Information tracing method and system for garbage pollution waste

Abstract

The present application relates to the garbage disposal technical field, specifically to a kind of garbage pollution waste information traceability method and system.The present application determines initial data accurate value according to the total garbage data and garbage transport situation of each node and its adjacent point in the garbage disposal network diagram of current batch garbage, and combined with the fluctuation of the confusion degree of the same node connection relationship in the garbage disposal network diagram of all batch garbage in historical period, and the same kind garbage data difference of the same node in the garbage disposal network diagram of current batch and batch garbage in historical period, obtain final data accurate value;Using it adjusts the total garbage data of node in the garbage disposal network diagram of current batch garbage to obtain data correction value, then the information traceability of garbage pollution waste is carried out.The present application corrects the data of garbage transport processing process, increases the accuracy of garbage data, and further improves the information traceability effect of garbage pollution waste.

Description

Technical Field

[0001] This invention relates to the field of waste treatment technology, specifically to a method and system for tracing the source of waste pollution. Background Technology

[0002] With socio-economic development, the amount of waste pollution from the petroleum and chemical industries is increasing year by year. This waste often contains large amounts of hazardous substances, such as heavy metals and harmful chemicals. If it is not sorted and directly landfilled or incinerated, it will cause serious pollution to soil, water sources, and the atmosphere, resulting in long-term harm to the environment and ecosystems. Sorting and treating waste pollution from the petroleum and chemical industries helps achieve resource recycling and environmental protection. However, problems arise in the recycling and treatment of waste pollution due to factors such as opaque data, blind spots in cross-regional supervision, and the inability to accurately trace pollution responsibility during waste sorting and transportation.

[0003] Consortium blockchains, with their decentralization, data immutability, and controllable transparency, can solve the problem of information traceability in waste disposal. They use consensus mechanisms for identity verification and data synchronization, encrypt relevant data during waste sorting and transportation, and generate traceable barcodes at each stage to ensure the transparency and traceability of data information throughout the waste sorting and disposal process. However, errors in waste collection statistics and waste loss during transportation can affect the accuracy of waste data, resulting in poor traceability of waste pollution. Summary of the Invention

[0004] To address the technical problem of poor traceability of waste pollution due to low accuracy of waste data, the present invention aims to provide a method and system for tracing waste pollution information. The specific technical solution adopted is as follows:

[0005] In a first aspect, one embodiment of the present invention provides a method for tracing the source of waste pollution, the method comprising:

[0006] Obtain the waste treatment network diagrams for the current batch of waste and each batch of waste in the historical time period, as well as the total waste data and each type of waste data for each node in the network diagram of each batch of waste;

[0007] Based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation, obtain the accurate initial data value of each node in the waste treatment network diagram of the current batch of waste.

[0008] Based on the fluctuations in the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the differences in the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, the initial data accuracy value is adjusted to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste.

[0009] Based on the final data accuracy, the total waste data of each node in the waste treatment network diagram of the current batch of waste is adjusted to obtain the data correction value of the corresponding node; the data correction value is used to trace the source of waste pollution.

[0010] Furthermore, obtaining the accurate initial data values ​​of each node in the waste treatment network graph of the current batch of waste includes:

[0011] Based on the difference in total waste data between the same node and its neighboring nodes in the waste disposal network diagram for all batches of waste within a historical period, the final transportation rate of each node in the waste disposal network diagram is obtained;

[0012] The sum of the products of the total waste data of each node's direct predecessor node in the waste treatment network graph of the current batch of waste and the final transportation rate is calculated as the predicted data value for each node.

[0013] The absolute value of the difference between the total waste data of each node in the waste treatment network diagram of the current batch of waste and the predicted data value is taken as the data error value of the corresponding node. The sum of the data error values ​​of all predecessor nodes of each node in the waste treatment network diagram of the current batch of waste is negatively correlated and normalized to obtain the initial accurate data value of each node in the waste treatment network diagram of the current batch of waste.

[0014] Furthermore, obtaining the final transport rate of each node in the waste disposal network graph includes:

[0015] Obtain the theoretical transport data from each node to each successor node in the waste disposal network diagram for each batch of waste; the total waste data for each node is equal to the sum of the theoretical transport data from each node to all its direct successor nodes.

[0016] Choose any node in the waste treatment network graph of each batch of waste as the target node, and choose any direct successor node of the target node as the target successor node. The ratio of the total waste data of the target successor node to the sum of the theoretical transportation data from all direct predecessor nodes of the target successor node to the target successor node is taken as the local transportation rate of all direct predecessor nodes of the target successor node. The average of all local transportation rates of each node in the waste treatment network graph of each batch of waste is taken as the initial transportation rate of the corresponding node.

