CN112016730A - Port berth loading and unloading efficiency excavating method, device, equipment and storage medium - Google Patents
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Abstract
The application discloses a digging method, a digging device, digging equipment and a digging storage medium for port berth loading and unloading efficiency. The method comprises the following steps: acquiring at least one piece of ship basic information, wherein each piece of ship basic information comprises historical ship draft data, a ship model, and maximum draft data and maximum load data corresponding to the ship model; inputting at least one historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a ship berthing at a port berth, the cargo handling capacity being a capacity of cargo loaded or unloaded by the ship berthing at the port berth; acquiring the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount; the loading and unloading efficiency of the port berth is calculated based on the maximum cargo loading and unloading amount and the minimum ship berthing time. The method and the device reduce the difficulty of digging the port berth loading and unloading efficiency and improve the accuracy of digging the port berth loading and unloading efficiency information.
Description
Technical Field
The application relates to the field of big data analysis, in particular to a method, a device, equipment and a storage medium for digging loading and unloading efficiency of a port berth.
Background
With the increasing closeness of international trade, marine transportation is an important way to transport goods, and the role played in international trade is more and more important.
In a marine transportation network, a port is an important hub node, and in a port operation system, a berth is the most basic working unit of the port. The level of the port berth loading and unloading efficiency reflects the level of the infrastructure construction, resource allocation and operation management of the port from the side, so that the acquisition of the port berth loading and unloading efficiency information has important significance.
However, the port berth loading and unloading efficiency information belongs to the private information of the port and is generally not disclosed to the outside, so that the difficulty in obtaining the port berth loading and unloading efficiency is high; or, even if the port operator wants to disclose the port berth loading and unloading efficiency, it is difficult to effectively exploit the port berth loading and unloading efficiency because the information is mainly collected by manpower and the information sources are limited.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies in the prior art, it is desirable to provide a method, an apparatus, a device, and a storage medium for digging port berth loading and unloading efficiency that reduce the digging difficulty of port berth loading and unloading efficiency and improve the accuracy of digging port berth loading and unloading efficiency information.
In a first aspect, an embodiment of the present application provides a method for digging loading and unloading efficiency of a port berth, where the method includes:
acquiring at least one piece of ship basic information, wherein each piece of ship basic information comprises historical ship draft data, a ship model, and maximum draft data and maximum load data corresponding to the ship model;
inputting at least one historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a ship berthing at a port berth, the cargo handling capacity being a capacity of cargo loaded or unloaded by the ship berthing at the port berth;
acquiring the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount;
the loading and unloading efficiency of the port berth is calculated based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
In a second aspect, an embodiment of the present application provides a digging device for loading and unloading efficiency of a port berth, including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is configured to acquire at least one piece of ship basic information, and each piece of ship basic information comprises historical ship draft data, a ship model, and maximum draft data and maximum load data corresponding to the ship model;
a first determination module configured to input at least one historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a berthing ship at a port berth, the cargo handling capacity being an amount of cargo loaded or unloaded by the berthing ship at the port berth;
a second acquisition module configured to acquire a minimum ship berthing time corresponding to a maximum cargo handling amount;
a calculation module configured to calculate a loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
In a third aspect, an embodiment of the present application provides a computer device, including:
a processor;
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the port berth handling efficiency excavation method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having instructions stored therein, which when run on a processing component, cause the processing component to perform the method for digging efficiency of loading and unloading a port berth as in the first aspect.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
according to the method, the device, the equipment and the storage medium for excavating the loading and unloading efficiency of the port berth, the maximum cargo loading and unloading amount of the ship berthed at the port berth can be determined based on at least one ship draft data in the basic information of at least one ship and a pre-constructed cargo estimation model, the minimum ship berthing time of the ship corresponding to the maximum cargo loading and unloading amount is obtained, the loading and unloading efficiency of the port berth is calculated based on the maximum cargo loading and unloading amount and the minimum ship berthing time, and the excavation of the loading and unloading efficiency information of the port berth is realized.
And determining the geographic range of the port berth based on the acquired global ship track data and port range data, establishing the corresponding relation among the port berth, the geographic range and the loading and unloading efficiency, and improving the informatization level of the port berth.
And the port berth loading and unloading efficiency can be updated after the preset time, so that the accuracy of the obtained port berth loading and unloading efficiency is improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a flowchart illustrating a method for digging loading and unloading efficiency of a port berth according to an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating another method for digging loading and unloading efficiency of a port berth according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an excavating device for loading and unloading efficiency of a port berth according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of another digging device for loading and unloading efficiency of a harbor berth according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computer system according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The port is used as an important hub node in a marine transportation network, and the operation capacity of a port operation system is an important index for determining the core competitiveness of the port. The operation capability of a port operation system is known, for a port, the advantages and the disadvantages of the port can be clarified, the strengthening infrastructure and the information construction of the port are promoted, the operation and service level is improved, and more potential customers are attracted; for the freight forwarder, the freight forwarder can conveniently select a proper consignment port, and the freight cost is reduced.
