Phase diagram evaluation method and system for multi-dimensional performance of renewable resource recycling technology

Abstract

This application relates to the technical field of multidimensional evaluation of renewable resource recycling technologies, and discloses a phase diagram-based evaluation method and system for the multidimensional performance of renewable resource recycling technologies. The method includes: setting recycling processing paths for each type of renewable resource; setting multiple evaluation factors for each recycling processing path and constructing an evaluation phase diagram of the renewable resource; assigning weights to the evaluation factors for each dimension based on the evaluation phase diagram; calculating a comprehensive evaluation index for each recycling processing path based on the evaluation factors and their weights for each dimension; and using the comprehensive evaluation index to assist in comparing and optimizing different recycling processing paths. This application achieves a multidimensional performance comprehensive evaluation of renewable resource recycling technologies, improving the accuracy of multi-objective optimization decisions for renewable resource processing.

Description

Technical Field

[0001] This application relates to the technical field of multidimensional evaluation of renewable resource recycling technologies, specifically to a phase diagram-based evaluation method and system for the multidimensional performance of renewable resource recycling technologies. Background Technology

[0002] The recycling and reuse methods for urban recyclable resources (such as construction waste, electronic waste, and organic waste) are becoming increasingly diversified. However, the resource reduction, environmental emission reduction, and economic value-added effects of different recycling technologies vary significantly. The lack of a systematic assessment of multidimensional benefits in the comprehensive evaluation and selection of recycling technologies makes it difficult to effectively quantify the goals of pollution reduction, carbon reduction, and efficiency improvement. Existing treatment systems typically evaluate and configure recycling technologies based on experience or policy-driven approaches, lacking data support and failing to achieve optimal decision-making for path switching.

[0003] When evaluating recycling technologies for renewable resources, existing technologies fail to comprehensively consider multiple dimensions such as environmental impact, policy guidance, and public acceptance. This one-sided evaluation approach can easily lead to biases in the selection of recycling technologies, failing to maximize economic and environmental benefits.

[0004] From the perspective of adjustment mechanisms for recycling technologies, existing technologies generally lack scientific and dynamic adjustment strategies. Many companies, after selecting a recycling technology, tend to use it for extended periods. Existing adjustment mechanisms often rely on human experience and lack data- and algorithm-based analysis, resulting in a lack of timeliness and accuracy in adjusting recycling technologies, making it difficult to meet the rapidly developing and changing needs of the recycling industry.

[0005] For example, Chinese patent CN114723311B discloses a data mining-driven method for evaluating the spatiotemporal management effectiveness of urban solid waste, including the following steps: S1: Obtaining solid waste management data; S2: Cleaning and preprocessing the solid waste management data, screening effectiveness tags, and calculating evaluation index values; S3: Constructing a TOPSIS scoring model to determine the comprehensive score of the evaluation index in various spatiotemporal states; S4: Drawing a dynamic heat map for visualization, completing the evaluation of the spatiotemporal management effectiveness of urban solid waste. This technical solution utilizes web crawling technology to mine and supplement the tag information lacking in management big data from online big data, thereby enriching the data source and refining the data granularity, providing data support for the spatiotemporal coupling and multi-benefit calculation of urban solid waste regional management effectiveness evaluation.

[0006] Patent application CN119831089A discloses an intelligent optimization method for reducing pollution and increasing efficiency in urban solid waste incineration processes. Through the coordinated operation optimization of multiple process stages, it improves the main steam flow rate and its stability, reduces pollutant emission concentrations, and simultaneously reduces the consumption of urea solution and limestone slurry. The method includes the following steps: First, data is acquired; inputs and outputs are determined, and a fuzzy neural network is used to establish an operational index model; second, based on the response times of the solid waste incineration, waste heat utilization, and flue gas treatment stages, a multi-timescale operational optimization objective function is established; a two-layer multi-objective competitive group optimization algorithm is designed to solve the dynamic coordinated operation optimization problem of the urban solid waste incineration process; finally, based on the optimization characteristics of different time scales, the optimal decision is determined, and the optimization performance is verified using actual urban solid waste incineration process data. This technical solution achieves pollution reduction and efficiency improvement in urban solid waste incineration processes, and has significant theoretical and practical value.

[0007] The above technical solutions suffer from the problems mentioned in this background: the lack of a systematic assessment of environmental benefits during the evaluation and selection of circular technologies makes it difficult to achieve optimal decision-making for switching to circular technologies.

[0008] The information disclosed in this background section is intended only to enhance the understanding of the overall background of this application and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0009] The technical problem to be solved by this application is to overcome the defects of the prior art, provide a phase diagram-based evaluation method and system for the multi-dimensional performance of renewable resource recycling technology, realize the multi-dimensional benefit evaluation of renewable resource recycling technology, and improve the accuracy of multi-objective optimization decision-making for renewable resource treatment.