[0017] The average of the initial transport rates of the same node in the waste management network graph for all batches of waste within a historical period is calculated as the final transport rate of each node in the waste management network graph.

[0018] Furthermore, obtaining the final accurate data value of each node in the waste treatment network graph of the current batch of waste includes:

[0019] Based on the fluctuations in the degree of disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste within a historical period, the error probability of each node in the waste treatment network diagram is obtained;

[0020] Based on the differences between the data of the same type of waste in each node of the waste treatment network diagram for all batches of waste in the historical period and the data of the current batch of waste, the data anomaly degree of each node in the waste treatment network diagram is obtained;

[0021] Based on the error probability and the data anomaly, the accuracy adjustment coefficient of each node in the waste treatment network diagram of the current batch of waste is obtained; the initial data accuracy value is weighted using the accuracy adjustment coefficient to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste; the error probability and the data anomaly are both negatively correlated with the accuracy adjustment coefficient.

[0022] Furthermore, the acquisition of the error probability of each node in the waste management network graph includes:

[0023] The ratio of the out-degree to the in-degree of each node in the waste treatment network graph for each batch of waste is used as the disorder of the relationship of the corresponding node.

[0024] The discrete index of the disorder of the relationship at the same node in the waste treatment network diagram of all batches of waste within a historical period is normalized to obtain the possible error value of each node in the waste treatment network diagram.

[0025] Furthermore, obtaining the data anomaly degree of each node in the waste management network graph includes:

[0026] The percentage of each type of waste data at the same node in the waste treatment network diagram of all batches of waste within a historical period in the total waste data is taken as the comprehensive percentage value of each type of waste at each node in the waste treatment network diagram.

[0027] The data anomaly degree of each node in the waste treatment network graph of the current batch is obtained by summing the absolute values ​​of the differences between the proportion of each type of waste data in the total waste data and the comprehensive proportion value of each node in the waste treatment network graph of the current batch.

[0028] Further, the step of adjusting the total waste data of each node in the waste treatment network graph of the current batch of waste based on the final data accuracy to obtain the data correction value of the corresponding node includes:

[0029] Using the difference between the constant 1 and the final accurate data value, the difference between the predicted data value and the total waste data of each node in the current batch of waste treatment network diagram is weighted to obtain the adjustment value of the corresponding node;

[0030] The sum of the total waste data of each node in the current batch of waste treatment network diagram and the adjustment value is used as the data correction value for the corresponding node.

[0031] Furthermore, all batches of waste share the same nodes in the waste treatment network graph.

[0032] Furthermore, the discrete index is the average difference.

[0033] Secondly, another embodiment of the present invention provides an information traceability system for waste pollution, the system comprising:

[0034] The data acquisition module is used to acquire the waste treatment network diagram of the current batch of waste and each batch of waste in the historical period, as well as the total waste data and each type of waste data of each node in the network diagram of each batch of waste;

[0035] The Preliminary Accuracy Value Analysis Module is used to obtain the initial accurate data value of each node in the waste treatment network diagram of the current batch of waste based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation.

[0036] The final accurate value analysis module is used to adjust the initial data accurate value based on the fluctuation of the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the difference of the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, and to obtain the final data accurate value of each node in the waste treatment network diagram of the current batch of waste.

[0037] The data correction and tracing module is used to adjust the total waste data of each node in the waste treatment network diagram of the current batch of waste based on the final data accuracy, and obtain the data correction value of the corresponding node; and to use the data correction value to trace the source of waste pollution.

[0038] The present invention has the following beneficial effects:

[0039] In this embodiment of the invention, the waste transportation situation reflects the loss of waste during transportation. The waste of a node is transported from its neighboring points. The predicted value of the node's waste data is obtained by combining the total waste data of the neighboring points and the waste transportation situation. This predicted value is then compared with the total waste data of the node to preliminarily analyze the accuracy of the node's waste data. The fluctuation of the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period reflects the possibility of errors in the waste data of manually measured nodes. The difference between the current batch of waste and the same type of waste data of waste batches in the historical period reflects the degree of abnormality of each type of waste data. The initial data accuracy value is adjusted by combining the above two factors, and the accuracy of the node's waste data is analyzed again to obtain the final data accuracy value. By adjusting the total waste data of the node with the final data accuracy value, the impact of factors such as incorrect statistics of waste collection volume and waste loss during transportation on the total waste data of the node can be effectively reduced, the accuracy of the data correction value of the node in the current batch of waste treatment network diagram can be increased, and the information traceability effect of waste pollution and waste can be improved. Attached Figure Description

[0040] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating the steps of a method for tracing the source of waste pollution provided in one embodiment of the present invention.