In a port operation system, an important index for measuring port operation capacity is the loading and unloading efficiency of a port berth, wherein the berth refers to the berthing position of a ship in a port and is the most basic working unit of the port, and the loading and unloading efficiency of the port berth refers to the ratio of the maximum cargo loading and unloading amount of the ship which can be carried by a certain berth to the minimum ship berthing time of the ship corresponding to the maximum cargo loading and unloading amount.
In the related art, the loading and unloading efficiency information of the port berth can be collected manually, but the manually collected loading and unloading efficiency of the port berth is derived from data reported by each port, and the loading and unloading efficiency information of the port berth belongs to private information of the port, so that all the loading and unloading efficiency information of the port berth cannot be collected; and because the port berth loading and unloading efficiency is estimated based on the port infrastructure, no unified standard data exists. Therefore, when the port berth loading and unloading efficiency collected manually is subjected to statistical analysis, the port berth loading and unloading efficiency is difficult to effectively dig due to the fact that data sources and data quality are difficult to guarantee.
The embodiment of the application provides a method for excavating the loading and unloading efficiency of port berths, which can solve the problem that the information of the loading and unloading efficiency of the port berths is difficult to obtain. As shown in fig. 1, the method includes:
In this step, the ship basic information includes historical ship draft data and ship profile information, and the ship profile information may include a ship model, maximum draft data corresponding to the ship model, and maximum load data. Wherein the historical ship draft data represents a set of draft data when the ship enters a berth and draft data when the ship leaves the berth in each berthing behavior of the ship at a port berth in a specific time period, and the draft data when the ship enters the port berth is generally as follows: during the voyage of the ship entering the port berth, the draft data of the latter half is concentrated with the draft data with higher frequency; draft data when the ship leaves a port berth is generally: during the voyage of the ship leaving the port berth, the draft data of the latter half is concentrated with the draft data with higher frequency; the maximum draft data and the maximum load data corresponding to the ship model are the maximum draft data and the maximum load data of different ships in a theoretical state.
At least one historical ship draft data is input into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a berthing ship at a port berth, step 102.
In this step, the cargo estimation model is used to represent the relation between the draft data of the ship and the actual cargo capacity of the ship, and the actual cargo capacity of the ship can be determined based on the cargo estimation model and the acquired historical ship draft data.
And 103, acquiring the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount.
In this step, the minimum ship berthing time is the time difference between the arrival and departure of the ship at the port berth.
And step 104, calculating the loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
In summary, the method for mining the loading and unloading efficiency of the port berth according to the embodiment of the present application may determine the maximum cargo loading and unloading amount of the ship berthed at the port berth based on at least one ship draft data in at least one piece of ship basic information and a pre-constructed cargo estimation model, obtain the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount, and calculate the loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time. The digging of the loading and unloading efficiency information of the harbor berth is realized, and the informatization level of the harbor is improved.
The method for excavating the loading and unloading efficiency of the harbor berth, provided by the embodiment of the application, can be applied to mobile terminal equipment (such as a smart phone, a tablet personal computer and the like) and can also be applied to a fixed terminal (a desktop computer) or a server.
As shown in fig. 2, the digging method of the loading and unloading efficiency of the port berth provided by the embodiment of the application includes:
and step 201, identifying the berthing behavior of the ship at the port according to the acquired global ship track data and the port range data.
In the embodiment of the application, the ship track data can be acquired based on various means such as an Automatic Identification System (AIS) for a ship, a radar, a Beidou, a Global Positioning System (GPS for a short), and the like, and the ship track data of different layers and different characteristics can be acquired by using the various means, and the ship track data can be effectively fused by processing such as Identification, detection, tracking, association, estimation and the like of the ship track data, so that the accuracy of the finally acquired ship track data is improved. Meanwhile, port range data may be mined based on the ship trajectory data and port midpoint location data.
Further, determining the port berthing behavior of the ship according to the acquired global ship track data and the port range data comprises the following steps: acquiring global ship track data, and preprocessing the global ship track data; according to the preprocessed global ship track data and port range data, identifying the ship in-port or non-in-port behaviors; and carrying out harbor berthing behavior identification on the harbor data. Wherein the global ship track data preprocessing comprises but is not limited to at least one of the following: data fusion, data correction, data filtering and data sorting.
In the embodiment of the present application, the process of determining the geographic range of the port berth may be implemented by the following steps 2021 to 2022.
Step 2021, performing cluster analysis on the berth data formed by the harbor berthing behavior to obtain harbor berthing behavior points.
