CN115599125B - Navigation aid light control strategy selection method based on edge calculation - Google Patents
Navigation aid light control strategy selection method based on edge calculation Download PDFInfo
- Publication number
- CN115599125B CN115599125B CN202211600968.9A CN202211600968A CN115599125B CN 115599125 B CN115599125 B CN 115599125B CN 202211600968 A CN202211600968 A CN 202211600968A CN 115599125 B CN115599125 B CN 115599125B
- Authority
- CN
- China
- Prior art keywords
- control strategy
- light control
- light
- grade
- terminal equipment
- 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.)
- Active
Links
- 238000011217 control strategy Methods 0.000 title claims abstract description 111
- 238000004364 calculation method Methods 0.000 title claims abstract description 21
- 238000010187 selection method Methods 0.000 title claims abstract description 11
- 238000013139 quantization Methods 0.000 claims abstract description 38
- 238000011156 evaluation Methods 0.000 claims abstract description 35
- 239000011159 matrix material Substances 0.000 claims abstract description 35
- 238000000034 method Methods 0.000 claims abstract description 27
- 238000013528 artificial neural network Methods 0.000 claims description 12
- 230000007613 environmental effect Effects 0.000 claims description 10
- 239000000126 substance Substances 0.000 claims description 9
- 238000010801 machine learning Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 2
- 238000005457 optimization Methods 0.000 abstract description 3
- 238000012545 processing Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000003672 processing method Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
- H05B47/10—Controlling the light source
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Computational Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Software Systems (AREA)
- Pure & Applied Mathematics (AREA)
- Artificial Intelligence (AREA)
- Automation & Control Theory (AREA)
- Algebra (AREA)
- Remote Sensing (AREA)
- Biomedical Technology (AREA)
- Aviation & Aerospace Engineering (AREA)
- Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Databases & Information Systems (AREA)
- Radar, Positioning & Navigation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Circuit Arrangement For Electric Light Sources In General (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention belongs to the technical field of navigation aid light control, and particularly provides a navigation aid light control strategy selection method based on edge calculation, which is used for meeting the navigation aid light control requirement during safe operation of an airport. The method fully utilizes the computing power of edge side computing equipment, adopts three environment parameter quantitative values of runway direction, operation time period and visibility to form an operation scene grade, sets an environment parameter evaluation matrix for the light-operated terminal equipment based on the operation scene grade, and sets a control strategy grade evaluation matrix based on a prior light control strategy; and then calculating according to the environment parameter evaluation matrix to obtain a comprehensive environment quantization set of the light-operated terminal equipment, further calculating based on the comprehensive environment quantization set and the control strategy grade evaluation matrix to obtain a control strategy grade quantization set of the light-operated terminal equipment, and finally realizing navigation-assisted light control strategy selection based on the control strategy grade quantization set. The invention can realize the maximum optimization of light control efficiency and save the computing resources.
Description
Technical Field
The invention belongs to the technical field of navigation aid lighting control, relates to an edge computing system, and particularly provides a navigation aid lighting control strategy selection method based on edge computing under the Internet of things.
Background
The navigation aid light is a light sign arranged at a specified section of an airport scene, is used as an important infrastructure for ensuring safe and efficient operation of an aircraft on the airport scene, and provides visual guidance for takeoff, landing and sliding of the aircraft at night or under the condition of low visibility. When an airport normally operates, different areas and different types of navigation aid lighting equipment need to operate corresponding specified setting combinations such as directions, light levels, stroboflash and the like at different time intervals and under different visibility and other environmental constraints. With the rapid development of civil aviation industry in China, the types and the number of navigation aid lighting equipment are rapidly increased by newly building, reconstructing and expanding large and medium airports, the calculated data volume, the complexity and the processing time delay of a system are improved, and the traditional navigation aid lighting control strategy processing method is provided with a small challenge.
In order to meet various application scenes with low time delay and high reliability requirements such as industrial control, unmanned driving, virtual reality and the like, a system framework based on edge computing appears, and edge computing equipment is introduced into a cloud computing server and a terminal equipment network layer; compared with cloud computing, edge computing brings nearby data processing capability, reduces network data transmission quantity, system processing time delay and computing complexity, and also improves data processing reliability, which is called the last kilometer of artificial intelligence. Based on the above, the invention introduces a system framework of edge calculation and provides a navigation light control strategy selection method based on edge calculation so as to solve the application problem in practical engineering.