[0042] Figure 2 A flowchart of a waste transportation and processing method provided in one embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of a waste management network provided in one embodiment of the present invention;

[0044] Figure 4 This is a partial schematic diagram of a waste management network diagram provided in one embodiment of the present invention;

[0045] Figure 5 This is a flowchart illustrating the steps of a method for obtaining accurate final data values ​​according to an embodiment of the present invention.

[0046] Figure 6 This is a system structure diagram of an information traceability system for waste pollution provided in one embodiment of the present invention;

[0047] Figure 7This is a schematic diagram of a computer device for tracing information on waste pollution, provided as an embodiment of the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a waste pollution information traceability method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] The following description, in conjunction with the accompanying drawings, details the specific scheme of the information tracing method and system for waste pollution provided by this invention.

[0051] Example 1:

[0052] This invention proposes a method for tracing the source of waste pollution. Please refer to [link / reference]. Figure 1 The diagram illustrates a flowchart of a method for tracing the source of waste pollution provided in an embodiment of the present invention. The method includes:

[0053] Step S1: Obtain the waste processing network diagrams for the current batch of waste and each batch of waste in the historical time period, as well as the total waste data and each type of waste data for each node in the network diagram of each batch of waste.

[0054] Figure 2 This is a flowchart illustrating waste transportation and processing according to an embodiment of the present invention. Waste production sources, waste collection stations, waste transfer stations, and waste disposal plants in a certain region are referred to as waste sites. The method for obtaining the waste processing network diagram is as follows: each waste site is treated as a node. Given that waste from waste production sources needs to be transported to waste collection stations, there exists an edge pointing from the node representing the waste production source to the node representing the waste collection station. The connection relationships between other nodes are similar. The waste processing network diagrams for the current batch of waste and each batch of waste in historical time periods are obtained according to the above method.

[0055] Figure 3 This is a schematic diagram of a waste management network provided in one embodiment of the present invention, such as... Figure 3 As shown, Figure 3The black dots in the diagram represent nodes. The nodes inside the dashed box K1 represent waste production sources, the nodes inside the dashed box K2 represent waste collection stations, the nodes inside the dashed box K3 represent waste transfer stations, and the nodes inside the dashed box K4 represent waste treatment plants. The nodes in each dashed box are nodes in the same process.

[0056] The number of waste collection points in a certain region is fixed, making the nodes in the waste treatment network graph identical for all batches of waste. However, due to differences in waste sorting effectiveness at different stages of the waste transportation and processing flow, the waste treatment network graphs for different batches of waste differ, with the differences lying in the connections between nodes. It should be noted that the waste treatment network graph is a directed graph; in the waste transportation and processing flow, a node representing each stage can only point to a node in the next stage.

[0057] In one specific implementation of this invention, the historical time period is set to one year, and each batch of garbage refers to the garbage of a certain region on a certain day. The implementer can set this according to the specific situation.

[0058] Before the waste from each node representing a waste site is transported to other waste sites in the waste network processing graph for each batch of waste, the physical property indicators of the waste from each node representing a waste site are obtained and recorded as the total waste data; then the waste from the waste sites is classified, and the physical property indicators of each type of waste from the waste sites are obtained and recorded as the waste data of each type of node.

[0059] It should be noted that physical property indicators can include waste volume or waste mass, and waste types include: recyclables, kitchen waste, hazardous waste and other waste.

[0060] Step S2: Based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation, obtain the accurate initial data value of each node in the waste treatment network diagram of the current batch of waste.

[0061] The garbage of a node is transported from its neighboring nodes. The garbage transportation situation reflects the loss of garbage during transportation. By combining the total garbage data of the node's neighboring nodes with the garbage transportation situation, the predicted value of the node's garbage data is obtained. This predicted value is then compared with the node's total garbage data, i.e., the actual value, to conduct a preliminary analysis of the accuracy of the node's garbage data and obtain the initial accurate value of the data.