In this step, a clustering algorithm may be used to perform clustering analysis on the berth data formed by the port berthing behavior to obtain the port berthing behavior points of the ship. Wherein the berthing behavior refers to the behavior of a ship entering a port berth and leaving the port berth. Optionally, the Clustering algorithm may be a Density-Based Clustering algorithm (English: Density-Based Spatial Clustering of Applications with Noise, abbreviated as DBSCAN). Specifically, the DBSCAN algorithm may be used to cluster the berth data to obtain a plurality of classification results, where the classification results include a core point set, an edge point set, and a noise point set, where the core point set is an in-port berthing behavior point. Wherein, the radius threshold value of the DBSCAN algorithm is 20 meters, and the density threshold value is 50.
Step 2022, performing convex hull operation on the identified port berthing behavior points, and determining the geographic range of port berths by combining the ship attribute information.
Specifically, convex hull operation is performed on the identified harbor berthing behavior points, boundary points of the convex hull are obtained according to the operation result, object range data of the convex hull are generated according to the boundary points, and finally the center point of the object is obtained. And further determining a rectangular area by combining ship attribute information such as the ship length, the ship width, the ship orientation and the like of the ship berthed at the berthing behavior point, wherein the rectangular area is the geographic range of port berths.
It should be noted that, since there is no clear boundary between port berths, there may be an intersection of range data of a plurality of port berths acquired based on attribute information of different ships. Therefore, the method of the embodiment of the application can also carry out merging processing on the berth range data so as to reduce the data volume of the port berth geographic range data and facilitate data processing. Specifically, the process of merging the berth range data includes: if the two berth geographic ranges in any port have the intersection area, and the intersection area is larger than the preset threshold value, merging the two berths, and updating the original berth geographic range. Optionally, the preset threshold may be: the intersection area of two berths is 80% of the area of either berth.
Furthermore, in order to ensure the accuracy of the port berth geographic range data, the port berth geographic range data can be periodically updated. For example, the obtained port berth geographic range data may be updated once every three months, and the updating method may refer to the above step 201 to step 202, which is not described in detail in this embodiment of the present application.
Optionally, in this application, a one-to-one correspondence relationship between the port berth and the geographic range data thereof may be established based on the port berth geographic range data acquired in the above-mentioned steps 2021 to 2022, so as to facilitate consulting and saving the port berth geographic range. For example, a port berth geographical range table as shown in table 1 may be established, where table 1 includes the number of port berths and geographical range data, where the port berths are generally rectangular areas, and the geographical range data is a data set composed of the positions of four vertices of the rectangular areas.
TABLE 1
In the embodiment of the application, the ship basic information comprises historical ship draft data and ship profile information, and the ship profile information refers to basic attribute information of a ship.
Wherein, this boats and ships archives information can include information such as boats and ships model, boats and ships length, boats and ships width, the biggest draft data and the biggest load data that correspond with this boats and ships model. The maximum draft data and the maximum load data corresponding to the ship model are the maximum draft data and the maximum load data of different ships in a theoretical state. Optionally, the ship profile information may be obtained based on a lawyer ship profile, which is an internationally recognized provider of basic attribute information of ships with higher authority.
The historical ship draft data represents the set of draft data when the ship enters the port berth and draft data when the ship leaves the port berth in each berthing behavior of the port berth in a specific period of time, and the draft data when the ship enters the port berth is generally as follows: during the voyage of the ship entering the port berth, the draft data of the latter half is concentrated with the frequently higher draft data, and the draft data when the ship leaves the port berth is generally: during the voyage of the ship leaving the port berth, the draft data of the latter half is concentrated with the draft data with higher frequency. Wherein the specific time period may be determined based on actual demand. Illustratively, the particular time period may be 3 years.
It should be noted that, since the historical ship draft data is acquired based on the ship draft data reported by the AIS, and there may be a certain error or delay when the AIS reports the data, the draft data with higher frequency in the second half draft data set of the ship entering the port berth and leaving the port berth are respectively used as the historical ship draft data of the ship entering the port berth and leaving the port berth, so that the acquired error of the historical ship draft data when the ship leaves or enters the port berth can be reduced, and the reliability of the acquired historical ship draft data is improved.
Optionally, in this step, the acquired ship profile information may have an incomplete phenomenon, and in order to ensure the integrity of the ship profile information, the ship profile information may be supplemented based on a machine learning algorithm to obtain more complete ship profile information. The ship file information supplementing process may be: aiming at the ship with missing ship file information, based on a machine learning algorithm, the missing ship file information is predicted by utilizing the known ship file information of the ship, the prediction result is used as supplementary information, and the ship file information of the ship is completely supplemented by utilizing the supplementary information. Alternatively, the machine learning algorithm may be a nearest neighbor algorithm or a random forest algorithm.
At least one historical ship draft data is input to a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a berthing ship at a port berth, step 204.
