Inland waterway network traffic state assessment method based on complex network

Abstract

The invention discloses an inland waterway network traffic state evaluation method based on a complex network, and the method comprises the steps: determining a research region and a time range, collecting related data, constructing an inland waterway topology network through employing a Space L method and graph theory knowledge, and calculating network feature indexes; constructing an index system, calculating the weight of each index according to an AHP-entropy weight method combination, selecting a proper evaluation model, and quantifying the weights of nodes and legs in the channel network; checking the ship traffic capacity of nodes and legs in the inland waterway network; evaluating the traffic state of each node and leg in the inland waterway network by taking the ratio of the ship traffic volume to the traffic capacity as a traffic state index; and constructing a step-by-step calculation model, and evaluating the overall traffic state of the channel network. The method breaks through the limitation that the previous research singly focuses on specific spatial scales (such as channels and ship locks), starts from a complex network theory, comprehensively considers the importance of a network structure, and realizes the macroscopic grasp of the traffic state of the whole channel network.

Description

Technical Field

[0001] The invention relates to an inland waterway network traffic status assessment method, belonging to the technical field of inland waterway transportation. Background Art

[0002] Networking is a typical symbol and development direction of modern transportation infrastructure construction. Inland waterway shipping has developed from the past "linear operation" to a new stage of "networked operation". With the rapid development of water transportation, the demand for navigation continues to expand, and there is a clear trend of large-scale ships and diversified ship types, and the traffic situation in inland waterways is becoming increasingly complex. In this scenario, when key nodes or waterways in the waterway network are blocked, the transportation performance of the shipping system will drop sharply. Therefore, how to identify the traffic status of inland waterways has become one of the core issues of intelligent management of inland waterways, and the traffic status of key structures that affect the overall network transportation efficiency needs to be highly concerned and valued.

[0003] At present, the research on the traffic status of inland waterway transport is still in its infancy and has not yet formed a system. The selection of its status indicators is usually based on road traffic flow theory, combined with the characteristics of water transport and actual conditions to innovate, such as the introduction of navigation guarantee rate for locks; speed, density, and traffic load ratio for waterways. However, most of the research on the traffic status of inland waterway networks only focuses on a single spatial scale such as waterways and locks, and there are few studies that evaluate the overall traffic status of the waterway network from a global perspective. Summary of the invention

[0004] According to the above-mentioned deficiencies in the existing inland waterway network traffic status assessment, the present invention breaks through the limitations of previous studies that only focus on specific spatial scales (such as waterways and locks), comprehensively considers the importance of network structure, and achieves a macroscopic grasp of the traffic status of the entire waterway network. It provides an inland waterway network traffic status assessment method based on a complex network, which is helpful to promote research progress in the field of inland waterway network traffic status assessment, promote the development of inland waterway shipping towards intelligence, networking and sustainability, and provide strong support for building an efficient, green and safe water transportation system.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] In a first aspect, the present invention provides a method for evaluating the traffic status of an inland waterway network based on a complex network, the method comprising:

[0007] S1. Determine the research area and time range, construct the inland waterway topological network, and calculate the network characteristic indicators;

[0008] S2. Construct an evaluation index system and calculate the weight of each evaluation index to quantify the weight of each node and edge in the topological network;

[0009] S3, the capacity of each node and edge in the calculation;

[0010] S4. Use the ratio of ship traffic volume to traffic capacity as the traffic status index to evaluate the traffic status of each node and edge.

[0011] Furthermore, S1 specifically includes:

[0012] Determine the research area and time range, and construct an inland waterway topological network based on the Space L method and graph theory knowledge; in which the ship locks, operation areas, and section intersections in the inland waterway network are abstracted as nodes, and the sections connecting the nodes are abstracted as edges;

[0013] Use the adjacency matrix W = [a ij ] n*n Represents the connectivity between nodes. If there is an edge between nodes i and j, then a ij =1, on the contrary a ij =0;

[0014] According to the adjacency matrix W, the network characteristic indicators are calculated, including node degree, betweenness, closeness centrality, eigenvector centrality, and edge betweenness.