[0062] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the initial data accuracy value includes: obtaining the final transportation rate of each node in the waste treatment network diagram based on the difference in the total waste data of the same node and its neighboring nodes in the waste treatment network diagram of all batches of waste in the historical period; calculating the sum of the products of the total waste data of the direct predecessor nodes of each node in the waste treatment network diagram of the current batch of waste and the final transportation rate, as the data prediction value of each node; taking the absolute value of the difference between the total waste data of each node in the waste treatment network diagram of the current batch of waste and the data prediction value as the data error value of the corresponding node; performing negative correlation and normalization processing on the sum of the data error values ​​of all predecessor nodes of each node in the waste treatment network diagram of the current batch of waste to obtain the initial data accuracy value of each node in the waste treatment network diagram of the current batch of waste.

[0063] Ideally, the total waste data at each node in the waste management network should equal the sum of the total waste data at all nodes in the previous stage. However, waste is subject to loss during transportation, such as waste spillage and liquid leakage, resulting in the total waste data at each node being less than the sum of the total waste data at all nodes in the previous stage. Based on the above theoretical analysis of the waste transportation situation at nodes in the waste management network diagram, the final transportation rate is obtained.

[0064] In this embodiment of the invention, the method for obtaining the final transportation rate is as follows: The theoretical transportation data from each node to each successor node in the waste treatment network diagram of each batch of waste is obtained; the total waste data of each node is equal to the sum of the theoretical transportation data of all its direct successor nodes; one node in the waste treatment network diagram of each batch of waste is randomly selected and designated as the target node, and one direct successor node of the target node is randomly selected and designated as the target successor node; the ratio of the total waste data of the target successor node to the sum of the theoretical transportation data from all its direct predecessor nodes to the target successor node is used as the local transportation rate of all its direct predecessor nodes; the average of all local transportation rates of each node in the waste treatment network diagram of each batch of waste is recorded as the initial transportation rate of the corresponding node; the average of the initial transportation rates of the same node in the waste treatment network diagram of all batches of waste during the historical period is calculated as the final transportation rate of each node in the waste treatment network diagram.

[0065] Before the garbage from a node is transported to its direct successor node, theoretical transport data from the node to each of its successor nodes is obtained, representing the amount of garbage that the node's garbage needs to be transported to each successor node. As an example, Figure 4 This is a partial schematic diagram of a waste management network diagram provided in one embodiment of the present invention. Figure 4 The black dots in the diagram represent nodes. Assume the total garbage volume of node A1 is W_A1, and the total garbage volume of node A2 is W_A1. , This represents the theoretical transportation data from node A2 to its direct successor node B1. This represents the theoretical transport data from node A2 to its direct successor node B2. The total garbage volume of node B1 is W_B1, the total garbage volume of node B2 is W_B2, and the initial transport rate of node A1 is equal to... The initial transport rate of node A2 is equal to .

[0066] It should be noted that the initial transport rate of a node reflects the waste loss during the transport of waste from the node to its successor nodes; the higher the initial transport rate, the less waste loss occurs. The number of local transport rates of a node is equal to the number of its direct successor nodes.

[0067] Considering waste loss, if the total waste data of each node in the waste treatment network diagram of the current batch of waste is closer to the sum of the total waste data of its related previous node, i.e., the direct predecessor node, it means that the data of the current batch of waste at each node is more accurate; at the same time, because the accuracy of data has a cumulative effect, the more accurate the data of the predecessor node, the higher the accuracy of the node's data.

[0068] In one specific implementation of this invention, the initial data accuracy value E of each node in the waste treatment network graph of the current batch of waste is expressed by the formula:

[0069]

[0070] In the formula, N is the total number of predecessor nodes of each node in the waste treatment network graph of the current batch of waste; This represents the total waste data of the nth predecessor node of each node in the waste treatment network graph for the current batch of waste. This represents the total number of direct predecessor nodes of the nth predecessor node of each node in the waste treatment network graph of the current batch of waste. Let h be the final transport rate of the h-th direct predecessor node of the n-th predecessor node of each node in the waste treatment network graph of the current batch of waste. This represents the total waste data of the h-th direct predecessor node of the n-th predecessor node of each node in the waste treatment network graph for the current batch of waste. This represents the predicted data value of the nth predecessor node for each node in the waste treatment network graph of the current batch of waste. This represents the data error value of the nth predecessor node of each node in the waste treatment network diagram for the current batch of waste. is an absolute value function; exp is an exponential function with the natural constant as the base.

[0071] It should be noted that, This represents the predicted total waste data of the nth predecessor node for each node, taking into account waste transportation losses. This is the actual value of the garbage data of the nth predecessor node for each node; if The larger the value, the lower the accuracy of the data in the nth predecessor node of each node, which in turn lowers the accuracy of the data in each node, and the smaller the initial accuracy value of the data in each node. It has a negative correlation with the accuracy of the initial data. For example... Figure 4 As shown, the direct predecessors of node c1 are nodes b1 and b2, and the predecessors of node c1 include: a1, a2, a3, a4, b1, and b2.