Before determining the maximum cargo handling capacity of a vessel berthed at a port berth, a cargo estimation model needs to be constructed, which can be constructed based on vessel basic information. Optionally, the ship basic information may be ship basic information of a global ship acquired in a specific period. The process of constructing the cargo estimation model includes: the method comprises the steps of obtaining a sample set formed by maximum load data, maximum draft data and draft data of a plurality of ships in an idle state, and training and learning according to a machine learning algorithm or a deep learning algorithm to establish a mapping relation between the draft data and the ship load data, wherein the mapping relation is a cargo estimation model.
Wherein draft data of the ship in an unloaded state can be determined based on the ship model, the maximum draft data of the ship and historical draft data of the ship, and the process comprises the following steps:
and step S11, calculating first no-load draft data based on the ship model and the maximum draft data of the ship.
In this step, for each ship, a first no-load draft data of the ship may be calculated by using a ship no-load draft data calculation formula based on a ship model of the ship and a maximum draft data corresponding to the ship model, where the first no-load draft data is theoretical draft data of the ship when the ship is no-load. Wherein the calculation formula of the no-load draught data of the ship is as follows,
wherein, TmaxThe values of α and β are determined based on the vessel type for maximum draft data. Optionally, if the ship type is an oil tanker, the values of α and β are 0.548 and 0.966, respectively; if the ship type is a bulk cargo ship, the values of alpha and beta are 0.551 and 0.993 respectively; for other types of vessels, the values of α and β are 0.352 and 1.172, respectively.
And step S12, determining draft data of the ship in an unloaded state based on the historical draft data and the first unloaded draft data of the ship model.
In this step, based on the historical ship draft data of each ship, it is determined whether the historical ship draft data has a value of [ 0.8 × T [ ]B，1.2×TBDetermining the minimum data with the maximum occurrence frequency in the range as the draft data of the ship in an idle state if the data exists in the range; and if not, determining the first idle draft data as draft data of the ship in an idle state.
The draft data of the ship in the no-load state is determined by correcting based on actual historical draft data of the ship and theoretical draft data of the ship in the no-load state, so that the finally determined draft data of the ship in the no-load state is more in line with the actual situation. Furthermore, the cargo estimation model established based on the draft data of the ship in the no-load state also has higher accuracy and actual reference value.
In the embodiment of the present application, the vessel basic information of at least one vessel berthing at the same port berth for a certain period of time may be acquired, and the process of determining the maximum cargo handling amount of the vessel berthed at the port berth may include: and further, determining the maximum cargo handling capacity of the ship berthed at the port berth based on the actual cargo handling capacity of the ship and the maximum load data of the ship. Wherein the cargo handling capacity is the amount of cargo that is loaded or unloaded by berthing the vessel at a port berth.
Optionally, the process of determining the maximum cargo handling capacity of a vessel berthed at a port berth may include at least the following two alternative realizations:
in a first alternative implementation, when only one vessel is berthed at the port berth, determining the maximum cargo handling capacity of the berthed vessel at the port berth includes:
step S21, inputting the historical ship draft data into a pre-constructed cargo estimation model to determine the actual cargo handling capacity of the ship corresponding to the historical ship draft data.
In the step, based on the acquired historical ship draft data when the ship enters the port berth, the historical ship draft data is input into a pre-constructed cargo estimation model, and the first cargo capacity of the ship is determined; based on the acquired historical ship draft data when the ship leaves the port berth, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a second cargo capacity of the ship; further, an actual cargo handling amount of the ship is determined based on the first cargo carrying amount and the second cargo carrying amount, and the actual cargo handling amount is a difference value of the first cargo carrying amount and the second cargo carrying amount.
Step S22 is to determine the maximum cargo handling amount of the ship berthed at the port berth based on the actual cargo handling amount of the ship and the maximum load data of the ship.
In this step, the maximum cargo handling amount of the ship berthed at the port berth may be determined by determining whether the actual cargo handling amount of the ship determined in the above-described step S21 is greater than or equal to a threshold cargo handling amount of the ship, which is 0.9 times the maximum load data of the ship. Optionally, if the actual cargo handling capacity of the ship is greater than or equal to the threshold cargo handling capacity of the ship, determining the actual cargo handling capacity of the ship as the maximum cargo handling capacity of the ship berthed at the port berth; and if the actual cargo handling capacity of the ship is smaller than the threshold value of the cargo handling capacity of the ship, filtering the actual cargo handling capacity of the ship.
For example, assume a berth A of a port berthing within three years1The ship is B1The ship B in three years can be acquired based on the basic ship information1Historical ship draft data C1And maximum load data E1。
Further, it may be based on ship B1Historical ship draft data C1And a cargo estimation model, determining the ship B1At port berth A1The actual cargo handling at berthing is D1And determining the actual cargo handling amount D1Maximum load data E greater than ship10.9 times of the total number of the parking spaces, determining the berth A at the port1The maximum cargo handling capacity of the berthed vessel is D1。
In a second alternative implementation, when a plurality of vessels are berthed at the port berth, determining the maximum cargo handling capacity of the vessels berthed at the port berth includes: acquiring a plurality of ship basic information of ships berthing at the port berth, respectively inputting each historical ship draft data into a pre-constructed cargo estimation model to determine the actual cargo handling capacity of each ship corresponding to each historical ship draft data, and further determining the maximum cargo handling capacity of the ships berthing at the port berth based on the actual cargo handling capacity of each ship and the corresponding maximum load data.
