarkable social and economic benefits.
(2) According to the method, the technical model schemes for utilizing the bulk solid wastes in the non-waste urban area are evaluated, so that a basis can be provided for planning and constructing the bulk solid wastes in the non-waste urban area; the evaluation of the resource degree of the bulk solid wastes in each region of the non-waste city provides a basis for evaluating the resource degree of the bulk solid wastes in different town regions. Provides technical support for the rapid development of the resource treatment and utilization industry of bulk solid wastes in non-waste urban areas of China.
Detailed Description
When a certain city is planned without waste, four technical model schemes for utilizing bulk solid waste resources in a primarily selected area are evaluated, and indexes of the four comparison schemes are shown in a table 1.
TABLE 1 indices of the four comparative protocols
| Unit of | (scheme one) | (scheme two) | (scheme III) | (scheme four) | |
| Dynamic investment benefit rate | 23 | 20.5 | 18 | 15 | |
| Degree of public acceptance | 0.5 | 0.58 | 0.72 | 0.9 | |
| Internal cost to benefit ratio | 0.61 | 0.74 | 0.84 | 0,89 | |
| Cost of transportation | Wan Yuan | 1196.6 | 1094.2 | 999.65 | 928.1 |
| Coverage of resources | Thousand mu area | 350 | 520 | 690 | 1020 |
| Total investment of project | Wan Yuan | 2050 | 2680 | 3354 | 4100 |
| Construction period | Every ten days | 2.5 | 3 | 4 | 4.5 |
| Amount of land used | Mu m | 0 | 0 | 35 | 420 |
| Efficiency of energy recovery | Hundred million yuan | 0 | 0 | 20 | 30 |
The evaluation analysis was performed as described above.
1. According to the relevant national or provincial and municipal regulation policy, the comprehensive practical situation of the city is combined, the target values of various indexes of each scheme are determined after 5-8 experts fully demonstrate, and a target difference rate matrix of each scheme is made.
Determining target values E of various indexes0Is composed of
E0＝[23 0.9 0.89 928 350 2050 2.5 35 30]T
To construct a target differential rate matrix X for each scheme, the indices and target values for each scheme in Table 1 are substituted
The formula is adopted, the target difference rate of each index of each scheme is calculated, and the target difference rate matrix X is
After the normalization processing is carried out on the X matrix
Giving an initial membership matrix mu satisfying the constraint condition0
The calculation example is divided into a good grade and a bad grade, wherein each scheme in the matrix is subordinate to the membership degree of a good mode sample, and each scheme in the matrix is subordinate to the membership degree of a bad mode sample.
2. According to μ0And calculating a pattern sample according to equation (9) for the target difference rate matrix of each scheme
Excellent mode sample
The following explanation is given for the example.
Will matrix mu0In the first row and columns mu1jThe (j ═ 1,2,3,4) values and the elements of the difference rate matrix are determined from equation (9)
Analogously, V can be determined12，V13,...，V10Is thus
3. A new fuzzy soft partition evaluation matrix mu is calculated according to equation (8), now as mu in the first row element of the matrix mu12The calculation is described by way of example, and formula (8) includes
In the above formula
According to the obtained
From the distance formula
||x2-V1||＝0.38414
||x2-V2||＝1.702
Then
Similarly, it can be obtained that all elements in the matrix μ are
From mu and mu0As can be seen, max { μij-μ0j0.296(i is 1, j is 4), 0.01 is adopted, so steps (4) and (5) are repeated.
The example is calculated on a computer to obtain the optimal matrix meeting the precision requirement as
Take the maximum element max μ of the first rowij→μ120.992, j is 2, that is, the scheme with the largest membership degree of the samples belonging to the excellent mode is the second scheme; taking the maximum element max mu of the second column at the same timei2→μ12And i is 1, that is, the second scheme belongs to the excellent mode sample with the maximum membership degree, and the second scheme is the optimal scheme.
The embodiment provides a basis for planning and construction of the bulk solid waste resource of the non-waste urban area by evaluating different utilization technical model schemes of the bulk solid waste resource of the non-waste urban area.
The method can also evaluate the recycling degree of the bulk solid wastes in each area of the non-waste city, and provides a basis for evaluating the recycling degree of the bulk solid wastes in different town areas of the non-waste city. The following principle should be adhered to at this time:
the evaluation of the resource degree of the bulk solid wastes in each area of the non-waste city is mainly to select indexes which have great influence on the resource of the bulk solid wastes through classification analysis and evaluate the condition of an evaluation object from a certain aspect or aspects to neutralization according to a certain rule and method, thereby determining the development level and the existing problems of the resource of the bulk solid wastes in the non-waste city.
In order to objectively and accurately reflect the development level of recycling of bulk solid wastes in a waste-free urban area through an evaluation result, the selection of an evaluation index follows the following principle.
(1) The principle of completeness. The selected indexes have integrity and completeness, generally, a single index can only evaluate one aspect of a target, and all the selected indexes can reflect technical indexes of a regional bulk waste resource utilization method, functions, adaptability and the like and complete information of bulk waste resource utilization management, so that main characteristics and development tendency of an evaluated system are comprehensively reflected.
(2) Systematic principle. The evaluation of regional bulk waste resource is a complex system involving multiple factors and multiple targets, an evaluation index system aims to comprehensively reflect the comprehensive condition of urban regions, not only reflects the internal structure and function of the system, but also can accurately evaluate the association between the system and the external environment; not only can reflect the direct effect, but also can reflect the indirect influence so as to ensure the reliability and systematicness of the evaluation.
