CN110750571A - Port berth data mining method, device, equipment and storage medium - Google Patents

Port berth data mining method, device, equipment and storage medium Download PDF

Info

Publication number
CN110750571A
CN110750571A CN201810813130.5A CN201810813130A CN110750571A CN 110750571 A CN110750571 A CN 110750571A CN 201810813130 A CN201810813130 A CN 201810813130A CN 110750571 A CN110750571 A CN 110750571A
Authority
CN
China
Prior art keywords
port
berth
data
berthing
attribute information
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201810813130.5A
Other languages
Chinese (zh)
Other versions
CN110750571B (en
Inventor
梁新
徐垚
朱福建
温建新
陈业坤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
CET MARINE INSTITUTE OF INFORMATION TECHNOLOGY Co Ltd
Original Assignee
CET MARINE INSTITUTE OF INFORMATION TECHNOLOGY Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by CET MARINE INSTITUTE OF INFORMATION TECHNOLOGY Co Ltd filed Critical CET MARINE INSTITUTE OF INFORMATION TECHNOLOGY Co Ltd
Priority to CN201810813130.5A priority Critical patent/CN110750571B/en
Publication of CN110750571A publication Critical patent/CN110750571A/en
Application granted granted Critical
Publication of CN110750571B publication Critical patent/CN110750571B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The invention discloses a method, a device, equipment and a storage medium for excavating port berth data. The method comprises the steps of determining the port berthing behavior of a ship according to the acquired global ship track data and port range data, determining the port berth geographic range according to the port berthing behavior and the ship attribute information, and carrying out statistical analysis on the additional attribute information of each berth according to the ship attribute information and the port berth geographic range. According to the technical scheme of the embodiment of the invention, the real-time performance and the accuracy of the harbor berth data can be ensured.