[0015] Furthermore, S2 specifically includes:

[0016] S21. For nodes, the degree, betweenness, closeness centrality, eigenvector centrality, node flow, node attributes, and node scale of nodes are selected as evaluation indicators to construct a node index system; for edges composed of flight segments, edge betweenness, ship flow, flight segment attributes, and navigation level are selected as evaluation indicators to construct an edge index system;

[0017] S22. Construct judgment matrices for node and edge indicator systems respectively, and apply analytic hierarchy process to calculate the subjective weight of each evaluation indicator;

[0018] S23. For the node and edge indicator systems, the entropy weight method is used to obtain the objective weight of each evaluation indicator;

[0019] S24. The arithmetic mean of the subjective weight and the objective weight is used as the combined weight of each evaluation index;

[0020] S25. Quantify the weight of each node and edge using the combined weight of the above evaluation indicators, and then set the weight value of each node and edge to be the ratio of the quantized weight value of each node and edge to the sum of the quantized weight values ​​of all nodes and flight segments.

[0021] Furthermore, S3 specifically includes:

[0022] S31. Calculate the segment capacity C within the study time range:

[0023]

[0024] Among them, C is the traffic capacity of the section within the study time range; s is the number of ships allowed to sail in parallel in the cross section of the section; t is the navigation time of the section within the study time range; V is the ship operating speed; m is the ship spacing coefficient; L is the ship length; β1 is the speed loss coefficient caused by ship overtaking and passing; β2 is the load reduction coefficient caused by the change of ship draft; β3 is the increase in operating resistance caused by the increase in ship traffic flow density; β4 is the throughput reduction coefficient caused by the imbalance of port arrival and departure and section scheduling; β5 is the average loading factor of the ship;

[0025] S32. The capacity of a node as a segment intersection within the study time period is the average capacity of the segments connected to it multiplied by the reduction factor;

[0026] S33. The capacity of a node as an operation area within the research time range is the average capacity of the connected segments multiplied by the reduction factor;

[0027] S34. The traffic capacity of the node serving as a ship lock within the research time range is calculated from the annual traffic capacity of the ship lock.

[0028] Furthermore, S4 specifically includes:

[0029] S41, for a node, its traffic status index is the ship flow of node i within the study time range and capacity Ratio:

[0030] S42, for the edge, its traffic state index is the ship flow of segment k within the study time range and capacity Ratio:

[0031] Furthermore, the overall assessment method also includes:

[0032] S5. Construct a step-by-step calculation model to evaluate the overall traffic status of the inland waterway network.

[0033] Furthermore, S5 specifically includes:

[0034] S51, overall traffic status index of all nodes n is the total number of nodes;

[0035] S52, overall traffic status index of all edges

[0036] In a second aspect, a computer-readable storage medium storing one or more programs is also provided. The one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform the method as described above.

[0037] According to a third aspect, an electronic device is also provided, comprising one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method described above.

[0038] Compared with the prior art, the present invention has the following significant advantages:

[0039] (1) The evaluation method proposed in this paper breaks through the limitation of previous studies that only focused on the traffic status of a specific spatial scale (such as waterways and locks), considers the importance of network structure, and achieves a macroscopic grasp of the traffic status of the entire waterway network. It has important reference significance for inland waterway management departments to conduct network traffic status evaluation.

[0040] (2) The evaluation method proposed in the present invention has easy-to-acquire data, simple methods, clear and intuitive results, and is flexible and scalable. It can dynamically adjust evaluation indicators and model parameters according to the needs of different time scales (such as hours, months, and years) and spatial scopes (such as river basins and regions), providing a scientific basis for the planning, design, management and emergency response of the inland waterway network. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the process of the present invention.

[0042] Figure 2 This is the topological network map of inland waterways in Jiangsu Province.