[0010] To solve the above-mentioned technical problems, this application provides the following technical solution:

[0011] On the one hand, this application provides a phase diagram-based evaluation method for the multidimensional performance of renewable resource recycling technologies, including the following steps:

[0012] A recycling process path is set for each type of renewable resource; an evaluation factor is set for each recycling process path, and an evaluation phase diagram of the renewable resource is constructed; the evaluation phase diagram includes each recycling process path of any renewable resource and its corresponding evaluation factor.

[0013] The path discrimination degree of each evaluation factor is calculated based on the evaluation phase diagram; an influence factor is assigned to each evaluation factor based on the path discrimination degree.

[0014] The configuration priority of each loop processing path is calculated based on the evaluation factors and impact factors.

[0015] A score reliability tensor for each loop processing path is constructed based on the evaluation phase diagram; the configuration priority of each loop processing path is adjusted and compensated based on the score reliability tensor.

[0016] The cyclic processing path for each type of regenerated resource is configured and adjusted based on the configured priority.

[0017] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, the evaluation factors are used to evaluate the merits of each recycling path from different dimensions; for any renewable resource, the path discrimination is calculated as follows:

[0018] Each evaluation factor for each recycling path of the regenerated resources is extracted based on the evaluation phase diagram.

[0019] Construct a path difference matrix for recycled resources; let there be m cyclic processing paths for recycled resources, and each cyclic processing path has n evaluation factors, then the path difference matrix is ​​an n-row m-column matrix; m and n are positive integers; the element in the i-th row and j-th column of the path difference matrix represents the i-th evaluation factor of the j-th cyclic processing path of recycled resources; the value range of i is 1, 2, ..., n; the value range of j is 1, 2, ..., m;

[0020] The path discrimination of each evaluation factor is calculated based on the path difference matrix; the path discrimination of the i-th evaluation factor is calculated as follows:

[0021] Extract all elements in the i-th row of the path difference matrix, and calculate the range and mean of all elements in the i-th row; the path discrimination of the i-th evaluation factor is the ratio of the range to the mean of all elements in the i-th row.

[0022] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, wherein: for any renewable resource, the method for assigning influencing factors to each evaluation factor is as follows:

[0023] Calculate the sum of the path discrimination of each evaluation factor; the influence factor of the i-th evaluation factor is the ratio of the path discrimination of the i-th evaluation factor to the sum of the path discrimination of each evaluation factor.

[0024] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, wherein: for any renewable resource, the configuration priority represents the improvement in the comprehensive evaluation index brought about by switching recycling paths; the method for calculating the configuration priority of each recycling path is as follows:

[0025] Calculate the comprehensive evaluation index for each cyclic processing path based on the evaluation factors and impact factors.

[0026] The configuration priority of each cyclic processing path is calculated based on the comprehensive evaluation index, specifically including: determining the current cyclic processing path of the recycled resources; subtracting the comprehensive evaluation index of the current cyclic processing path from the comprehensive evaluation index of each cyclic processing path to obtain the configuration priority of each cyclic processing path.

[0027] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, the calculation of the comprehensive evaluation index for each recycling path specifically includes: dividing the evaluation factors of each recycling path into benefit-type evaluation factors and cost-type evaluation factors; weighting and summing all evaluation factors for each recycling path to obtain the comprehensive evaluation index for each recycling path; wherein, the weight of the benefit-type evaluation factor in the weighted summation is the corresponding influence factor; and the weight of the cost-type evaluation factor in the weighted summation is the corresponding influence factor multiplied by -1.

[0028] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, the method for constructing the scoring reliability tensor is as follows:

[0029] Set the processing configuration cycle for regenerated resources; update the evaluation phase diagram of regenerated resources at the beginning of each processing configuration cycle; based on the evaluation phase diagram of each processing configuration cycle, extract the value of each evaluation factor for each cyclic processing path in each processing configuration cycle, and form a value set for each evaluation factor.

[0030] Based on the value set of the evaluation factors, calculate the stable distribution value of each evaluation factor for each cyclic processing path;

[0031] The stable distribution values ​​of each evaluation factor are arranged in a specified order to form the scoring reliability tensor of the corresponding cyclic processing path.