The method for acquiring the actual cargo handling capacity of each ship may include: acquiring historical ship draft data when a ship enters a port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a first cargo capacity of the ship; acquiring historical ship draft data when the ship leaves a port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a second cargo capacity of the ship; and determining the actual cargo handling capacity of each ship based on the first cargo carrying capacity and the second cargo carrying capacity, wherein the actual cargo handling capacity is the difference value of the first cargo carrying capacity and the second cargo carrying capacity.
The process of determining the maximum cargo handling capacity of a vessel berthed at a port berth may include: judging whether the actual cargo handling capacity of each ship is larger than or equal to a cargo handling capacity threshold value of the ship or not; determining the actual cargo handling capacity of the at least one vessel as the maximum cargo handling capacity of the vessel berthing at the port berth if there is at least one vessel having an actual cargo handling capacity greater than or equal to a threshold cargo handling capacity of the vessel; and if the actual cargo handling capacity of the ship is smaller than the threshold value of the cargo handling capacity of the ship, filtering the actual cargo handling capacity of the ship.
Alternatively, when there are multiple vessels berthing at the port berth, the process of determining the maximum cargo handling capacity of the vessels berthed at the port berth may be at least one of the following three alternative implementations:
in a first alternative implementation, if there is no ship in the plurality of ships whose actual cargo handling capacity is greater than or equal to the threshold cargo handling capacity of the ship, the actual cargo handling capacity of the plurality of ships is filtered out.
In a second alternative implementation, if the actual cargo handling capacity of one of the plurality of vessels is greater than or equal to the threshold cargo handling capacity of the vessel, the actual cargo handling capacity of the vessel is determined as the maximum cargo handling capacity of the vessel berthed at the port berth.
In a third alternative implementation, if the actual cargo handling capacity of the plurality of vessels is greater than or equal to the cargo handling capacity threshold of the corresponding vessel, the actual cargo handling capacity of the plurality of vessels is determined as the maximum cargo handling capacity of the vessel berthed at the port berth.
For example, assume a berth A of a port berthing within three years1The ship has a ship B1、B2、B3And B4The ship B in three years can be acquired based on the basic ship information1、B2、B3And B4Respective historical ship draft data C1、C2、C3And C4And maximum load data E1、E2、E3And E4。
Further, it may be based on ship B1、B2、B3And B4Historical ship draft data C1、C2、C3And C4And a cargo estimation model, determining the ship B1、B2、B3And B4At port berth A1The actual cargo handling capacity at the time of parking is D1、D2、D3And D4And determining the actual cargo handling amount D1、D2And D4Maximum load data E greater than respective ship1、E2And E40.9 times of the total number of the parking spaces, determining the berth A at the port1The maximum cargo handling capacity of the berthed vessel is D1、D2And D4。
In this step, when only one ship is berthed at the port berth and the actual cargo handling amount of the ship is greater than or equal to the cargo handling amount threshold value of the ship, the berthing time of the ship at the port berth is determined as the minimum ship berthing time.
Determining the berthing time of the ship at the port berth as the minimum ship berthing time when a plurality of ships are berthed at the port berth and the actual cargo handling amount of only one ship in the plurality of ships is greater than or equal to the cargo handling amount threshold value of the ship; or, if the actual cargo handling amount of a plurality of the plurality of ships is greater than or equal to the cargo handling amount threshold value of the corresponding ship, determining the minimum value of the plurality of ship berthing times as the minimum ship berthing time.
Illustratively, at port berth A1Berthing vessel B1、B2、B3And B4Middle, ship B1、B2And B4Actual cargo handling capacity D1、D2And D4Maximum load data E greater than respective ship1、E2And E40.9 times of, and ship B2At port berth A1At a parking time t2Are all smaller than the ship B1And B4Parking time t1And t4And the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount is t2。
It should be noted that, in the embodiment of the present application, the obtained ship berthing time may be screened based on actual experience to filter time data with errors, so as to improve the reliability of the obtained minimum ship berthing time. By way of example, the screening method may be: assuming that a ship having an actual cargo handling capacity of 20 tons is generally parked at a port berth for 12 hours to 24 hours, if a ship having an actual cargo handling capacity of 20 tons is obtained and is parked at a port berth for 2 hours, it is possible to determine the parking time data as error data and filter the parking time data of the ship.