Disclosure of Invention
The invention aims to provide a navigation light control strategy selection method based on edge calculation, which is used for solving the problems of complex central system setting and adjustment, large data calculation amount, high processing time delay, unquantized manual experience, potential safety hazard caused by human errors and the like in the traditional navigation light control strategy processing method. According to the invention, the edge computing system is adopted, the edge side computing equipment quantizes airport environment parameters faced by the light-operated terminal equipment of the navigational lights according to various navigational light requirements during safe operation of an airport, and the navigational light control strategy selection is carried out according to quantized objective standards, so that the maximum optimization of the light control efficiency based on the edge computing system is realized.
In order to realize the purpose, the invention adopts the technical scheme that:
a navigation light control strategy selection method based on edge calculation is characterized in that the navigation light control strategy selection method is realized based on an edge calculation system and specifically comprises the following steps:
step 1 for the firstiThe edge side computing equipment sets an environment parameter evaluation matrix of the light-operated terminal equipment according to the operation scene gradeA i ，i=1,2,...,k，kThe number of the light-operated terminal equipment;
step 2, the edge side computing equipment evaluates the matrix according to the environmental parametersA i Is calculated to obtainiComprehensive environment quantization set of individual light-operated terminal equipmentW i ；
Step 3, the edge side computing equipment sets a control strategy grade evaluation matrix according to the prior light control strategyB；
Step 4, the edge side computing equipment quantizes the set according to the comprehensive environmentW i And control strategy grade evaluation matrixBIs calculated to obtain the firstiControl strategy grade quantization set of individual light-operated terminal equipmentZ i ；
Step 5, the edge side computing equipment quantizes the set according to the control strategy gradeZ i Is as followsiAnd the light control terminal equipment provides a light control strategy and sends the light control strategy to the light control terminal equipment.
Further, in step 1, the environment parameter evaluation matrixA i The method specifically comprises the following steps:
wherein, the first and the second end of the pipe are connected with each other,
is shown asiApplication of individual light-operated terminal equipmentvAt the level of the operating scenetA quantized value of an environmental parameter of the dimension;v=1,2,...,s，snumber of operational scene levels;t=1,2,3, corresponding to runway direction, operating hours, visibility respectively.
Further, in step 2, the integrated environment quantization setW i The method specifically comprises the following steps:
wherein the content of the first and second substances,
denotes the firstiApplication of individual light-operated terminal equipmentvThe comprehensive environment quantization value of each operation scene grade specifically comprises the following steps:
wherein, the first and the second end of the pipe are connected with each other,
is shown asiApplication of individual light-operated terminal equipmentvAt the level of the operating scenetA quantized value of an environmental parameter of the dimension;v=1,2,...,s，sthe number of operating scene levels;tand =1,2 and 3 respectively correspond to the direction of the runway, the running time period and the visibility.
Further, in step 3, the control strategy grade evaluation matrixBThe method specifically comprises the following steps:
wherein the content of the first and second substances,
is shown asvUnder the level of each operation scene, the first step is adoptedjThe grade evaluation value of each light control strategy,j=1,2,...,p，pthe number of prior light control strategies.
Further, the method can be used for preparing a novel materialIn step 4, the control strategy level quantization setZ i The method specifically comprises the following steps:
wherein the content of the first and second substances,
is shown asiThe individual light-operated terminal equipment adoptsjThe level quantization value of the individual light control strategy,j=1,2,...,p，pthe number of prior light control strategies.
Further, in step 5, when the first stepiWhen the light-operated terminal equipment needs a single light control strategy for control, the edge side computing equipment performs the level quantization set of the control strategyZ i And the light control strategy corresponding to the maximum value is selected and issued to the light control terminal equipment.
Further, in step 5, wheniWhen the light-operated terminal equipment needs two or more light control strategies to carry out combined control, a hierarchical analysis method or a machine learning algorithm is adopted to select the light control strategies so as to realize the combined control. Furthermore, the specific process of selecting the light control strategy by adopting the machine learning algorithm comprises the following steps: selecting light control strategy by BP neural network, and quantizing control strategy gradeZ i And the light control strategy is input into a BP neural network, and two or more than two light control strategies are output by the BP neural network and are issued to the light control terminal equipment to realize combined control.