[0032] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, the calculation of the stable distribution value of each evaluation factor specifically includes:

[0033] Calculate the mean of all values ​​in the value set for each evaluation factor, and use it as a reference value for each evaluation factor;

[0034] Calculate the difference between each value of each evaluation factor and the corresponding reference mean, and take the absolute value as the offset of the corresponding value;

[0035] Set an offset threshold for each evaluation factor; mark values ​​whose offsets are greater than the offset threshold as fluctuating values;

[0036] Calculate the proportion of the volatility of each evaluation factor relative to all values ​​in the value set, and use this as the volatility of the corresponding evaluation factor;

[0037] The stable distribution value of each evaluation factor is calculated based on the volatility; the stable distribution value of each evaluation factor is 1 minus the corresponding volatility.

[0038] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology described in this application, the compensation adjustment of the configuration priority of each recycling path specifically includes:

[0039] The validity of each loop processing path is calculated based on the rating reliability tensor. The method is as follows: the rating reliability tensor of the current loop processing path is marked as the reference reliability tensor; the rating reliability tensor of the loop processing path whose validity is to be calculated is marked as the target reliability tensor.

[0040] Calculate the difference between the stable distribution values ​​of each evaluation factor in the reference reliability tensor and the target reliability tensor, and take the absolute value as the stability variance of the corresponding evaluation factor; calculate the sum of the stability variances of each evaluation factor.

[0041] Set an adjustment factor, denoted as k; the effectiveness of any loop processing path is 1 minus the sum of k times the stability differences;

[0042] The configuration priority is adjusted based on the validity of each loop processing path. The method is as follows: multiply the configuration priority of each loop processing path by the corresponding validity to obtain the updated value of the configuration priority of each loop processing path.

[0043] As a preferred embodiment of the phase diagram-based evaluation method for the multidimensional performance of the recycling technology of renewable resources described in this application, the following steps are taken: The recycling processing path for each renewable resource is configured and adjusted based on the configuration priority, specifically including: sorting the configuration priority of each recycling processing path for each renewable resource by size; setting a configuration priority threshold for each renewable resource; and for any renewable resource, if the maximum configuration priority is greater than the corresponding configuration priority threshold, it is recommended to switch the current recycling processing path to the recycling processing path corresponding to the maximum configuration priority.

[0044] Secondly, this application provides a phase diagram-based evaluation system for the multi-dimensional performance of renewable resource recycling technologies, including an evaluation phase diagram module, a first calculation module, a second calculation module, a compensation and adjustment module, and a processing configuration module; wherein:

[0045] The evaluation phase diagram module is used to construct an evaluation phase diagram that includes each recycling path of any renewable resource and its corresponding evaluation factors.

[0046] The first calculation module calculates the path discrimination of each evaluation factor based on the evaluation phase diagram, and assigns an influence factor to each evaluation factor based on the path discrimination.

[0047] The second calculation module calculates the configuration priority of each loop processing path based on the evaluation factors and impact factors.

[0048] The compensation and adjustment module is used to compensate and adjust the configuration priority of each loop processing path;

[0049] The processing configuration module adjusts the cyclic processing path for each type of regenerated resource based on the configuration priority.

[0050] Compared with the prior art, the beneficial effects achieved by this application are as follows:

[0051] This application constructs an evaluation phase diagram that includes evaluation factors such as recycling pathways, carbon emission reduction, resource recovery rate, and treatment cost, forming a multi-objective decision-making framework for pollution and carbon reduction oriented towards recycling technologies. This solves the problem in existing technologies where it is difficult to effectively compare the environmental effects of pollution and carbon reduction from different recycling pathways for renewable resources.

[0052] This application calculates the comprehensive evaluation index of each cyclic processing path and compares it with the current cyclic processing path to obtain the configuration priority, quantifying the comprehensive benefit improvement brought about by path switching. A scoring reliability tensor is constructed, and by calculating the stable distribution values ​​of evaluation factors and the stable difference between paths, the configuration priority is adjusted to compensate for and avoid decision-making biases caused by data instability, thereby improving the system's fit to real-world scenarios. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0054] Figure 1 A flowchart of the phase diagram-based evaluation method for the multidimensional performance of the renewable resource recycling technology provided in this application;

[0055] Figure 2 A schematic diagram of the phase diagram-based evaluation system for the multidimensional performance of the renewable resource recycling technology provided in this application;

[0056] Figure 3 This application provides an evaluation phase diagram in the form of a bar chart;

[0057] Figure 4 A heatmap of configuration priority is provided for this application. Detailed Implementation

[0058] The technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of this application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0059] Example 1

[0060] This embodiment introduces a phase diagram-based evaluation method for the multi-dimensional performance of renewable resource recycling technologies, referring to... Figure 1 The method includes the following steps:

[0061] A recycling process path is set for each type of renewable resource; an evaluation factor is set for each recycling process path, and an evaluation phase diagram of the renewable resource is constructed; the evaluation phase diagram includes each recycling process path of any renewable resource and its corresponding evaluation factor.