Description

Port berth data mining method, device, equipment and storage medium
Technical Field
The embodiment of the invention relates to the technical field of internet, in particular to a method, a device, equipment and a storage medium for excavating port berth data.
Background
With the acceleration of the global economy integration process, international trade is more and more close, and according to the statistics data of un department of government (UNSD), about 79% of goods in international trade are transported by ocean. The port is used as an important hub node in the global shipping traffic network, and provides basic support for national economic construction and development of external trade.
With the continuous resurgence of the shipping industry, the port plays an increasingly large role in the development of national economy, and becomes an important guarantee that the port is integrated into the global economy and has competitiveness therein, and the berth is used as a working unit of the basic function of the port, so that the role of the berth is undoubted.
The port berth refers to the position of a ship berthing in a port, and the number and the size of the berths in the port are important indexes for measuring the scale of one port or wharf. In addition to the position information contained in the harbor berth, the harbor berth generally has related additional attribute information, such as the type of ships that the berth can be parked, the maximum parking load, the maximum parking draft, the maximum parked ship length and the like. However, the berth information is private information of the port, is generally not disclosed, and only can acquire information such as port berth number, berthable ship type, cargo loading and unloading type and the like from basic introduction of the port, and cannot acquire accurate geographic position and attribute information of the port berth.
At present, port berth information is mainly collected manually, but the manual collection of the port berth data has the following defects:
(1) the information source is limited, the data quality is difficult to ensure, and the result accuracy is influenced. The port berth information collected manually has no uniform standard due to different data sources; the data is not accurate enough, and the port berth geographical position provided by the data source is only an approximate position (such as (33.8,130.99) a longitude and latitude point on a map), while the port berth is generally a geographical range with a certain length and a certain safe separation distance with adjacent berths. Therefore, in the manual statistical analysis, the data source and the data quality are difficult to be ensured, and the accuracy of the subsequent analysis result is influenced. (2) The data source data has certain limitation, the port berth data collected manually comes from each port, each port only contains the port berth data of the port, and the berth data has certain characteristic characteristics. (3) The information is acquired in a delayed mode, and the real-time performance of the result is affected. The information needed by manual statistics is limited by whether the data source side provides relevant information or updates the information in time. The new construction and abandonment of the harbor berth are generally familiar to the owners of ships, etc. who know the inside of the harbor or frequently go to and from the harbor, and under the normal condition, the information can not be updated in the first time, even after a long time, so that the real-time performance of the information is difficult to be ensured, and the real-time performance of the analysis result is poor.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, it is desirable to provide a method, a device, a facility and a storage medium for digging harbor berth data, which can ensure real-time and accuracy of harbor berth data.
In a first aspect, an embodiment of the present invention provides a method for digging port berth data, including:
determining 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 berthing geographic range according to the port berthing behavior and the ship attribute information;
and according to the ship attribute information and the geographic range of the port berths, statistically analyzing the additional attribute information of each berth.
In a second aspect, an embodiment of the present invention further provides a harbor berth data excavating device, including:
the port berthing behavior determining module is used for determining the port berthing behavior of the ship according to the acquired global ship track data and the port range data;
the port berth geographic range determining module is used for determining a port berth geographic range according to the port berthing behavior and the ship attribute information;
and the attribute information statistical module is used for performing statistical analysis on the additional attribute information of each berth according to the ship attribute information and the geographical range of the port berth.
In a third aspect, an embodiment of the present invention further provides an apparatus, including:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of the first aspect of embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, where the computer program is executed by a processor to implement the method according to the first aspect of the embodiment of the present invention.
According to the technical scheme provided by the embodiment of the invention, the port berthing behavior of the ship is determined according to the acquired global ship track data and the port range data, the port berthing geographic range is determined according to the port berthing behavior and the ship attribute information, and the additional attribute information of each berth is statistically analyzed according to the ship attribute information and the port berthing geographic range, so that the real-time performance and the accuracy of port berthing data can be ensured.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1 is a schematic flow chart of a port berth data mining method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a port berth data mining method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a port berth data excavating device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying 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 may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
Example one