And step 206, calculating the loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
In this step, the ratio of the maximum cargo handling amount to the minimum ship berthing time is taken as the handling efficiency of the port berth based on the determined minimum ship berthing time and the maximum cargo handling amount of the ship corresponding to the minimum ship berthing time.
Illustratively, at port berth A2Of a plurality of berthing vessels, for a berthing time t2Is the minimum ship berthing time t2Corresponding ship B2The actual cargo handling amount of (D) is the maximum cargo handling amount2Then load and unload the maximum cargo by the amount D2With the minimum ship berthing time t2Ratio v of2As the port berth A2The loading and unloading efficiency of (1).
It should be noted that the digging method of the loading and unloading efficiency of the port berth provided in the above steps 203 to 206 is a realizable method provided for one port berth, and the digging method of the loading and unloading efficiency of other port berths may refer to the above steps 203 to 206, which is not described in detail in this embodiment of the present application.
And step 207, establishing a corresponding relation between the port berth geographic range and the port berth loading and unloading efficiency.
In this embodiment, the loading and unloading efficiencies of a plurality of port berths may be obtained based on the digging method of the port berth loading and unloading efficiency provided in the above steps 203 to 206, and further, a one-to-one correspondence relationship among the port berths, the geographic range, and the loading and unloading efficiency may be established in combination with the geographic range data of the plurality of port berths, so as to improve the informatization level of the port berths.
For example, a port berth loading and unloading efficiency table as shown in table 2 may be established, the table 2 including port berth numbers, geographical range data, and loading and unloading efficiency, wherein the unit of the loading and unloading efficiency may be ton/hour (t/h).
TABLE 2
And step 208, updating the loading and unloading efficiency of the port berth after preset time, wherein the preset time is determined based on actual needs.
In order to ensure the accuracy of the obtained port berth loading and unloading efficiency, the basic data of the ship berthed at the port berth can be updated after the preset time, and the loading and unloading efficiency of the port berth is further updated based on the digging method of the port berth loading and unloading efficiency provided in the steps 203 to 207. Wherein the preset time may be determined based on actual needs. For example, the preset time is half a month.
To sum up, the method for mining the loading and unloading efficiency of the port berth provided by the embodiment of the application can determine the geographic range of the port berth based on the acquired global ship track data and the port range data, further determine the maximum cargo loading and unloading amount of the ship berthed at the port berth based on at least one ship draft data in the basic information of at least one ship and a pre-constructed cargo estimation model, acquire the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount, calculate the loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time, realize the mining of the loading and unloading efficiency information of the port berth, establish the corresponding relation among the port berth, the geographic range and the loading and unloading efficiency, and improve the informatization level of the port berth. And the port berth loading and unloading efficiency can be updated after the preset time, so that the accuracy of the obtained port berth loading and unloading efficiency is improved.
The embodiment of the present application provides a digging device for loading and unloading efficiency of a port berth, as shown in fig. 3, the digging device 30 includes:
a first obtaining module 301 configured to obtain at least one piece of ship basic information, each piece of ship basic information including historical ship draft data, a ship model, maximum draft data corresponding to the ship model, and maximum load data;
a first determining module 302 configured to input at least one historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a berthing ship at a port berth, the cargo handling capacity being an amount of cargo loaded or unloaded by the berthing ship at the port berth;
a second acquisition module 303 configured to acquire a minimum ship berthing time corresponding to a maximum cargo handling amount;
a calculation module 304 configured to calculate a loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
Optionally, the first determining module 302 is configured to:
inputting the draft data of each historical ship into a pre-constructed cargo estimation model respectively to determine the actual cargo handling capacity of the ship corresponding to the draft data of the historical ship;
the maximum cargo handling capacity of a vessel berthing at a port berth is determined based on actual cargo handling capacity of the vessel and maximum load data of the vessel.
Optionally, the first determining module 302 is configured to:
acquiring historical ship draft data when a ship enters a port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a first cargo capacity of the ship;
acquiring historical ship draft data when the ship leaves a port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a second cargo capacity of the ship;
and determining the actual cargo handling capacity of the ship based on the first cargo carrying capacity and the second cargo carrying capacity, wherein the actual cargo handling capacity is the difference value of the first cargo carrying capacity and the second cargo carrying capacity.
Optionally, the first determining module 302 is configured to:
judging whether the actual cargo handling capacity of each ship is larger than or equal to a cargo handling capacity threshold value of the ship, wherein the cargo handling capacity threshold value of the ship is 0.9 times of the maximum load data of the ship;
determining the actual cargo handling capacity of the at least one vessel as the maximum cargo handling capacity of the vessel berthing at the port berth if there is at least one vessel having an actual cargo handling capacity greater than or equal to a threshold cargo handling capacity of the vessel;
and if the actual cargo handling capacity of the ship is smaller than the threshold value of the cargo handling capacity of the ship, filtering the actual cargo handling capacity of the ship.