(3) Scientific principle. The selection of the specific indexes is established on the scientific basis of fully understanding and deeply researching the resource utilization of the bulk waste in the non-waste urban area, and can reflect the resource utilization engineering of the bulk waste in the non-waste urban area, and pursue the idea of unifying the environmental benefit, the economic benefit and the social benefit by taking sustainable development as a target. In the evaluation and analysis process, the method has both quantitative analysis indexes and qualitative analysis indexes; has both macroscopic index and microscopic index. The combination of quantification and qualitative and microscopic and macroscopic is realized.
(4) The principle of independence. Indexes describing the resource utilization development condition of bulk solid wastes in a non-waste urban area often overlap, so that the indexes with relative independence are selected as far as possible in the process of selecting the indexes, and the accuracy and the scientificity of evaluation are improved.
(5) The principle of comparability. When determining the evaluation index and standard, the changes of time and space and the influence thereof are considered, and the relative index and the absolute index are reasonably selected, so that the method is not only suitable for longitudinal comparison of different regions of one non-waste city in different periods, but also suitable for transverse comparison among different non-waste cities.
(6) And (5) operability principle. The evaluation index system considers the quantization of indexes and the difficulty and credibility of data acquisition, achieves the purposes of index refinement, simple method and high use value and popularization value. Therefore, the selected index has operability, the index meaning is clear and easy to understand, and the index data is easy to survey, arrange or theoretically calculate and actually measure.
In the foregoing specification, although a preferred embodiment of the invention has been described, it is understood that it is not intended to limit the scope of the invention to the particular embodiment, since various changes in the details of construction and details of operation, which will become apparent to those skilled in the art from this detailed description, may be made without departing from the spirit and scope of the invention.
Claims (2)
1. A method for evaluating the utilization of bulk solid wastes in a waste-free urban area is characterized by comprising the following steps:
target value Eoi is provided for each index of each area, i is l,2,3
Wherein Rij (i ═ 1,2,3, - - - -, j ═ 1,2,3, - - - - -) is each index of each region; in order to comprehensively evaluate the quality degree of each region, fuzzy clustering evaluation is carried out on the target difference rate matrix; the fuzzy clustering evaluation is to classify areas which are relatively close (namely, have small Euclidean distance) in a difference rate matrix into one class according to a certain optimization criterion, and classify areas with larger differences into different classes, and express the areas with a plurality of grades such as quality; because the quality is a fuzzy concept and does not have an absolute clear boundary; therefore, a certain region can be considered as belonging degree muijFrom the best modeV1，V1(V11V 12V 13. cndot. V1n) with a degree of membership μijSubordinate to inferior mode samplesV2，V2(V21, V22, V23 · V2 n). Then there is a fuzzy clustering matrix U:
each type of mode sample is the core of all the regions of the type and comprehensively reflects the characteristic indexes of the regions of the type; therefore, the membership degree of each area to the good and bad mode samples is used as a basis for evaluating each area, and the method is a core problem for determining the good and bad areas; the fuzzy clustering matrix should satisfy the following constraints:
(1)0≤μij≤1 (2)
(3)
the constraint condition (2) indicates that the sum of the liveness of the patterns belonging to the good and bad patterns is 1, and the constraint condition (3) indicates that each type of fuzzy set is not an empty set;
now to determine the best classification from an infinite number of clustering matrices, according to the least square criterion, it can be considered that the weighted distance square sum of the target difference rates of the respective schemes and the target difference rates of the superior and inferior mode samples is the minimum as the objective function, and there are
The above formula is also understood to be expressed as muijThe sum of the squared distances, which is the weight, reaches a minimum;
according to the target function formula and constraint condition equation, constructing Lagrange function, and transforming equation constraint extremum into unconditional extremum problem
The formula is Lagrange multiplier, respectively corresponding to variable lambdae，μst(s 1, 2.. times, c, t 1, 2.. times, m) calculating the partial derivative of formula (1), and making the partial derivative equal to zero, then
Obtained by the formula (3):
is represented by the formulae (2) and (4)
Then
(6) Substituting into formula (4) to obtain
Thus can obtain
Iterative formula for solving objective function formula (1) in time
The difference rate of each target corresponding to a certain type of mode sample is the weighted average of the difference rates of each scheme, and the same is used for muij 2As a weight, then
Can be calculated by equation (9);
the fuzzy soft partition evaluation step can be summarized as follows:
1) determining the target value of each index in each scheme and making a target difference rate matrix
2) Giving an initial clustering matrix mu satisfying a constraint condition0
3) According to μ0And a target difference rate matrix for each scheme, calculating pattern samples according to equation (9)
4) Calculating a new fuzzy clustering evaluation matrix mu from equation (6)
5) Comparison of mu0And μ, if max { | μ ij- μ 0ij | } < ε, the computation is stopped (ε is a small positive number that satisfies the computation accuracy), and the resulting μ and
the optimal soft partition matrix and the mode sample wood are obtained, otherwise, the steps (2), (3) and (4) are repeated until the precision requirement is met
6) And (3) solving the mu matrix according to the formula (8), finding out a scheme with the maximum membership degree belonging to the excellent mode sample, namely the optimal scheme, and sequencing according to the membership degree to evaluate the advantages and disadvantages of the different utilization technical model schemes of the regional bulk solid waste resources, so as to provide a basis for planning and construction of the regional bulk solid waste resources, or determining the resource degree of the regional bulk solid waste, so as to provide a basis for evaluating the resource degree of the bulk solid waste in different town regions.
2. The method according to claim 1, wherein each technical model solution or each index in each area can be objective index or subjective index; the target value Eoi is provided for each index of each region, and is generally determined after being fully demonstrated by experts according to relevant national or provincial legislative policies and actual conditions.
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| CN117077005B (en) * | 2023-08-21 | 2024-05-10 | 广东国地规划科技股份有限公司 | Optimization method and system for urban micro-update potential |
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