Fig. 1 is a schematic flow chart of a port berth data mining method according to an embodiment of the present invention, and an execution main body of the embodiment may be the port berth data mining device according to the embodiment of the present invention, and the device may be integrated in a mobile terminal device (e.g., a smart phone, a tablet computer, etc.), or may be integrated in a fixed terminal (a desktop computer) or a server, and the port berth data mining device may be implemented by hardware or software. The following description will be made with reference to an embodiment, as shown in fig. 1, specifically including:
s101, determining the port berthing behavior of the ship according to the acquired global ship track data and the port range data.
Specifically, the Global ship track data, the ship attribute data and the port range data can be acquired based on various means such as an Automatic Identification System (AIS) of a ship, a radar, a Beidou, a Global Positioning System (GPS) and the like, so that sufficient data can be provided for analysis, a Global port can be comprehensively covered, and the excavated port berth data is more comprehensive. In addition, the data sources are wide, are not influenced by human factors, and have high accuracy and reliability, so the data sources do not become the bottleneck of analysis any more.
Optionally, determining the port berthing behavior of the ship according to the acquired global ship track data and port range data includes: acquiring global ship track data, and preprocessing the global ship track data; performing port-in or port-out identification according to the preprocessed data and port range data; and carrying out port berthing behavior identification on the port data.
Wherein the pretreatment includes but is not limited to at least one of the following: data fusion, data correction, data filtering and data sorting.
Specifically, port/non-port identification is performed on the preprocessed data, and if the data is in the port range data, subsequent processing is performed, that is, step S102 is executed; if the data is not within the port-wide data, the data is filtered.
S102, determining the port berthing geographical range according to the port berthing behavior and the ship attribute information.
Optionally, the present step includes: performing cluster analysis on berth data formed by the berthing behaviors in the harbor to obtain at least one berthing behavior point in the harbor; and performing convex hull operation on the identified port berthing behavior points, and determining the port berth geographical range by combining the ship attribute information.
Among them, the clustering algorithm that can be used is Density-Based clustering algorithm (DBSCAN). Specifically, the berthing data is clustered by using a DBSCAN algorithm, an obtained core point set is berthing behavior points (a plurality of classes can be formed) in the port, berthing duration is recorded, convex hull algorithm operation is carried out on the identified berthing behavior points, and a port berthing geographical range is formed by combining ship attribute data.
In addition, in order to make the data more accurate, the method of this embodiment further includes: grouping the berth data in a preset time according to the port; and if the cross area exists in the geographic range of the port berth and meets a preset threshold value, merging the berths and updating the geographic range of the port berth.
And periodically counting the berth data and updating the geographical range of the port berth.
S103, according to the ship attribute information and the port berth geographic range, the additional attribute information of each berth is statistically analyzed.
Optionally, the additional attribute information includes at least one of: the type of vessel that can be parked, the maximum load of berthing, the maximum draft of berthing, the maximum length of berthing.
In addition, in order to make the data more accurate, the method of this embodiment further includes: and counting information such as the load, the berthing duration and the like of various types of ships berthing the same berth within a period of time to form additional attribute information of the berth.
And periodically counting the berth data to update the berth data.
According to the embodiment, the harbor berthing behavior of the ship is determined according to the acquired global ship track data and the harbor range data, the harbor berthing geographic range is determined according to the harbor berthing behavior and the ship attribute information, the additional attribute information of each berth is statistically analyzed according to the ship attribute information and the harbor berthing geographic range, and the real-time performance and the accuracy of harbor berthing data can be ensured.
Example two
Fig. 2 is a schematic flow chart of a harbor berth data mining method according to a second embodiment of the present invention, and this embodiment is a specific embodiment for explaining the implementation process of the present invention in detail, and as shown in fig. 2, the method includes:
s201, global ship track data are obtained, and preprocessing is carried out on the global ship track data.
And S202, identifying whether the harbor exists or not according to the preprocessed data and the harbor range data.
And S203, identifying the port berthing behavior of the port data.
S204, carrying out cluster analysis on the berth data formed by the berthing behaviors in the harbor to obtain at least one berthing behavior point in the harbor.
S205, performing convex hull operation on the identified harbor berthing behavior points, and determining the harbor berthing geographical range by combining ship attribute information.
And S206, grouping the berth data in the preset time according to the port.
And S207, if the cross area exists in the geographic range of the port berth and meets a preset threshold value, merging the berths and updating the geographic range of the port berth.
S208, counting information of loads, berthing duration and the like of various types of ships berthing in the same berth within a period of time to form additional attribute information of the berth.