Optionally, the first determining module 302 is configured to:
training and learning according to a machine learning algorithm or a deep learning algorithm by using a sample set consisting of the maximum load data, the maximum draft data and the draft data of the ship in an idle state, so as to establish a mapping relation between the draft data of the ship and the load data of the ship, wherein the mapping relation is used as a cargo estimation model.
Optionally, the first determining module 302 is configured to:
calculating first no-load draft data based on the ship model and the maximum draft data of the ship;
and determining draft data of the ship in an unloaded state based on the historical ship draft data and the first unloaded draft data of the ship model.
Optionally, as shown in fig. 4, the apparatus 30 further includes:
an identification module 305 configured to identify a berthing behavior of the ship at the port according to the acquired global ship trajectory data and the port range data;
a second determining module 306 configured to determine a port berth geographic range according to the berthing behavior and the ship attribute information;
the establishing module 307 is configured to establish a corresponding relationship between the port berth geographic range and the port berth loading and unloading efficiency.
In summary, according to the digging device of port berth loading and unloading efficiency provided by the embodiment of the application, the identification module can identify the berthing behavior of the ship at the port based on the acquired global ship track data and port range data, the second determination module can determine the geographic range of the port berth based on the berthing behavior and the ship attribute information, the first acquisition module can acquire at least one ship draught data based on the basic file of at least one ship, the first determination module can determine the maximum cargo loading and unloading amount of the ship based on at least one ship draught data and a pre-constructed cargo estimation model, the second acquisition module can acquire the minimum ship berthing time of the ship corresponding to the maximum cargo loading and unloading amount, the calculation module can calculate the port loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time, and realize the digging of the berth loading and unloading efficiency information, furthermore, the establishing module can establish the corresponding relation among the port berth, the geographic range and the loading and unloading efficiency, and improve the informatization level of the port berth. And the port berth loading and unloading efficiency can be updated after the preset time, so that the accuracy of the obtained port berth loading and unloading efficiency is improved.
Fig. 5 is a diagram illustrating a computer system according to an exemplary embodiment, which includes a Central Processing Unit (CPU)401 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for system operation are also stored. The CPU401, ROM402, and RAM403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. Drivers are also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
In particular, the processes described above in fig. 1-2 may be implemented as computer software programs, according to embodiments of the present application. For example, various embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section, and/or installed from a removable medium. The above-described functions defined in the system of the present application are executed when the computer program is executed by a Central Processing Unit (CPU) 401.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods, apparatus, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves. The described units or modules may also be provided in a processor, and may be described as: a processor comprises a first obtaining module, a first determining module, a second obtaining module and a calculating module. The names of these units or modules do not in some cases constitute a limitation on the units or modules themselves, and for example, the first acquisition module may also be described as "a first acquisition module for acquiring ship profile information".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement the method for digging efficiency of loading and unloading the harbor berth as described in the above embodiments.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (16)
1. A port berth loading and unloading efficiency excavating method is characterized by comprising the following steps:
acquiring at least one piece of ship basic information, wherein each piece of ship basic information comprises historical ship draft data, a ship model, and maximum draft data and maximum load data corresponding to the ship model;
inputting at least one of said historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo load capacity of a ship berthing at a port berth, the cargo load capacity being the amount of cargo loaded or unloaded by the ship berthing at said port berth;
acquiring the minimum ship berthing time corresponding to the maximum cargo loading and unloading amount;
the loading and unloading efficiency of the port berth is calculated based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
2. The method of claim 1, wherein said inputting at least one of said historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling of a berthing ship at a port berth comprises:
inputting each historical ship draft data into a pre-constructed cargo estimation model respectively to determine the actual cargo handling capacity of the ship corresponding to the historical ship draft data;
determining a maximum cargo handling amount of a vessel berthed at the port berth based on actual cargo handling amount of the vessel and maximum load data of the vessel.
3. The method of claim 2, wherein said inputting each of said historical vessel draft data into a pre-constructed cargo estimation model to determine an actual cargo handling capacity of said vessel corresponding to said historical vessel draft data comprises:
acquiring historical ship draft data when the ship enters the port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a first cargo capacity of the ship;
acquiring historical ship draft data when the ship leaves the port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a second cargo capacity of the ship;
and determining the actual cargo handling amount of the ship based on the first cargo carrying amount and the second cargo carrying amount, wherein the actual cargo handling amount is the difference value of the first cargo carrying amount and the second cargo carrying amount.
4. The method of claim 2, wherein determining the maximum cargo handling capacity for a vessel berthing at the port berth based on the actual cargo handling capacity of the vessel and the maximum load data for the vessel comprises:
judging whether the actual cargo handling capacity of each ship is larger than or equal to a cargo handling capacity threshold value of the ship, wherein the cargo handling capacity threshold value of the ship is 0.9 times of the maximum load data of the ship;
determining the actual cargo handling capacity of at least one of said vessels as the maximum cargo handling capacity of a vessel berthing at said port berth if there is at least one of said vessels whose actual cargo handling capacity is greater than or equal to said vessel's cargo handling capacity threshold;
and if the actual cargo handling amount of the ship is smaller than the threshold value of the cargo handling amount of the ship, filtering the actual cargo handling amount of the ship.