[0043] Figure 3 This is the traffic status map of the inland waterway network in Jiangsu Province. DETAILED DESCRIPTION

[0044] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] like Figure 1 As shown, the present invention provides a method for evaluating the traffic status of an inland waterway network based on a complex network, the steps of which are:

[0047] S1. Determine the research area and time range, collect relevant data, use the Space L method and graph theory knowledge to construct the inland waterway topological network, and calculate the network characteristic indicators;

[0048] S2. Construct an indicator system, such as calculating the weight of each indicator based on the AHP-entropy weight method, selecting a suitable evaluation model, and quantifying the weights of nodes and edges in the waterway network;

[0049] S3. Calculate the ship traffic capacity of nodes and edges in the inland waterway network;

[0050] S4. Use the ratio of ship traffic volume to traffic capacity as the traffic status index to evaluate the traffic status of each node and edge in the inland waterway network;

[0051] S5. Construct a step-by-step calculation model to evaluate the overall traffic status of the inland waterway network.

[0052] In the specific implementation, as a preferred embodiment of the present invention, in step S1, the research area and time range are determined, relevant data are collected, the SpaceL method and graph theory knowledge are used to construct the inland waterway topological network, and the network characteristic indicators are calculated, including:

[0053] S11. Assume that the geographical area of ​​this embodiment is Jiangsu Province. Figure 2 As shown in the figure, the time range is July 2022. Based on the Space L method, the fourth-level and above trunk sections in the inland waterway network of Jiangsu Province are abstracted as edges, and the locks, main operating areas, and section intersections (the intersection of two or more sections or the section and the boundary of the jurisdiction) on the sections are abstracted as nodes to construct the topological network of inland waterways in Jiangsu Province. The network consists of 49 locks, 75 section intersections, 33 main operating areas, a total of 157 nodes, and 182 edges.

[0054] S12. Collect relevant data information, including: node attributes (is the node a lock, an operation area, or a section intersection), node scale (the operation area and section intersection are based on the section level of the section in which they are located, and the lock is based on its lock level), node longitude and latitude, navigation level and attributes of the section (if the adjacent nodes of the section contain an operation area or a lock, the values ​​are 3 or 2, and the rest are 1). At the same time, based on the AIS data of inland ships in Jiangsu Province in July 2022, the flow rate of each section, operation area, and section intersection is counted, and the throughput of each lock is obtained based on the lock passing data.

[0055] S13. Use graph G = (V, E) to describe the topological network of inland waterways in Jiangsu Province, where the point set V = {v1, v2, ..., v n}, n is the total number of nodes, n = 157, v i It represents node i, and contains the following fields: node ID, node attribute, node name, node scale, node longitude and latitude, node flow, and some results are shown in Table 1; the edge set is E = {e1, e2, ..., e m}, m is the total number of edges, m = 182, e k Represents edge k, which contains the following fields: edge ID, edge start point, edge end point, edge attribute, navigation level, and ship flow. Some results are shown in Table 2.

[0056] Table 1 Topological network node information of inland waterways in Jiangsu Province

[0057]

[0058] Table 2. Information on the topological network of inland waterways in Jiangsu Province

[0059]

[0060]

[0061] S14. Use the adjacency matrix W to represent the connectivity between nodes in the inland waterway network of Jiangsu Province. W is a 157-order square matrix, and its element a ij Indicates the connection relationship between node i and node j. If there is an edge, then a ij =1, on the contrary a ij =0.

[0062] S15. According to the adjacency matrix W, Gephi is used to calculate the characteristic indicators of the inland waterway network in Jiangsu Province, including the degree, betweenness, closeness centrality, eigenvector centrality and edge betweenness of the nodes.

[0063] In the specific implementation, as a preferred embodiment of the present invention, in step S2, an index system is constructed, the weight of each index is calculated according to the AHP-entropy weight method, a suitable evaluation model is selected, and the weights of nodes and edges in the waterway network are quantified, including:

[0064] S21. For nodes, select node degree, betweenness, closeness centrality, eigenvector centrality, node flow, node attributes, and node scale to build an index system; for edges composed of flight segments, select edge betweenness, ship flow, flight segment attributes, and navigation grade to build an index system.

[0065] S22. For the node and segment indicator systems, comparison matrices B1 and B2 were constructed respectively, and the analytic hierarchy process was used to calculate the subjective weight of each indicator. The consistency test results were 0.07269 and 0.07336 respectively, which met the requirements.

[0066]

[0067] S23. For the node and edge indicator systems, the entropy weight method is used to obtain the objective weight of each evaluation indicator.

[0068] S24. Combining the subjective weight and the objective weight, the arithmetic mean is used as the combined weight of each evaluation index. The calculation results are shown in Table 3.

[0069] Table 3 Calculation results of weights of each indicator

[0070]

[0071] S25. Using the combined weights of the above indicators, the TOPSIS method combined with grey correlation is selected to quantify the weights of nodes and sections in the inland waterway network of Jiangsu Province. Then the weight value of each node and edge is set to be the ratio of the quantified weight value to the quantified weight values ​​of all nodes and edges. Some results are shown in Tables 4 and 5, where the sum of the quantified weights of the node set is 75.99, and the sum of the quantified weights of the edge set is 81.11.

[0072] Table 4 Node weights of Jiangsu Province inland waterway topological network

[0073]

[0074] Table 5 Weights of the topological network of inland waterways in Jiangsu Province

[0075]

[0076] S26. Add the weight fields calculated for each node and edge obtained in S25 to the graph G = (V, E), then the weight of node i is The weight of edge k is

[0077] In specific implementation, as a preferred embodiment of the present invention, in step S3, calculating the ship traffic capacity of nodes and edges in the inland waterway network includes:

[0078] S31. Define the values ​​of each parameter of the waterway capacity calculation formula based on the navigation level of the waterway section, and calculate the capacity of each side (waterway section). Among them, the value of t is calculated based on the first-class and second-class waterways according to the first-class maintenance (the navigation time guarantee rate is not less than 98%), the third-class waterway according to the second-class maintenance (the navigation time guarantee rate is not less than 95%), and the fourth-class waterway according to the third-class maintenance (the navigation time guarantee rate is not less than 90%). That is, taking the month as the time unit, the navigation log of the second-class waterway is t = 30 * 24 * 0.98 = 705.6 hours; at the same time, assuming that the average ship load of the second-class waterway is 2,000 tons, the third-class waterway is 1,000 tons, and the fourth-class waterway is 500 tons, and based on this, according to the GB50139-2014 inland navigation standard, the ship length L is taken, and the results are shown in Table 6.

[0079] Table 6 Parameter values ​​of capacity formula and waterway capacity according to segment level

[0080]

[0081] S32. Determine the connected segments of the segment intersection (i.e., the edges connected to the segment intersection nodes in the topological network), multiply the average capacity of these connected segments by the reduction factor 0.5, and calculate the ship capacity at the segment intersection node. Some results are shown in Table 7.

[0082] Table 7 Calculation of traffic capacity at route segment intersections

[0083]

[0084] S33. Determine the connected segments of the operation area (i.e., the edges connected to the operation area nodes in the topological network), multiply the average capacity of these connected segments by the reduction factor of 0.8, and calculate the ship capacity at the operation area nodes. Some results are shown in Table 8.

[0085] Table 8 Calculation of traffic capacity in the work area

[0086]

[0087]

[0088] S34. The annual capacity of the lock node is determined according to its design documents, and the monthly capacity is calculated based on the navigation guarantee rate, ship load factor and flow balance coefficient. Some results are shown in Table 9.

[0089] The ship lock capacity is the product of the annual number of passages, the average number of passages per day, and the average tonnage of the ship passing through the lock, taking into account the influence of the ship balance and the ship's load capacity:

[0090]

[0091] In the formula, num is the average number of lock-passing times; N is the number of annual navigation, N = 365 × γ, γ is the navigation guarantee rate; G is the average tonnage of a lock-passing; α is the ship load factor; is the balance coefficient of ships arriving at the lock.

[0092] The annual capacity of the ship lock node is directly obtained by the relevant departments. The monthly capacity and hourly capacity can be inferred based on the above formula. Therefore, the monthly capacity and hourly capacity of the ship lock are:

[0093]

[0094]

[0095] Table 9 Calculation of ship lock capacity

[0096]

[0097] S35. Add the capacity fields calculated for each node (including the segment intersection, operation area and lock) and segment to the graph G = (V, E). Then the capacity of node i is The capacity of edge k is

[0098] In specific implementation, as a preferred embodiment of the present invention, in step S4, the ratio of ship traffic volume to traffic capacity is used as the traffic state index to evaluate the traffic state of each node and edge in the inland waterway network, including:

[0099] S41. For a node, its traffic state index is the ship flow of node i during the study period and capacity Ratio: The calculation results of traffic status of each node in Jiangsu Province’s inland waterway network are shown in Table 10.

[0100] S42. For an edge, its traffic state index is the ship flow of edge k during the study time and capacity Ratio: The calculation results of traffic status on each side of Jiangsu Province’s inland waterway network are shown in Table 11.

[0101] The results show that the traffic status index ranges of the navigation sections, navigation section intersections and operation areas in Jiangsu inland waterway network are 0.01-0.07, 0.01-0.37 and 0.01-0.18 respectively. The traffic status is good, but most of the locks are facing varying degrees of congestion, among which the locks with a status index greater than 0.9 account for 61% of the total. Figure 3Different colors are used to represent different traffic operation status, which presents the traffic status of each node and edge of Jiangsu Province's inland waterway network in a more intuitive and comprehensive way.

[0102] From a regional perspective, the waterway network in southern Jiangsu is busier than that in northern Jiangsu. This is mainly due to the developed economy in southern Jiangsu, the high demand for water transport, the denser waterway network, the large number of intersections, operation areas, locks and other nodes, the large volume of ships, and the relatively complex traffic conditions. Therefore, the traffic operation status is more prominent. In contrast, the overall traffic operation status of the waterway network in northern Jiangsu is slightly better, but there is still congestion at some nodes.

[0103] Table 10 Traffic status index of each node in Jiangsu Province inland waterway network

[0104]

[0105] Table 11 Traffic status index of each section of Jiangsu inland waterway network

[0106]

[0107]

[0108] In specific implementation, as a preferred embodiment of the present invention, in step S5, a step-by-step calculation model is constructed to evaluate the overall traffic status of the waterway network, including:

[0109] S51, traffic status index of each node obtained by calculation and node weight Weighted calculation of traffic status index of inland waterway network node set in Jiangsu Province

[0110] S52, based on the calculated traffic status index of each side and segment weight Weighted calculation of traffic status index of Jiangsu Province inland waterway network segment set The results are shown in Table 12.

[0111] Table 12 Traffic status of inland waterway network in Jiangsu Province

[0112]

[0113] Through calculation, the state index of the node set is 0.370, and the traffic state index of the edge set is 0.029. The difference between these two values ​​reflects the significant difference in the operation status of the nodes and edges. Overall, the operation status of ships on the waterway is smooth, which is significantly better than the situation at the nodes. The traffic state index of the waterway is kept below 0.1, which means that ships can maintain a steady speed, the traffic flow is stable, and the service level and operation efficiency are extremely high.

[0114] The present invention breaks through the limitation of previous studies that only focused on specific spatial scales (such as waterways and locks). Starting from the complex network theory, the present invention comprehensively considers the importance of network structure, realizes the macroscopic grasp of the traffic status of the entire waterway network, and improves the shortcomings of the existing evaluation methods. In addition, the data is easy to obtain, the calculation is simple, and the results are intuitive. It has important reference significance for inland waterway management departments to conduct network traffic status evaluation, helps to promote the research progress in the field of inland waterway network traffic status evaluation, promotes the development of inland shipping towards intelligence, networking and sustainability, and provides strong support for building an efficient, green and safe water transportation system.

[0115] Based on the same technical solution, the present invention also provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, enable the computing device to execute the above-mentioned inland waterway traffic operation status assessment method.

[0116] Based on the same technical solution, the present invention also provides an electronic device, comprising one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing the above-mentioned inland waterway traffic operation status assessment method.

[0117] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented 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.

[0118] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0119] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0121] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for evaluating the traffic status of an inland waterway network based on a complex network, characterized in that: The evaluation methods include: S1. Determine the research area and time range, construct the inland waterway topological network, and calculate the network characteristic indicators; S2. Construct an evaluation index system and calculate the weight of each evaluation index to quantify the weight of each node and edge in the topological network; S3, the capacity of each node and edge in the calculation; S4. Use the ratio of ship traffic volume to traffic capacity as the traffic status index to evaluate the traffic status of each node and edge.

2. According to the complex network-based inland waterway network traffic status assessment method of claim 1, it is characterized in that: S1 specifically includes: Determine the research area and time range, and construct an inland waterway topological network based on the Space L method and graph theory knowledge; in which the ship locks, operation areas, and section intersections in the inland waterway network are abstracted as nodes, and the sections connecting the nodes are abstracted as edges; Use the adjacency matrix W = [a ij ] n*n Represents the connectivity between nodes. If there is an edge between nodes i and j, then a ij =1, on the contrary a ij =0; n is the total number of nodes; According to the adjacency matrix W, the network characteristic indicators are calculated, including node degree, betweenness, closeness centrality, eigenvector centrality, and edge betweenness.

3. According to the complex network-based inland waterway network traffic status assessment method of claim 1, it is characterized in that: S2 specifically includes: S21. For nodes, the degree, betweenness, closeness centrality, eigenvector centrality, node flow, node attributes, and node scale of nodes are selected as evaluation indicators to construct a node index system; for edges composed of flight segments, edge betweenness, ship flow, flight segment attributes, and navigation level are selected as evaluation indicators to construct an edge index system; S22. Construct judgment matrices for node and edge indicator systems respectively, and apply analytic hierarchy process to calculate the subjective weight of each evaluation indicator; S23. For the node and edge indicator systems, the entropy weight method is used to obtain the objective weight of each evaluation indicator; S24. The arithmetic mean of the subjective weight and the objective weight is used as the combined weight of each evaluation index; S25. Quantify the weight of each node and edge using the combined weight of the above evaluation indicators, and then set the weight value of each node and edge to be the ratio of the quantized weight value of each node and edge to the sum of the quantized weight values ​​of all nodes and edges.

4. According to the complex network-based inland waterway network traffic status assessment method of claim 1, it is characterized in that: S3 specifically includes: S31. Calculate the segment capacity C within the study time range: Among them, C is the traffic capacity of the section within the study time range; s is the number of ships allowed to sail in parallel in the cross section of the section; t is the navigation time of the section within the study time range; V is the ship operating speed; m is the ship spacing coefficient; L is the ship length; β1 is the speed loss coefficient caused by ship overtaking and passing; β2 is the load reduction coefficient caused by the change of ship draft; β3 is the increase in operating resistance caused by the increase in ship traffic flow density; β4 is the throughput reduction coefficient caused by the imbalance of port arrival and departure and section scheduling; β5 is the average loading factor of the ship; S32. The capacity of a node as a segment intersection within the study time period is the average capacity of the segments connected to it multiplied by the reduction factor; S33. The capacity of a node as an operation area within the research time range is the average capacity of the connected segments multiplied by the reduction factor; S34. The traffic capacity of the nodes serving as ship locks within the research time range is calculated from the annual traffic capacity of the ship locks.

5. The method for evaluating the traffic status of an inland waterway network based on a complex network according to claim 1, characterized in that: S4 specifically includes: S41. For a node, its traffic status index is the ship flow of node i within the study time range and capacity Ratio: S42, for the edge, its traffic state index is the ship flow of segment k within the study time range and capacity Ratio:

6. The method for evaluating the traffic status of an inland waterway network based on a complex network according to claim 1, characterized in that: The evaluation method also includes: S5. Construct a step-by-step calculation model to evaluate the overall traffic status of the inland waterway network, including: S51, overall traffic status index of all nodes n is the total number of nodes; S52, overall traffic status index of all edges 7. A computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, characterized in that: When the instructions are executed by a computing device, the computing device is caused to perform the method according to any one of claims 1 to 6.

8. An electronic device, characterized in that: The method comprises one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method as claimed in any one of claims 1 to 6.

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