The embodiment excavates the berth geographic position range and the additional attribute information thereof in the global port range based on the global ship track data, the ship attribute information and the port range data. On one hand, the digging of the global port berth data breaks the situation of the privacy and the limitation of the port berth data, and provides comprehensive, standard and accurate data for the subsequent research on shipping; on the other hand, the excavated global port berth geography and related attribute information are beneficial to confirming various goods types and estimating specific loads in the global shipping and transportation network, and information data are provided for analysis in the global economy field; by the excavated global port berth geography and related attribute information, information such as load and type of ships berthing at the port berth is counted and analyzed, information such as port cargo handling capacity, port bearing capacity and port operation condition is analyzed, accurate operation condition analysis information is provided for ports, and port resources and facilities are adjusted correctly and reasonably by the ports; by the aid of the excavated global port berth geography and related attribute information, port ship information of the port is analyzed in real time, and port berth information is fed back to the captain in time, so that timely adjustment of a flight line is facilitated, and economic loss caused by long-term queuing for berthing is avoided.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a port berth data mining device according to a third embodiment of the present invention, where the device may be integrated in a mobile terminal (e.g., a smart phone, a tablet computer, etc.), or may be integrated in a fixed terminal (a desktop computer) or a server, and the port berth data mining device may be implemented by hardware or software. The following description will be made with reference to an embodiment, as shown in fig. 3, specifically including: an on-port berthing behavior determining module 301, a port berthing geographic range determining module 302 and an attribute information counting module 303;
the port-in berthing behavior determining module 301 is configured to determine port-in berthing behaviors of the ship according to the acquired global ship trajectory data and port range data;
the port berth geographic range determining module 302 is used for determining a port berth geographic range according to port berthing behaviors and ship attribute information;
the attribute information statistic module 303 is configured to statistically analyze the additional attribute information of each berth according to the ship attribute information and the geographic range of port berths.
Optionally, the additional attribute information includes at least one of: the type of vessel that can be parked, the maximum load of berthing, the maximum draft of berthing, the maximum length of berthing.
Optionally, the at-port berthing behavior determining module is specifically configured to: acquiring global ship track data, and preprocessing the global ship track data; performing port-in or port-out identification according to the preprocessed data and port range data; and carrying out port berthing behavior identification on the port data.
Optionally, the port berth geographic range determining module is specifically configured to: performing cluster analysis on berth data formed by the berthing behaviors in the harbor to obtain at least one berthing behavior point in the harbor; and performing convex hull operation on the identified port berthing behavior points, and determining the port berth geographical range by combining the ship attribute information.
Optionally, the apparatus further comprises: the berth merging and updating module is used for grouping berth data in preset time according to a port; and if the cross area exists in the geographic range of the port berth and meets a preset threshold value, merging the berths and updating the geographic range of the port berth.
It should be understood that the modules and units described in the embodiments of the present invention correspond to the respective steps in the method described in fig. 1. Thus, the operations and features described above for the method are equally applicable to the apparatus and will not be described in detail here. The device can be realized in the browser or other security applications of the electronic equipment in advance, and can also be loaded into the browser or other security applications of the electronic equipment in a downloading mode and the like. The corresponding modules in the device can cooperate with units in the electronic equipment to implement the solution of the embodiment of the invention.
Example four
Fig. 4 is a schematic structural diagram of an apparatus according to a fourth embodiment of the present invention, which shows a schematic structural diagram of an apparatus suitable for implementing the fourth embodiment of the present invention.
As shown in fig. 4, the apparatus includes a Central Processing Unit (CPU)401 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for system operation are also stored. The CPU 401, ROM402, and RAM 403 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 407 including a display device 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. A driver 410 is 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 process described above in FIG. 1 may be implemented as a computer software program, according to the disclosed embodiments of the invention. For example, embodiments of the invention include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method of FIG. 1. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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 or modules described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware. The described units or modules may also be provided in a processor, and may be described as: a processor comprises an on-port berthing behavior determining module, a port berthing geographic range determining module and an attribute information counting module. Where the names of these units or modules do not in some cases constitute a limitation of the unit or module itself, for example, the at port berthing behavior determining module may also be described as a "module for determining at port berthing behavior".
As another aspect, the present invention also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiments; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the method of port berth data mining described in the present invention.
The foregoing description is only exemplary of the preferred embodiments of the invention and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features and (but not limited to) features having similar functions disclosed in the present invention are mutually replaced to form the technical solution.