[0062] The recyclable resources refer to reusable waste, such as scrap metal and electronic waste. The circular treatment path refers to the process flow of recyclable resources, including processing, recycling, and end-of-pipe treatment (such as landfill and incineration). The environmental effects of different circular treatment paths for recyclable resources, such as pollution reduction and carbon reduction, lack a unified evaluation standard, making effective comparison difficult. This application constructs an evaluation phase diagram for recyclable resources to achieve multi-objective decision-making for pollution reduction and carbon reduction based on circular technologies, solving the problem of relying on manual experience to set circular treatment paths in existing technologies, and optimizing the treatment methods for recyclable resources.

[0063] The evaluation factors are used to evaluate the merits of each recycling pathway from different dimensions. In this embodiment, preferred evaluation factors include carbon emission reduction, resource recovery rate, treatment cost, energy output rate, pollution emission intensity, policy priority, and public acceptance. Furthermore, this embodiment also preferably sets the evaluation factors for each recycling pathway in the following manner:

[0064] Calculate the carbon emissions from the production of recycled resources; based on Life Cycle Assessment (LCA), calculate the carbon emissions of the entire recycling pathway, thereby calculating the carbon emission reduction; for example, the carbon emissions of the entire recycling pathway include the carbon emissions from the collection, sorting, transportation, and reprocessing stages of recycled resources. Calculate the proportion of reusable resources after treatment to the total amount of recycled resources, as the resource recovery rate of the recycling pathway. Calculate the cost of treating a unit volume of recycled resources, as the treatment cost of the recycling pathway. Calculate the ratio of usable energy produced by treating a unit volume of recycled resources to the energy consumption of the treatment process, as the energy output rate of the recycling pathway. Calculate the pollutant quality emitted per unit volume of recycled resources treated, as the pollution emission intensity of the recycling pathway. Assign a policy priority value to each recycling pathway based on the latest obtained support levels, subsidy standards, and mandatory requirements. Obtain public acceptance of the recycling pathway through questionnaires and other methods (such as the opposition rate of residents around the incineration plant), and assign a public acceptance value to each recycling pathway. Following the above method, each evaluation factor is calculated by combining historical data on renewable resource processing and industry experience. The data for each evaluation factor is then converted into standardized values ​​through standardization.

[0065] Those skilled in the art can set various forms of evaluation phase diagrams. This embodiment preferably uses a bar chart format for the evaluation phase diagram, such as… Figure 3 As shown. Figure 3 This diagram illustrates three recycling paths for a renewable resource, along with corresponding evaluation factors. The horizontal axis represents each evaluation factor for each recycling path, and the vertical axis represents the value of each evaluation factor. In this embodiment, standardization is used to ensure that the values ​​of evaluation factors with different dimensions are of the same order of magnitude, facilitating simultaneous display in the same evaluation phase diagram. Figure 3 As shown, the carbon emission reduction is expressed in kg CO2 / ton, which is the weight (kg) of carbon dioxide emission reduction corresponding to the treatment of one ton of renewable resources; the resource recovery rate is expressed in percentage; and the treatment cost is expressed in yuan / ton. Figure 3 The circular processing pathways shown include landfill, recycling, and co-processing; for example, recycling is carried out through sorting and recycling, and co-processing includes co-incineration and co-utilization of organic products.

[0066] The path discrimination degree of each evaluation factor is calculated based on the evaluation phase diagram; an influence factor is assigned to each evaluation factor based on the path discrimination degree.

[0067] For any type of renewable resource, the path distinguishability is calculated as follows:

[0068] Each evaluation factor for each recycling path of the regenerated resources is extracted based on the evaluation phase diagram.

[0069] Construct a path difference matrix for recycled resources; let there be m cyclic processing paths for recycled resources, and each cyclic processing path has n evaluation factors, then the path difference matrix is ​​an n-row m-column matrix; m and n are positive integers; the element in the i-th row and j-th column of the path difference matrix represents the i-th evaluation factor of the j-th cyclic processing path of recycled resources; the value range of i is 1, 2, ..., n; the value range of j is 1, 2, ..., m;

[0070] The path discrimination of each evaluation factor is calculated based on the path difference matrix; the path discrimination of the i-th evaluation factor is calculated as follows:

[0071] Extract all elements in the i-th row of the path difference matrix, and calculate the range and mean of all elements in the i-th row; the path discrimination of the i-th evaluation factor is the ratio of the range to the mean of all elements in the i-th row.