5. The method of claim 1, wherein the pre-constructed cargo estimation model comprises:
and training and learning according to a machine learning algorithm or a deep learning algorithm by using a sample set consisting of the maximum load data, the maximum draft data and the draft data of the ship in the no-load state so as to establish a mapping relation between the draft data of the ship and the load data of the ship, wherein the mapping relation is used as a cargo estimation model.
6. The method of claim 5, wherein draft data for the vessel in an unloaded state comprises:
calculating first no-load draft data based on the ship model and the maximum draft data of the ship;
and determining draft data of the ship in an unloaded state based on the historical ship draft data of the ship model and the first unloaded draft data.
7. The method of claim 1, further comprising:
identifying the berthing behavior of the ship at the port according to the acquired global ship track data and the port range data;
determining the port berth geographical range according to the berthing behavior and the ship attribute information;
and establishing a corresponding relation between the port berth geographic range and the port berth loading and unloading efficiency.
8. A port berth handling efficiency excavating gear, characterized by that, the said device includes:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is configured to acquire at least one piece of ship basic information, and each piece of ship basic information comprises historical ship draft data, a ship model, and maximum draft data and maximum load data corresponding to the ship model;
a first determination module configured to input at least one of the historical ship draft data into a pre-constructed cargo estimation model to determine a maximum cargo handling capacity of a berthing ship at a port berth, the cargo handling capacity being an amount of cargo loaded or unloaded by the berthing ship at the port berth;
a second acquisition module configured to acquire a minimum ship berthing time corresponding to the maximum cargo handling amount;
a calculation module configured to calculate a loading and unloading efficiency of the port berth based on the maximum cargo loading and unloading amount and the minimum ship berthing time.
9. The apparatus of claim 8, wherein the first determining module is configured to:
inputting each historical ship draft data into a pre-constructed cargo estimation model respectively to determine the actual cargo handling capacity of the ship corresponding to the historical ship draft data;
determining a maximum cargo handling amount of a vessel berthed at the port berth based on actual cargo handling amount of the vessel and maximum load data of the vessel.
10. The apparatus of claim 9, wherein the first determining module is configured to:
acquiring historical ship draft data when the ship enters the port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a first cargo capacity of the ship;
acquiring historical ship draft data when the ship leaves the port berth from each historical ship draft data, inputting the historical ship draft data into a pre-constructed cargo estimation model, and determining a second cargo capacity of the ship;
and determining the actual cargo handling amount of the ship based on the first cargo carrying amount and the second cargo carrying amount, wherein the actual cargo handling amount is the difference value of the first cargo carrying amount and the second cargo carrying amount.
11. The apparatus of claim 9, wherein the first determining module is configured to:
judging whether the actual cargo handling capacity of each ship is larger than or equal to a cargo handling capacity threshold value of the ship, wherein the cargo handling capacity threshold value of the ship is 0.9 times of the maximum load data of the ship;
determining the actual cargo handling capacity of at least one of said vessels as the maximum cargo handling capacity of a vessel berthing at said port berth if there is at least one of said vessels whose actual cargo handling capacity is greater than or equal to said vessel's cargo handling capacity threshold;
and if the actual cargo handling amount of the ship is smaller than the threshold value of the cargo handling amount of the ship, filtering the actual cargo handling amount of the ship.
12. The apparatus of claim 8, wherein the first determining module is configured to:
and training and learning according to a machine learning algorithm or a deep learning algorithm by using a sample set consisting of the maximum load data, the maximum draft data and the draft data of the ship in the no-load state so as to establish a mapping relation between the draft data of the ship and the load data of the ship, wherein the mapping relation is used as a cargo estimation model.
13. The apparatus of claim 12, wherein the first determining module is configured to:
calculating first no-load draft data based on the ship model and the maximum draft data of the ship;
and determining draft data of the ship in an unloaded state based on the historical ship draft data of the ship model and the first unloaded draft data.
14. The apparatus of claim 8, further comprising:
the identification module is configured to identify the berthing behavior of the ship at the port according to the acquired global ship track data and the port range data;
the second determining module is configured to determine the geographic range of the port berth according to the berthing behavior and the ship attribute information;
the establishing module is configured to establish a corresponding relation between the port berth geographic range and the port berth loading and unloading efficiency.
15. A computer device, characterized in that the computer device comprises:
a processor;
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the port berth handling efficiency excavation method of any of claims 1 to 7.
16. A computer readable storage medium having stored therein instructions which, when run on a processing component, cause the processing component to perform the method of port berth loading efficiency excavation of any of claims 1 to 7.
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