Claims (12)

1. A method for mining port berth data is characterized by comprising the following steps:
determining 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 berthing geographic range according to the port berthing behavior and the ship attribute information;
and according to the ship attribute information and the geographic range of the port berths, statistically analyzing the additional attribute information of each berth.
2. The method of claim 1, wherein the additional attribute information comprises at least one of:
the type of vessel that can be parked, the maximum load of berthing, the maximum draft of berthing, the maximum length of berthing.
3. The method of claim 1, wherein determining the port berthing behavior of the vessel based on the acquired global vessel trajectory data and port range data comprises:
acquiring global ship track data, and preprocessing the global ship track data;
performing port-in or port-out identification according to the preprocessed data and port range data;
and carrying out port berthing behavior identification on the port data.
4. The method of claim 3, wherein determining the port berth geographic extent from the port berthing behavior and vessel attribute information comprises:
performing cluster analysis on the berth data formed by the berthing behaviors in the harbor to obtain at least one berthing behavior point in the harbor;
and performing convex hull operation on the identified port berthing behavior points, and determining the port berth geographical range by combining the ship attribute information.
5. The method according to any one of claims 1-4, further comprising:
grouping the berth data in a preset time according to the port;
and if the cross area exists in the geographic range of the port berth and meets a preset threshold value, merging the berths and updating the geographic range of the port berth.
6. A port berth data mining device, characterized in that the device comprises:
the port berthing behavior determining module is used for determining the port berthing behavior of the ship according to the acquired global ship track data and the port range data;
the port berth geographic range determining module is used for determining a port berth geographic range according to the port berthing behavior and the ship attribute information;
and the attribute information statistical module is used for performing statistical analysis on the additional attribute information of each berth according to the ship attribute information and the geographical range of the port berth.
7. The apparatus of claim 6, wherein the additional attribute information comprises at least one of:
the type of vessel that can be parked, the maximum load of berthing, the maximum draft of berthing, the maximum length of berthing.
8. The apparatus of claim 6, wherein the at-port berthing behavior determination module is specifically configured to:
acquiring global ship track data, and preprocessing the global ship track data; performing port-in or port-out identification according to the preprocessed data and port range data; and carrying out port berthing behavior identification on the port data.
9. The apparatus of claim 8, wherein the port berth geographic range determination module is specifically configured to:
performing cluster analysis on the berth data formed by the berthing behaviors in the harbor to obtain at least one berthing behavior point in the harbor; and performing convex hull operation on the identified port berthing behavior points, and determining the port berth geographical range by combining the ship attribute information.
10. The apparatus according to any one of claims 6-9, further comprising:
the berth merging and updating module is used for grouping berth data in preset time according to a port; and if the cross area exists in the geographic range of the port berth and meets a preset threshold value, merging the berths and updating the geographic range of the port berth.
11. An apparatus, characterized in that the apparatus comprises:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method recited in any of claims 1-5.
12. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
CN201810813130.5A 2018-07-23 2018-07-23 Port berth data mining method, device, equipment and storage medium Active CN110750571B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810813130.5A CN110750571B (en) 2018-07-23 2018-07-23 Port berth data mining method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810813130.5A CN110750571B (en) 2018-07-23 2018-07-23 Port berth data mining method, device, equipment and storage medium

Publications (2)

Publication Number Publication Date
CN110750571A true CN110750571A (en) 2020-02-04
CN110750571B CN110750571B (en) 2023-12-29

Family

ID=69275134

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810813130.5A Active CN110750571B (en) 2018-07-23 2018-07-23 Port berth data mining method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN110750571B (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111402636A (en) * 2020-06-05 2020-07-10 江苏海事职业技术学院 Ship berthing command method and system based on big data
CN111581314A (en) * 2020-04-26 2020-08-25 亿海蓝(北京)数据技术股份公司 Berth identification method and device based on ship track
CN112541591A (en) * 2020-11-26 2021-03-23 中远海运科技股份有限公司 Parking position identification method and platform
CN113159429A (en) * 2021-04-26 2021-07-23 亿海蓝(北京)数据技术股份公司 Method and device for acquiring parking lot information
CN113822513A (en) * 2020-12-09 2021-12-21 清华大学 Port congestion monitoring method based on anchor ground and berth automatic identification algorithm
CN113988213A (en) * 2021-11-12 2022-01-28 中远海运科技股份有限公司 Ship in-dock repair identification method and system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110131050A1 (en) * 2009-12-01 2011-06-02 The Boeing Company Harbor Berth Information System
CN102622913A (en) * 2012-04-11 2012-08-01 成都林海电子有限责任公司 Guidance system for vessel harboring
CN107256438A (en) * 2017-05-26 2017-10-17 亿海蓝(北京)数据技术股份公司 Predict the method and device of Ship and port residence time