[0072] This embodiment preferably uses another method to calculate the path discrimination of the i-th evaluation factor, as follows: extract all elements in the i-th row of the path difference matrix; calculate the variance of all elements in the i-th row as the path discrimination of the i-th evaluation factor.

[0073] Path discrimination refers to the strength of the differentiating effect of each evaluation factor on different recycling processing paths during the selection of recycling processing paths; that is, the degree of difference between different paths at this evaluation factor. The greater the difference between different recycling processing paths at a certain evaluation factor, i.e., the higher the path discrimination, the greater the influence of this evaluation factor when calculating the allocation priority of recycling processing paths. In this embodiment, this is manifested as a larger influence factor of the evaluation factor. Given a type of renewable resource and its recycling processing path, this application calculates the path discrimination of each scoring factor among different recycling processing paths, and assigns a normalized influence factor to each non-evaluation factor based on the path discrimination, forming an influence factor assignment mechanism that best distinguishes recycling processing paths under the current circumstances. This achieves dynamic generation of influence factors, improving the discriminative power and real-world fit of subsequent allocation priorities. For example, if the public acceptance of different recycling processing paths is not significantly different, the influence factor of public acceptance is small; if the difference in carbon emission reduction is large (i.e., the path discrimination of carbon emission reduction is large), the influence factor of carbon emission reduction is also large.

[0074] For any type of renewable resource, the method for assigning influence factors to each evaluation factor is as follows:

[0075] Calculate the sum of the path discrimination of each evaluation factor; the influence factor of the i-th evaluation factor is the ratio of the path discrimination of the i-th evaluation factor to the sum of the path discrimination of each evaluation factor.

[0076] By normalizing the path discrimination of each evaluation factor using the above method and using it as its influencing factor, the dynamic quantification of the influence of each evaluation factor is achieved.

[0077] The configuration priority of each loop processing path is calculated based on the evaluation factors and impact factors; the method is as follows:

[0078] Based on the aforementioned evaluation factors and impact factors, a comprehensive evaluation index is calculated for each cyclic processing path, specifically including:

[0079] The evaluation factors for each cyclic processing path are divided into benefit-based evaluation factors and cost-based evaluation factors.

[0080] The evaluation factors for each cyclic processing path are weighted and summed to obtain the comprehensive evaluation index for each cyclic processing path. Among them, the weight of the benefit-type evaluation factor in the weighted sum is the corresponding influence factor; the weight of the cost-type evaluation factor in the weighted sum is the corresponding influence factor multiplied by -1. In this embodiment, the treatment cost and pollution emission intensity are used as cost-type evaluation factors, while carbon emission reduction, resource recovery rate, energy output rate, policy priority, and public acceptance are benefit-type evaluation factors.

[0081] For any type of recyclable resource, the configuration priority represents the improvement in the comprehensive evaluation index brought about by switching the cyclic processing path; the configuration priority of each cyclic processing path is calculated based on the comprehensive evaluation index, specifically including: determining the current cyclic processing path of the recyclable resource; subtracting the comprehensive evaluation index of the current cyclic processing path from the comprehensive evaluation index of each cyclic processing path to obtain the configuration priority of each cyclic processing path.

[0082] The current recycling path for recyclable resources is either the current recycling path used for that type of recyclable resource or the default recycling path. For example, it can be determined by analyzing the historical processing records of that type of recyclable resource to identify the recycling path with the highest proportion, or by using industry experience to determine the default recycling path as the current recycling path. Configuration priority is the marginal analysis result of the overall benefits of path switching, used to determine whether each recycling path is worth switching.

[0083] A score reliability tensor for each loop processing path is constructed based on the evaluation phase diagram; the configuration priority of each loop processing path is adjusted and compensated based on the score reliability tensor.

[0084] The method for constructing the rating reliability tensor is as follows:

[0085] Set the processing configuration cycle for regenerated resources; update the evaluation phase diagram of regenerated resources at the beginning of each processing configuration cycle; based on the evaluation phase diagram of each processing configuration cycle, extract the value of each evaluation factor for each cyclic processing path in each processing configuration cycle, and form a value set for each evaluation factor.

[0086] Based on the value set of the evaluation factors, calculate the stable distribution value of each evaluation factor for each cyclic processing path; specifically including:

[0087] Calculate the mean of all values ​​in the value set for each evaluation factor, and use it as a reference value for each evaluation factor;

[0088] Calculate the difference between each value of each evaluation factor and the corresponding reference mean, and take the absolute value as the offset of the corresponding value;

[0089] Set an offset threshold for each evaluation factor; mark values ​​whose offsets are greater than the offset threshold as fluctuating values;

[0090] Calculate the proportion of the volatility of each evaluation factor relative to all values ​​in the value set, and use this as the volatility of the corresponding evaluation factor;

[0091] The stable distribution value of each evaluation factor is calculated based on the volatility; the stable distribution value of each evaluation factor is 1 minus the corresponding volatility.

[0092] The stable distribution values ​​of each evaluation factor are arranged in a specified order to form the scoring reliability tensor of the corresponding cyclic processing path.

[0093] The compensation adjustment of the configuration priority for each loop processing path specifically includes:

[0094] The validity of each loop processing path is calculated based on the rating reliability tensor. The method is as follows: the rating reliability tensor of the current loop processing path is marked as the reference reliability tensor; the rating reliability tensor of the loop processing path whose validity is to be calculated is marked as the target reliability tensor.

[0095] Calculate the difference between the stable distribution values ​​of each evaluation factor in the reference reliability tensor and the target reliability tensor, and take the absolute value as the stability variance of the corresponding evaluation factor; calculate the sum of the stability variances of each evaluation factor.

[0096] Set an adjustment factor, denoted as k; the effectiveness of any loop processing path is 1 minus the sum of k times the stability variability. Those skilled in the art set the value of the adjustment factor k based on actual needs; the adjustment factor k is used to scale the sum of stability variability, ensuring that its value is less than 1, so as to control the effectiveness of the loop processing path to be reasonable (greater than 0).

[0097] The configuration priority is adjusted based on the validity of each loop processing path. The method is as follows: multiply the configuration priority of each loop processing path by the corresponding validity to obtain the updated value of the configuration priority of each loop processing path.

[0098] The stable distribution value describes the fluctuation tendency and degree of each cyclic processing path at the corresponding evaluation factor. The smaller the stable distribution value, the more unstable the evaluation factor, i.e., the higher the uncertainty. The scoring reliability tensor describes the uncertainty of the cyclic processing path at each evaluation factor. The allocation priority is the difference in the comprehensive evaluation index of different cyclic processing paths. Different cyclic processing paths are only highly comparable if they are based on an equally stable evaluation factor structure. When there is a significant difference in the scoring reliability tensor of two cyclic processing paths, it is considered that there is a confidence asymmetry in the scoring basis of the comprehensive evaluation index. At this time, the difference in the scoring reliability tensor is used as a confidence penalty term to suppress the adjustment of the allocation priority, so as to avoid pseudo-optimization of the cyclic processing path due to the calculation error of the comprehensive evaluation index. For example, if the comprehensive evaluation index of the current cyclic processing path A is mainly contributed by the evaluation factors with high stable distribution values, then its comprehensive evaluation index is relatively stable; if the comprehensive evaluation index of path B is mainly contributed by the evaluation factors with low stable distribution values, then its comprehensive evaluation index fluctuates greatly. At this point, even if the comprehensive evaluation indicators of the two are very different, the direct comparability between the two is not high, and the credibility of the difference in the comprehensive evaluation indicators is not high, so it is not suitable to be used directly as a reliable basis for switching cyclic processing paths.

[0099] The cyclic processing path for each type of regenerated resource is configured and adjusted based on the aforementioned configuration priority; specifically, this includes:

[0100] Sort the configuration priority of each loop processing path for each type of recyclable resource by size; set a configuration priority threshold for each type of recyclable resource; for any type of recyclable resource, if the maximum configuration priority is greater than the corresponding configuration priority threshold, it is recommended to switch the current loop processing path to the loop processing path corresponding to the maximum configuration priority.

[0101] Preferably, the configuration priority of each recycling path is visualized in the form of a heat map, which makes it easier for managers to intuitively observe the configuration priority of each recycling path for each type of regenerated resource, thereby assisting in the decision-making of switching recycling paths. Figure 4 A heatmap showing the configuration priority of partial recycling paths for some renewable resources is displayed. (Refer to...) Figure 4Each tile in the heatmap corresponds to the priority of a recycling path for a specific type of recyclable resource. For example, the tile in the lower left corner corresponds to the priority of recycling electronic waste when the current recycling path is landfill. The numbers on any tile and the color depth of the tile represent the heat value, i.e., the priority value. This heatmap can serve as a basis for decision-making regarding switching recycling paths. For instance, food waste has a very high priority for recycling, and switching to this recycling path can be prioritized. Construction waste also has a relatively high priority for co-processing, making it suitable for areas lacking recycling infrastructure. Electronic waste has a generally lower priority, and adjustments to the current recycling path can be postponed or maintained.

[0102] Example 2

[0103] This embodiment is the second embodiment of this application; it is based on the same inventive concept as Embodiment 1, and refers to... Figure 2 This embodiment introduces a phase diagram-based evaluation system for the multi-dimensional performance of renewable resource recycling technologies, including an evaluation phase diagram module, a first calculation module, a second calculation module, a compensation and adjustment module, and a processing configuration module; wherein:

[0104] The evaluation phase diagram module is used to construct an evaluation phase diagram that includes each recycling path of any renewable resource and its corresponding evaluation factors.

[0105] The first calculation module calculates the path discrimination degree of each evaluation factor based on the evaluation phase diagram, and assigns an influence factor to each evaluation factor based on the path discrimination degree. This module extracts the cyclic processing paths of regenerated resources and the evaluation factors from the evaluation phase diagram, constructs a path difference matrix, and determines the discrimination ability of each evaluation factor for different paths by calculating the ratio of the range to the mean of each row of data. The path discrimination degrees of all evaluation factors are summed, and the influence factors are dynamically assigned through normalization calculation to quantify the importance of the evaluation factors.

[0106] The second calculation module calculates the configuration priority of each cyclic processing path based on the evaluation factors and influence factors. This module uses the influence factors as weights to perform a weighted summation of the evaluation factors to obtain the comprehensive evaluation index of each path. Based on the current cyclic processing path, it calculates the difference between the comprehensive evaluation index of each cyclic processing path and the current path to obtain the configuration priority brought about by the switching of cyclic processing paths.

[0107] The compensation adjustment module is used to compensate and adjust the configuration priority of each loop processing path. This module first constructs a score reliability tensor for each loop processing path based on the evaluation phase diagram, and then compensates and adjusts the configuration priority of each loop processing path based on the score reliability tensor.

[0108] The processing configuration module adjusts the cyclic processing path for each type of regenerated resource based on the configuration priority. This module sorts the configuration priority of each cyclic processing path for each type of regenerated resource by size, sets a configuration priority threshold for each regenerated resource, and recommends switching the current cyclic processing path to the cyclic processing path corresponding to the highest configuration priority if the highest priority is greater than the corresponding threshold.

[0109] The specific functions of each module described above are implemented with reference to the relevant content in the phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology described in Example 1, and will not be repeated here.

[0110] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of protection of this application, and these forms are all within the protection scope of this application.

Claims

1. A phase diagram-based evaluation method for the multidimensional performance of renewable resource recycling technologies, characterized by: Includes the following steps: A recycling process path is set for each type of renewable resource; an evaluation factor is set for each recycling process path, and an evaluation phase diagram of the renewable resource is constructed; the evaluation phase diagram includes each recycling process path of any renewable resource and its corresponding evaluation factor. The path discrimination degree of each evaluation factor is calculated based on the evaluation phase diagram; an influence factor is assigned to each evaluation factor based on the path discrimination degree. The evaluation factors are used to evaluate the quality of each cyclic processing path from different dimensions; for any regenerated resource, the path discrimination is calculated as follows: Each evaluation factor for each recycling path of the regenerated resources is extracted based on the evaluation phase diagram. Construct a path difference matrix for recycled resources; let there be m cyclic processing paths for recycled resources, and each cyclic processing path has n evaluation factors, then the path difference matrix is ​​an n-row m-column matrix; m and n are positive integers; the element in the i-th row and j-th column of the path difference matrix represents the i-th evaluation factor of the j-th recycling path of the renewable resources; the value range of i is 1, 2, ..., n; the value range of j is 1, 2, ..., m; The path discrimination of each evaluation factor is calculated based on the path difference matrix; the path discrimination of the i-th evaluation factor is calculated as follows: Extract all elements in the i-th row of the path difference matrix, and calculate the range and mean of all elements in the i-th row; the path discrimination of the i-th evaluation factor is the ratio of the range to the mean of all elements in the i-th row. The configuration priority of each loop processing path is calculated based on the evaluation factors and impact factors. A score reliability tensor for each loop processing path is constructed based on the evaluation phase diagram; the configuration priority of each loop processing path is adjusted and compensated based on the score reliability tensor. The cyclic processing path for each type of regenerated resource is configured and adjusted based on the aforementioned configuration priority. The method for constructing the rating reliability tensor is as follows: Set the processing configuration cycle for regenerated resources; update the evaluation phase diagram of regenerated resources at the beginning of each processing configuration cycle; based on the evaluation phase diagram of each processing configuration cycle, extract the value of each evaluation factor for each cyclic processing path in each processing configuration cycle, and form a value set for each evaluation factor. Based on the value set of the evaluation factors, calculate the stable distribution value of each evaluation factor for each cyclic processing path; The stable distribution values ​​of each evaluation factor are arranged in a specified order to form the scoring reliability tensor of the corresponding cyclic processing path.

2. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 1, characterized in that: For any type of renewable resource, the method for assigning influence factors to each evaluation factor is as follows: Calculate the sum of the path discrimination of each evaluation factor; the influence factor of the i-th evaluation factor is the ratio of the path discrimination of the i-th evaluation factor to the sum of the path discrimination of each evaluation factor.

3. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 2, characterized in that: For any type of recyclable resource, the configuration priority represents the improvement in comprehensive evaluation indicators brought about by switching the cyclic processing path; the method for calculating the configuration priority of each cyclic processing path is as follows: Calculate the comprehensive evaluation index for each cyclic processing path based on the evaluation factors and impact factors. The configuration priority of each cyclic processing path is calculated based on the comprehensive evaluation index, specifically including: determining the current cyclic processing path of the regenerated resources; The overall evaluation index of the current cyclic processing path is subtracted from the overall evaluation index of each cyclic processing path to obtain the configuration priority of each cyclic processing path.

4. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 3, characterized in that: The calculation of the comprehensive evaluation index for each cyclic processing path specifically includes: dividing the evaluation factors of each cyclic processing path into benefit-type evaluation factors and cost-type evaluation factors; weighting and summing all evaluation factors for each cyclic processing path to obtain the comprehensive evaluation index for each cyclic processing path; wherein, the weight of the benefit-type evaluation factor in the weighted summation is the corresponding influence factor; the weight of the cost-type evaluation factor in the weighted summation is the corresponding influence factor multiplied by 1.

5. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 4, characterized in that: The calculation of the stable distribution value of each evaluation factor specifically includes: Calculate the mean of all values ​​in the value set for each evaluation factor, and use it as a reference value for each evaluation factor; Calculate the difference between each value of each evaluation factor and the corresponding reference mean, and take the absolute value as the offset of the corresponding value; Set an offset threshold for each evaluation factor; mark values ​​whose offsets are greater than the offset threshold as fluctuating values; Calculate the proportion of the volatility of each evaluation factor relative to all values ​​in the value set, and use this as the volatility of the corresponding evaluation factor; The stable distribution value of each evaluation factor is calculated based on the volatility; the stable distribution value of each evaluation factor is 1 minus the corresponding volatility.

6. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 5, characterized in that: The compensation adjustment of the configuration priority for each loop processing path specifically includes: The validity of each loop processing path is calculated based on the rating reliability tensor. The method is as follows: the rating reliability tensor of the current loop processing path is marked as the reference reliability tensor; the rating reliability tensor of the loop processing path whose validity is to be calculated is marked as the target reliability tensor. Calculate the difference between the stable distribution values ​​of each evaluation factor in the reference reliability tensor and the target reliability tensor, and take the absolute value as the stability variance of the corresponding evaluation factor; calculate the sum of the stability variances of each evaluation factor. Set an adjustment factor, denoted as k; the effectiveness of any loop processing path is 1 minus the sum of k times the stability differences; The configuration priority is adjusted based on the validity of each loop processing path. The method is as follows: multiply the configuration priority of each loop processing path by the corresponding validity to obtain the updated value of the configuration priority of each loop processing path.

7. The phase diagram evaluation method for the multidimensional performance of renewable resource recycling technology as described in claim 6, characterized in that: The configuration priority is used to adjust the cyclic processing path of each type of recyclable resource. Specifically, this includes: sorting the configuration priority of each cyclic processing path of each type of recyclable resource by size; setting a configuration priority threshold for each type of recyclable resource; and for any type of recyclable resource, if the maximum configuration priority is greater than the corresponding configuration priority threshold, it is recommended to switch the current cyclic processing path to the cyclic processing path corresponding to the maximum configuration priority.

8. A phase diagram-based evaluation system for the multidimensional performance of renewable resource recycling technologies, used to implement the phase diagram-based evaluation method for the multidimensional performance of renewable resource recycling technologies as described in any one of claims 1-7, characterized in that: It includes an evaluation phase diagram module, a first calculation module, a second calculation module, a compensation and adjustment module, and a processing configuration module; among which: The evaluation phase diagram module is used to construct an evaluation phase diagram that includes each recycling path of any renewable resource and its corresponding evaluation factors. The first calculation module calculates the path discrimination of each evaluation factor based on the evaluation phase diagram, and assigns an influence factor to each evaluation factor based on the path discrimination. The second calculation module calculates the configuration priority of each loop processing path based on the evaluation factors and impact factors. The compensation and adjustment module is used to compensate and adjust the configuration priority of each loop processing path; The processing configuration module adjusts the cyclic processing path for each type of regenerated resource based on the configuration priority.

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