[0072] It is important to note that for each predecessor node of a node, if the predecessor node does not have a direct predecessor node and the predecessor node cannot analyze the data error value, then the predecessor node does not need to participate in the analysis process of the initial data accuracy value of each node.

[0073] Step S3: Based on the fluctuations in the degree of disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the differences in the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, adjust the initial data accuracy value and obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste.

[0074] Because different types of waste require different treatment methods, the waste transportation and processing network diagram exhibits variations in vehicle transport processes. Different regions may sort waste at different levels before transporting it to different treatment plants or transfer stations, resulting in a single batch of waste potentially having different transport routes. If waste is well-sorted in the earlier stages, the waste processing network diagram presents a clear tree structure, with the waste generation source representing the root node. Conversely, if waste sorting is poor, the connections between nodes in the network diagram appear chaotic. Fluctuations in the degree of chaos in the connections between the same node in the waste processing network diagrams of all batches of waste over a historical period reflect the possibility of errors in the waste data from manually measured nodes. The proportion of different waste types generated by a region varies, with different regions having different quantities of different types of waste. Differences between the current batch of waste and the data for the same type of waste from previous batches reflect the degree of anomaly in each type of waste data. By combining these two factors to adjust the initial data accuracy value and re-analyzing the accuracy of the waste data at each node, the final data accuracy value is obtained.

[0075] Please see Figure 5 The diagram illustrates a flowchart of a method for obtaining accurate final data values ​​according to an embodiment of the present invention. The method includes:

[0076] Step S310: Based on the fluctuation of the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, obtain the error probability of each node in the waste treatment network diagram.

[0077] In some possible implementations of this invention, the method for obtaining the possible error value includes: taking the ratio of the out-degree to the in-degree of each node in the waste treatment network graph of each batch of waste as the relation disorder degree of the corresponding node; normalizing the discrete index of the relation disorder degree of the same node in the waste treatment network graph of all batches of waste in the historical period to obtain the possible error value of each node in the waste treatment network graph.

[0078] Nodes with larger out-degrees are more likely to engage in waste sorting. A higher out-degree to in-degree ratio indicates more waste sorting operations and a more chaotic node connectivity. A larger discrete index of the disorder in the relationships of the same node across all batches of waste in the waste management network graph over a historical period indicates more variations in the waste transportation routes, a greater likelihood of errors in manually measured waste data, and thus a larger potential error value.

[0079] It should be noted that while the Norm function is used for normalization in this embodiment of the invention, other normalization methods can also be chosen, such as function transformation, max-min normalization, etc., and are not limited here. Mean deviation, variance, standard deviation, and interquartile range can all reflect the degree of data fluctuation; in this embodiment, the dispersion index is the mean deviation, used to measure the degree of fluctuation in the disorder of the relationship; in other embodiments, the mean deviation can be replaced by variance, standard deviation, or interquartile range, etc.

[0080] Step S320: Based on the differences between the data of the same type of waste in each node of the waste treatment network diagram for all batches of waste in the historical period and the data of the same type of waste in the current batch of waste treatment network diagram, obtain the data anomaly degree of each node in the waste treatment network diagram.

[0081] In some possible implementations of this invention, the method for obtaining data anomaly degree includes: taking the proportion of the sum of each type of waste data at the same node in the waste treatment network diagram of all batches of waste within a historical period to the total sum of waste data, as the comprehensive proportion value of each type of waste at each node in the waste treatment network diagram; calculating the sum of the absolute values ​​of the differences between the proportion of each type of waste data at each node in the waste treatment network diagram of the current batch and the comprehensive proportion value, to obtain the data anomaly degree of each node in the waste treatment network diagram of the current batch. In a specific implementation of this invention, the data anomaly degree is expressed by the formula:

[0082]

[0083] In the formula, F represents the data anomaly degree of each node in the waste treatment network graph of the current batch; U represents the number of waste types of each node in the waste treatment network graph of the current batch. This represents the percentage of the u-th type of waste data at each node in the waste treatment network diagram for the current batch in the total waste data. Let be the overall proportion of type u waste at each node in the waste management network graph; Norm is the normalization function. It is an absolute value function. It should be noted that... This can be viewed as a node representing the normal proportion of each type of junk data received by a junk site within the total junk data. The larger the value, the greater the difference in physical properties between the current batch of waste and the same type of waste received by each waste station at each node in historical periods. This indicates a greater degree of anomaly in the data for each type of waste in the current batch, and a higher data anomaly rate.

[0084] Step S330: Based on the probability of error and the degree of data anomaly, obtain the accuracy adjustment coefficient of each node in the waste treatment network diagram of the current batch of waste; use the accuracy adjustment coefficient to weight the initial data accuracy value to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste.

[0085] The greater the probability of error and the higher the data anomaly, the greater the likelihood of errors and anomalies in the total waste data of each node in the current batch of waste management network graph. This results in lower accuracy of the total waste data for each node, requiring a smaller accuracy adjustment coefficient to ensure lower data accuracy. Therefore, both the probability of error and the data anomaly are negatively correlated with the accuracy adjustment coefficient. In this embodiment of the invention, the product of the probability of error and the data anomaly of each node in the waste management network graph is negatively correlated and normalized to obtain the accuracy adjustment coefficient for the corresponding node.

[0086] In one specific implementation of this invention, the final accurate data value is expressed by the formula:

[0087]

[0088] In the formula, denoted as , where is the final accurate data value of each node in the waste treatment network graph for the current batch of waste; E is the initial accurate data value of each node in the waste treatment network graph for the current batch of waste; U is the data anomaly degree of each node in the waste treatment network graph; F is the data anomaly degree of each node in the waste treatment network graph for the current batch of waste; Norm is the normalization function; exp is the exponential function with the natural constant as the base.

[0089] Step S4: Adjust the total waste data of each node in the waste treatment network diagram of the current batch of waste based on the final data accuracy to obtain the data correction value of the corresponding node; use the data correction value to trace the source of waste pollution.

[0090] Adjusting the total waste data of a node using the final accurate data value can effectively reduce the impact of factors such as incorrect waste collection statistics and waste loss during transportation on the node's total waste data, and increase the accuracy of the data correction value of the node in the waste treatment network diagram for the current batch.

[0091] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the data correction value includes: using the difference between the constant 1 and the final accurate data value, weighting the difference between the predicted data value of each node in the current batch of waste treatment network diagram and the total waste data to obtain the adjustment value of the corresponding node; and using the sum of the total waste data and the adjustment value of each node in the current batch of waste treatment network diagram as the data correction value of the corresponding node.

[0092] If the total waste volume of a node in the waste management network diagram for the current batch of waste is less than the predicted data value, the total waste data for that node should be increased; conversely, the total waste data should be decreased. The difference between the predicted data value and the total waste data for a node represents the required adjustment level for that node's waste data. However, since nodes with higher final data accuracy values ​​require less adjustment, it is necessary to use the difference between a constant 1 and the final data accuracy value to adjust the required adjustment level for the node's waste data, thus obtaining the node's adjustment value. The data correction value is expressed by the formula:

[0093]

[0094]

[0095] In the formula, is the data correction value for each node in the waste management network graph for the current batch; W is the total waste data for each node in the waste management network graph for the current batch. This represents the predicted data value for each node in the waste management network diagram for the current batch. G represents the final accurate data value of each node in the waste treatment network graph of the current batch of waste; G represents the total number of direct predecessor nodes of each node in the waste treatment network graph of the current batch of waste. Let g be the final transport rate of the g-th direct predecessor node of each node in the waste treatment network graph of the current batch of waste. This represents the total waste data of the g-th direct predecessor node of each node in the waste treatment network graph for the current batch of waste. This represents the adjustment value for each node in the waste management network diagram for the current batch.

[0096] When using a consortium blockchain for data storage, when garbage enters each node representing a garbage collection site, the garbage volume, garbage type, operator information, and arrival time of the garbage at the garbage collection site are statistically analyzed. This data is first stored in JSON as key-value pairs, and then converted to Base64 encoding. An online QR code generator is then used to convert the Base64 encoding of each node into a QR code, obtaining a traceability code. Next, the garbage information of each site is obtained through the traceability code of its direct predecessor node, and the total garbage data for each node is corrected. Then, the corrected data value, garbage type, operator information, arrival time of the garbage at the garbage collection site, and the traceability code of each node's direct predecessor node are stored on the blockchain via a smart contract and broadcast through a consensus mechanism to synchronize information and form traceability conditions. During tracing, the connection relationship between traceability codes allows for the identification of relevant garbage collection sites level by level, completing information tracing through accurate garbage data.

[0097] This invention is now complete.

[0098] Example 2:

[0099] This invention proposes an information traceability system for waste pollution. Please refer to [link / reference]. Figure 6 The diagram illustrates a system structure of an information traceability system for waste pollution provided in an embodiment of the present invention. The system includes:

[0100] The data acquisition module 510 is used to acquire the waste treatment network diagram of the current batch of waste and each batch of waste in the historical period, as well as the total waste data and each type of waste data of each node in the network diagram of each batch of waste;

[0101] The accurate value preliminary analysis module 520 is used to obtain the initial data accurate value of each node in the waste treatment network diagram of the current batch of waste based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation.

[0102] The final accuracy value analysis module 530 is used to adjust the initial data accuracy value based on the fluctuation of the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the difference of the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, and to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste.

[0103] The data correction and tracing module 540 is used to adjust the total waste data of each node in the waste treatment network diagram of the current batch of waste based on the final data accuracy, and obtain the data correction value of the corresponding node; and to use the data correction value to trace the source of waste pollution.

[0104] It should be noted that the devices provided in the above embodiments are only illustrative examples of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the waste pollution information traceability system and the waste pollution information traceability method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0105] Example 3:

[0106] Figure 7 This is a schematic diagram of a computer device for tracing the source of waste pollution, provided as an embodiment of the present invention. For example,... Figure 7 As shown, the computer device includes: a memory 601, a processor 602, and a computer program 603 stored in the memory 601 and running on the processor 602, wherein when the processor 602 executes the computer program 603, the computer device can execute any of the aforementioned waste pollution traceability methods.

[0107] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform an information tracing method for waste pollution provided in embodiments of this application.

[0108] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0109] It should be understood that the apparatus provided in this embodiment is used to execute the above-described method for tracing the source of waste pollution, and therefore can achieve the same effect as the above-described implementation method.

[0110] When using integrated units, the device may include a processing module and a storage module. When applied to a workpiece, the processing module can be used to control and manage the workpiece's operations. The storage module can be used to support the execution of program code by the workpiece.

[0111] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits contained in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0112] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0113] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for tracing the source of information on waste pollution, characterized in that, The method includes: Obtain the waste treatment network diagrams for the current batch of waste and each batch of waste in the historical time period, as well as the total waste data and each type of waste data for each node in the network diagram of each batch of waste; Based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation, obtain the accurate initial data value of each node in the waste treatment network diagram of the current batch of waste. Based on the fluctuations in the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the differences in the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, the initial data accuracy value is adjusted to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste. Based on the final accurate data value, adjust the total waste data of each node in the waste treatment network diagram of the current batch of waste to obtain the data correction value of the corresponding node; use the data correction value to trace the source of waste pollution; The process of obtaining the final accurate data value of each node in the waste treatment network graph of the current batch of waste includes: Based on the fluctuations in the degree of disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste within a historical period, the error probability of each node in the waste treatment network diagram is obtained; Based on the differences between the data of the same type of waste in each node of the waste treatment network diagram for all batches of waste in the historical period and the data of the current batch of waste, the data anomaly degree of each node in the waste treatment network diagram is obtained; Based on the error probability and the data anomaly, the accuracy adjustment coefficient of each node in the waste treatment network diagram of the current batch of waste is obtained; the initial data accuracy value is weighted using the accuracy adjustment coefficient to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste; the error probability and the data anomaly are both negatively correlated with the accuracy adjustment coefficient.

2. The method for tracing the source of waste pollution according to claim 1, characterized in that, The process of obtaining the accurate initial data values ​​for each node in the waste treatment network graph of the current batch of waste includes: Based on the difference in total waste data between the same node and its neighboring nodes in the waste disposal network diagram for all batches of waste within a historical period, the final transportation rate of each node in the waste disposal network diagram is obtained; The sum of the products of the total waste data of each node's direct predecessor node in the waste treatment network graph of the current batch of waste and the final transportation rate is calculated as the predicted data value for each node. The absolute value of the difference between the total waste data of each node in the waste treatment network diagram of the current batch of waste and the predicted data value is taken as the data error value of the corresponding node. The sum of the data error values ​​of all predecessor nodes of each node in the waste treatment network diagram of the current batch of waste is negatively correlated and normalized to obtain the initial accurate data value of each node in the waste treatment network diagram of the current batch of waste.