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110131050A1 (en) * 2009-12-01 2011-06-02 The Boeing Company Harbor Berth Information System
CN102622913A (en) * 2012-04-11 2012-08-01 成都林海电子有限责任公司 Guidance system for vessel harboring
CN107256438A (en) * 2017-05-26 2017-10-17 亿海蓝(北京)数据技术股份公司 Predict the method and device of Ship and port residence time

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
周晓怡 等: "利用AIS 数据连续观测港口泊位服务水平的方法", 《中国水运》 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111581314A (en) * 2020-04-26 2020-08-25 亿海蓝(北京)数据技术股份公司 Berth identification method and device based on ship track
CN111581314B (en) * 2020-04-26 2023-06-23 亿海蓝(北京)数据技术股份公司 Berth recognition method and berth recognition device based on ship track
CN111402636A (en) * 2020-06-05 2020-07-10 江苏海事职业技术学院 Ship berthing command method and system based on big data
CN112541591A (en) * 2020-11-26 2021-03-23 中远海运科技股份有限公司 Parking position identification method and platform
CN113822513A (en) * 2020-12-09 2021-12-21 清华大学 Port congestion monitoring method based on anchor ground and berth automatic identification algorithm
CN113159429A (en) * 2021-04-26 2021-07-23 亿海蓝(北京)数据技术股份公司 Method and device for acquiring parking lot information
CN113159429B (en) * 2021-04-26 2023-07-14 亿海蓝(北京)数据技术股份公司 Method and device for acquiring information of berth goods seeds
CN113988213A (en) * 2021-11-12 2022-01-28 中远海运科技股份有限公司 Ship in-dock repair identification method and system
CN113988213B (en) * 2021-11-12 2024-03-19 中远海运科技股份有限公司 Method and system for identifying repairing of ship in dock

Also Published As

Publication number Publication date
CN110750571B (en) 2023-12-29

Similar Documents

Publication Publication Date Title
CN110750571B (en) Port berth data mining method, device, equipment and storage medium
CN109658439B (en) Ship harbor state identification method, device, equipment and storage medium
US11492091B2 (en) Method for vessel tracking
CN112016730B (en) Port berth loading and unloading efficiency mining method, device, equipment and storage medium
US10178511B2 (en) Vessel traffic management system
CN110608982A (en) Detection method, detection device, mobile equipment, electronic equipment and storage medium
CN110069582B (en) Ship anchoring area determining method, device, equipment and storage medium
WO2015127540A1 (en) System and method for tracking and forecasting the positions of marine vessels
US20170276490A1 (en) Gps-based area recognition in vehicles
CN109597920B (en) Ship target black and white list maintenance method based on real-time AIS
CN111091226A (en) Transport capacity prediction method based on actual shipping service and data mining
EP2495696A1 (en) Management server, population information calculation management server, zero population distribution area management method, and population information calculation method
CN111311908A (en) Method and device for identifying and processing repeated traffic information
CN110186472B (en) Vehicle yaw detection method, computer device, storage medium, and vehicle system
CN112991820B (en) Fake plate ship identification method and system
CN111127930A (en) Method and device for acquiring common driving route of vehicle
CN110502601B (en) Method and device for searching warehouse
CN116955937A (en) Marine suspicious ship monitoring method and device, electronic equipment and storage medium
CN115221220B (en) Multi-airport system identification method based on spatial organization characteristics
CN114331568B (en) Commercial vehicle market segment identification method, equipment and medium based on Internet of vehicles
CN107084728B (en) Method and device for detecting digital map
CN115880533A (en) Bridge apparent crack identification method based on adaptive subset search and deep learning
CN115481170A (en) Vehicle track processing method and device, electronic equipment and storage medium
CN114358404A (en) Flight data processing method, device electronic equipment and storage medium
Asborno et al. Inland waterway network mapping of AIS data for freight transportation planning

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant