Harbor-approaching industry layout system and method based on big data

Abstract

The invention relates to the technical field of data processing systems or methods specially suitable for supervision or prediction purposes, in particular to a port-approaching industry layout system and method based on big data, and the system comprises a recording module, a processing module and an iteration module; the recording module is in data connection with the processing module, the processing module is in data connection with the iteration module, and the iteration module is in data connection with the back-end execution center. Through combination of the recording module, the processing module and the iteration module, reasonable and rapid layout of the traffic industry in the port-approaching industry is realized; and meanwhile, by performing clustering processing on the data, the accuracy of the data is ensured, and the problem of data processing errors of the port-approaching traffic industry is further solved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing systems or methods specifically suitable for monitoring or forecasting purposes, and in particular to a port industry layout system based on big data, and also to a method. Background Art

[0002] Modern ports are transforming from simple cargo transshipment stations to complexes integrating various functions. Due to the geographical location and convenient transportation of ports, a large number of related industries have gathered, forming a port economy centered on port terminals, relying on port cities and economic hinterlands, with port areas as carriers, supported by finance and port-related industries, giving full play to the advantages of port shipping and comprehensive transportation, utilizing port resources, and participating in industrial division of labor and trade exchanges. Reasonable planning of port industry layout can give full play to the advantages of port industries and promote regional economic development. It is conducive to giving full play to the advantages of ports, promoting the industrialization and urbanization process of port cities, giving full play to the advantages of industrial agglomeration, accelerating technological innovation, and achieving intensive growth. Among them, the reasonable layout of port transportation is particularly important.

[0003] In the prior art, the application number is 201910255612.8, the application date is April 1, 2019, and the name is irregular port industrial zone layout system and method based on multi-agent evolutionary algorithm. It discloses a data acquisition unit for acquiring map data of the port industrial zone to be laid out; a rasterization processing unit for rasterizing the area of ​​the port industrial zone; a raster allocation unit for allocating a corresponding number of grids to each port industry according to its planned area and to existing buildings according to their actual area; a model establishment unit, which takes the sum of the correlations between each grid as the comprehensive correlation, and constructs an irregular port industrial layout model with the goal of maximizing the comprehensive correlation of the entire port industrial zone; a model solving unit, which is used to solve the irregular port industrial layout model by a multi-agent evolutionary algorithm, and the result is the port industrial layout plan for the port industrial zone.

[0004] Although the aforementioned technical solution can realize the automatic generation of industrial zone layout plans, it cannot achieve a reasonable layout for the traffic problems in the port area. Summary of the invention

[0005] Through research, the inventor found that the transportation layout construction of port-related industries is conducive to giving full play to the port's locational advantages and competitive advantages, and plays a leading and driving role in the economic development of the region. Since port-related industries are affected by factors such as natural resources, economic conditions, ecological environment, social cooperation, technological level and human capital level, the rationality of the transportation layout will directly affect the regional advantages and economic development.

[0006] The purpose of this application is to provide a port industry layout system and method based on big data, and to solve the technical problem that the prior art cannot provide a system that can quickly and accurately carry out port transportation industry layout through recording modules, processing modules and iteration modules.

[0007] According to one aspect of the present application, there is provided a port industry layout system based on big data, including a recording module for port logistics flow statistics;

[0008] a processing module for performing layout calculations on statistical traffic;

[0009] Iteration module, used to perform information update on the real-time port logistics volume based on the layout calculation results;

[0010] The recording module data is connected to the processing module, the processing module data is connected to the iteration module, and the iteration module data is connected to the backend execution center.

[0011] In some embodiments, the recording module includes a statistical model, which is:

[0012]

[0013] Where T represents the total port traffic; A i Represents the total inbound traffic; A j Represents the total outbound traffic.

[0014] In some embodiments, the processing module includes a calculation model, which is:

[0015]

[0016] Among them, y is the regional flow value; e is the constant of the exponential function; T is the total port flow.

[0017] In some embodiments, the iteration module includes a hierarchical iteration model, which is:

[0018]

[0019] Among them, A c is the total number of incoming traffic after the change; A d is the total outbound traffic after the change; A c standard A is the preset standard port inflow flow number; c standard A is the preset standard outbound flow number; c min is the minimum flow number into the port; A c max is the maximum flow rate into the port; Ad min is the minimum outbound flow number; A d max is the maximum outbound flow; T represents the total port flow after the change; ψ represents the proportion of the total flow after the change.

[0020] In some embodiments, the iteration module further includes a data cleaning unit, and the data cleaning unit performs clustering on the iteratively updated data.

[0021] In some embodiments, the clustering includes at least a K-Means algorithm.

[0022] According to another aspect of the present application, a method for port industry layout based on big data is provided, the method being executed by a processor and comprising:

[0023] Obtain past port logistics flow data;

[0024] Perform layout and calculation on past port logistics flow data;

[0025] Combine the layout and calculation results with the real-time logistics volume of the port, update the logistics volume data, and obtain layout guidance information.

[0026] In some embodiments, the layout guidance information includes at least traffic layout information.

[0027] Compared with the prior art, the present application has the following advantages and beneficial effects: by combining the recording module, the processing module and the iteration module, the present application realizes the reasonable and rapid layout of the transportation industry in the port industry; at the same time, by performing clustering processing on the data, the accuracy of the data is ensured, and the problem of data processing errors in the port transportation industry is further solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 It is a schematic diagram of the layout system structure of this application;

[0030] Figure 2 It is a flow chart of the layout method of this application. DETAILED DESCRIPTION

[0031] The following will be combined with the attached examples of the present application Figure 1-2The technical solutions in the embodiments of the present application are clearly and completely described together. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0032] Application Overview

[0033] As scarce and strategic resources that support regional economic and transportation development, port resources need to be planned in an orderly manner, optimize functional configuration, improve utilization efficiency, tap development potential, and effectively guide the high-quality, healthy, and sustainable development of ports. Modern ports are transforming from simple cargo transshipment stations to complexes that integrate various functions. Due to the geographical location and convenient transportation of ports, a large number of related industries have gathered, creating a port economy centered on port terminals, relying on port cities and economic hinterlands, with port areas as carriers, and supported by finance and port-related industries. It takes advantage of port shipping and comprehensive transportation, utilizes port resource endowments, and participates in industrial division of labor and trade exchanges. Reasonable planning of port industry layout can give play to the advantages of port industries, accelerate technological innovation, and achieve intensive growth. Among them, the reasonable layout of port transportation is an especially important part of achieving the above content.

[0034] This application realizes the rational layout of the transportation industry in the port industry and improves the comprehensive transportation capacity of the port through the coordination between the recording module, the processing module and the iteration module, that is, through the rapid and accurate processing of the port traffic data through the statistical model, the calculation model and the hierarchical iteration model.

[0035] In order to better understand this application, some of the contents in this application are now explained:

[0036] Logistics flow: In this implementation, it refers to the traffic flow in the port area. In other situations, it can also refer to the flow of products in the area.

[0037] The present embodiment provides a port industry layout system based on big data, and the system includes: a recording module for port logistics flow statistics, a processing module for performing layout calculations on statistical flows, and an iteration module for performing information updates on real-time port logistics flows based on layout calculation results, wherein the recording module data is connected to the processing module, the processing module data is connected to the iteration module, and the iteration module data is connected to the backend execution center. In detail, the recording module in the present embodiment will record the previous port logistics flow data to form a data set. The data set will be input into the processing module to perform data calculations. After the data calculations, the regional flow value-added of the corresponding port area will be obtained. The regional flow value-added is input into the iteration module to calculate the proportion of the total flow after iteration. After the proportion data is obtained, the transportation industry layout mode of the port area is judged and analyzed according to the proportion data.

[0038] In some possible implementations, the recording module includes a statistical model, which is:

[0039]

[0040] Where T represents the total port traffic; A i Represents the total inbound traffic; A j Represents the total outbound traffic.

[0041] In some possible implementations, the processing module includes a calculation model, which is:

[0042]

[0043] Among them, y is the regional flow value; e is the constant of the exponential function; T is the total port flow.

[0044] In some possible implementations, the iteration module includes a hierarchical iteration model, which is:

[0045]

[0046] Among them, A c is the total number of incoming traffic after the change; A d is the total outbound traffic after the change; A c standard A is the preset standard port inflow flow number; c standard A is the preset standard outbound flow number; c min is the minimum flow number into the port; A c max is the maximum flow rate into the port; A d min is the minimum outbound flow number; A d max is the maximum outbound flow; T represents the total port flow after the change; ψ represents the proportion of the total flow after the change.

[0047] In some possible implementations, the iteration module further includes a data cleaning unit, and the data cleaning unit performs clustering on the iteratively updated data, and the clustering includes at least a K-Means algorithm.

[0048] In order to better connect the system of this embodiment, it should be noted that the statistical model in the recording module will record the traffic data in the target port area in the past, and obtain the total port traffic A i and the total outbound traffic A j, brought into the model to obtain the total port flow T. Next, the calculation model in the processing module will bring the total port flow T into the model to calculate the regional flow value y, where the regional flow value y represents the traffic flow data of the target port area. Further, the regional flow value y is brought into the hierarchical iteration model in the iteration module to calculate the proportion of the total flow after the iteration ψ. It should be noted here that the data in the hierarchical iteration model is the real-time flow data of the target port after data cleaning, and the flow data at least includes the data of cargo ships entering and leaving the port.

[0049] In some possible implementations, the data cleaning unit performs cleaning on the iteratively updated data by data clustering, classifies the data attributes, and eliminates interference data, wherein clustering includes at least a K-Means algorithm, and an agglomerative hierarchical clustering algorithm may also be used.

[0050] Exemplarily, the computer program can be divided into one or more modules, one or more modules are stored in the memory and executed by the processor to complete the present invention. One or more modules can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the system. For example, the computer program can be divided into a recording module, a processing module and an iteration module, and the specific functions of each module are as follows: a recording module for port logistics flow statistics; a processing module for performing layout calculations on the statistical flow; an iteration module for performing information updates on the real-time logistics volume of the port based on the layout calculation results. The system may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that the schematic diagram is only an example of the system and does not constitute a limitation on the system.

[0051] Exemplary Methods

[0052] A method for the layout of Lingang industries based on big data, which is executed by a processor. It is understandable that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The processor is the control center of the system, and various interfaces and lines are used to connect various parts of the entire system.

[0053] In detail, past port logistics flow data are obtained; layout and calculation are performed on past port logistics flow data; based on the layout and calculation results, the port logistics flow data is updated in combination with the real-time port logistics flow, and layout guidance information is obtained.

[0054] In some possible implementations, the layout guidance information at least includes traffic layout information.

[0055] Based on the above, the method of this implementation is now described in detail as follows. The processor obtains past port logistics flow data by executing the recording module, performs layout and calculation on the past port logistics flow data on the processing module, and executes the update of the port logistics flow data based on the layout and calculation results combined with the real-time port logistics volume on the iteration module to obtain layout guidance information. After executing the above steps, the layout of the port transportation industry can be quickly realized. It can be understood that the transportation industry in this embodiment at least includes the data of cargo ships entering and leaving the port.

[0056] The above shows and describes the basic principles, main features and advantages of the present application. For those skilled in the art, it is obvious that the present application is not limited to the details of the above-mentioned exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or basic features of the present application.

[0057] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present application is limited by the appended claims rather than the above description, so it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the present application. Any reference sign in the claims should not be regarded as limiting the claims involved.

[0058] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A port industry layout system based on big data, characterized in that: include: Recording module, used for port logistics flow statistics; a processing module for performing layout calculations on statistical traffic; Iteration module, used to perform information update on the real-time port logistics volume based on the layout calculation results; The recording module data is connected to the processing module, the processing module data is connected to the iteration module, and the iteration module data is connected to the backend execution center.

2. The system according to claim 1, characterized in that The recording module includes a statistical model, which is: Where T represents the total port traffic; A i Represents the total inbound traffic; A j Represents the total outbound traffic.

3. The system according to claim 1, characterized in that The processing module includes a calculation model, which is: Among them, y is the regional flow value; e is the constant of the exponential function; T is the total port flow.

4. The system according to claim 1, characterized in that The iteration module includes a hierarchical iteration model, which is: Among them, A c is the total number of incoming traffic after the change; A d is the total outbound traffic after the change; A c standard A is the preset standard port inflow flow number; c standard A is the preset standard outbound flow number; c min is the minimum flow number into the port; A c max is the maximum flow rate into the port; A d min is the minimum outbound flow number; A d max is the maximum outbound flow; T represents the total port flow after the change; ψ represents the proportion of the total flow after the change.

5. The system according to claim 1, characterized in that The iteration module also includes a data cleaning unit, which performs clustering on the iteratively updated data.

6. The system according to claim 5, characterized in that The clustering includes at least a K-Means algorithm.

7. A method for port industry layout based on big data, the method being executed by a processor, characterized in that: include: Obtain past port logistics flow data; Perform layout and calculation on past port logistics flow data; Combine the layout and calculation results with the real-time logistics volume of the port, update the logistics volume data, and obtain layout guidance information.

8. The method according to claim 7, characterized in that The layout guidance information at least includes traffic layout information.

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