3. The method for tracing the source of waste pollution according to claim 2, characterized in that, The process of obtaining the final transport rate of each node in the waste disposal network graph includes: Obtain the theoretical transport data from each node to each successor node in the waste disposal network diagram for each batch of waste; the total waste data for each node is equal to the sum of the theoretical transport data from each node to all its direct successor nodes. Choose any node in the waste treatment network graph of each batch of waste as the target node, and choose any direct successor node of the target node as the target successor node. The ratio of the total waste data of the target successor node to the sum of the theoretical transportation data from all direct predecessor nodes of the target successor node to the target successor node is taken as the local transportation rate of all direct predecessor nodes of the target successor node. The average of all local transportation rates of each node in the waste treatment network graph of each batch of waste is taken as the initial transportation rate of the corresponding node. The average of the initial transport rates of the same node in the waste management network graph for all batches of waste within a historical period is calculated as the final transport rate of each node in the waste management network graph.

4. The method for tracing the source of waste pollution according to claim 1, characterized in that, The method of obtaining the error probability of each node in the waste management network graph includes: The ratio of the out-degree to the in-degree of each node in the waste treatment network graph for each batch of waste is used as the disorder of the relationship of the corresponding node. The discrete index of the disorder of the relationship at the same node in the waste treatment network diagram of all batches of waste within a historical period is normalized to obtain the possible error value of each node in the waste treatment network diagram.

5. The method for tracing the source of waste pollution according to claim 1, characterized in that, The process of obtaining the data anomaly degree of each node in the waste management network graph includes: The percentage of each type of waste data at the same node in the waste treatment network diagram of all batches of waste within a historical period in the total waste data is taken as the comprehensive percentage value of each type of waste at each node in the waste treatment network diagram. The data anomaly degree of each node in the waste treatment network graph of the current batch is obtained by summing the absolute values ​​of the differences between the proportion of each type of waste data in the total waste data and the comprehensive proportion value of each node in the waste treatment network graph of the current batch.

6. The method for tracing the source of waste pollution according to claim 2, characterized in that, The process of adjusting the total waste data of each node in the waste treatment network diagram for the current batch of waste based on the final accurate data value to obtain the data correction value for the corresponding node includes: Using the difference between the constant 1 and the final accurate data value, the difference between the predicted data value and the total waste data of each node in the current batch of waste treatment network diagram is weighted to obtain the adjustment value of the corresponding node; The sum of the total waste data of each node in the current batch of waste treatment network diagram and the adjustment value is used as the data correction value for the corresponding node.

7. The method for tracing the source of waste pollution according to claim 2, characterized in that, The nodes in the waste treatment network diagram are the same for all batches of waste.

8. The method for tracing the source of waste pollution according to claim 4, characterized in that, The discrete index is the average difference.

9. An information traceability system for waste pollution, characterized in that, The system includes: The data acquisition module is used to acquire the waste treatment network diagram of the current batch of waste and each batch of waste in the historical period, as well as the total waste data and each type of waste data of each node in the network diagram of each batch of waste; The Preliminary Accuracy Value Analysis Module is used to obtain the initial accurate data value of each node in the waste treatment network diagram of the current batch of waste based on the total waste data of each node in the waste treatment network diagram of the current batch of waste, as well as the total waste data of each node's adjacent nodes and the waste transportation situation. The final accurate value analysis module is used to adjust the initial data accurate value based on the fluctuation of the disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste in the historical period, and the difference of the same type of waste data of the same node in the waste treatment network diagram of the current batch of waste and the batches of waste in the historical period, and to obtain the final data accurate value of each node in the waste treatment network diagram of the current batch of waste. The data correction and tracing module is used to adjust the total waste data of each node in the waste treatment network diagram of the current batch of waste based on the final accurate data value, and obtain the data correction value of the corresponding node; and to use the data correction value to trace the source of waste pollution. The process of obtaining the final accurate data value of each node in the waste treatment network graph of the current batch of waste includes: Based on the fluctuations in the degree of disorder of the connection relationship of the same node in the waste treatment network diagram of all batches of waste within a historical period, the error probability of each node in the waste treatment network diagram is obtained; Based on the differences between the data of the same type of waste in each node of the waste treatment network diagram for all batches of waste in the historical period and the data of the current batch of waste, the data anomaly degree of each node in the waste treatment network diagram is obtained; Based on the error probability and the data anomaly, the accuracy adjustment coefficient of each node in the waste treatment network diagram of the current batch of waste is obtained; the initial data accuracy value is weighted using the accuracy adjustment coefficient to obtain the final data accuracy value of each node in the waste treatment network diagram of the current batch of waste; the error probability and the data anomaly are both negatively correlated with the accuracy adjustment coefficient.

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