Based on the technical scheme, the invention has the beneficial effects that:
the invention provides a navigation light control strategy selection method based on edge calculation, which fully utilizes the calculation capability of edge side calculation equipment, adopts three environment parameter quantized values of runway direction, operation time period and visibility to form an operation scene grade, sets an environment parameter evaluation matrix for light control terminal equipment based on the operation scene grade, and sets a control strategy grade evaluation matrix based on a prior light control strategy; and then calculating according to the environment parameter evaluation matrix to obtain a comprehensive environment quantization set of the light-operated terminal equipment, further calculating based on the comprehensive environment quantization set and the control strategy grade evaluation matrix to obtain a control strategy grade quantization set of the light-operated terminal equipment, and finally realizing navigation-assisted light control strategy selection based on the control strategy grade quantization set. The invention selects the light control strategy of the edge side light-operated terminal equipment through a quantitative objective standard, and realizes the maximum optimization of the light control efficiency based on an edge computing system; and the edge side computing equipment is used for carrying out comprehensive evaluation on the light control strategy grade based on the multi-dimensional environmental parameters, so that the computing resources are saved most on the premise of meeting the requirements of accurate and efficient light control.
Drawings
Fig. 1 is a schematic structural diagram of an edge computing system according to an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating a method for selecting a navigational lighting control strategy based on edge calculation according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a method for selecting a navigational lighting control strategy based on edge calculation according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a BP neural network in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail with reference to the accompanying drawings and examples.
The embodiment provides a method for selecting a navigation light control strategy based on edge calculation, which relates to an edge calculation system shown in fig. 1, and the system comprises: the system comprises a cloud computing server, edge side computing equipment and light-operated terminal equipment, wherein the light-operated terminal equipment comprises a light-operated terminal, an edge running light-operated terminal and a sliding light-operated terminal, and the edge side computing equipment is in wireless connection or wired connection with the light-operated terminal equipment.
In the embodiment, the running scene grade is formed by using three environment parameter quantized values of runway direction, running time period and visibility, as shown in fig. 2; setting an environment parameter evaluation matrix for each light-operated terminal device based on the operation scene grade, and setting a control strategy grade evaluation matrix based on a prior light control strategy; and the edge side computing equipment calculates to obtain a comprehensive environment quantization set of the light-operated terminal equipment according to the environment parameter evaluation matrix, calculates to obtain a control strategy grade quantization set of the light-operated terminal equipment based on the comprehensive environment quantization set and the control strategy grade evaluation matrix, and finally realizes navigation-aid light control strategy selection based on the control strategy grade quantization set.
Specifically, in the present embodiment, as shown in fig. 3, the method for selecting a navigation light control strategy based on edge calculation includes the following steps:
step 1, for the secondiThe edge side computing device sets an environment parameter evaluation matrix of the light-operated terminal device according to the operation scene gradeA i ，i=1,2,...,k，kThe number of the light-operated terminal equipment;
the environment parameter evaluation matrixA i The method specifically comprises the following steps:
wherein the content of the first and second substances,
denotes the firstiApplication of individual light-operated terminal equipmentvAt the level of the operating scenetA quantized value of an environmental parameter of the dimension;v=1,2,...,s，snumber of operational scene levels;t=1,2,3, corresponding to runway direction, running time period, visibility respectively;
the environment parameter evaluation matrix is an empirical quantization matrix, wherein each environment parameter quantization value can be determined by methods such as empirical quantization, user setting and the like by combining scene probability, equipment type, scene action weight and the like, the environment parameter evaluation matrices of the same type of light-operated terminal equipment under the same operation scene level are the same, and the exemplary environment parameter quantization values provided by the embodiment are shown in table 1;
TABLE 1
Step 2, the edge side computing equipment evaluates the matrix according to the environmental parametersA i Is calculated to obtainiComprehensive environment quantization set of individual light-operated terminal equipmentW i ；
The integrated environment quantization setW i The method specifically comprises the following steps:
wherein the content of the first and second substances,
is shown asiApplication of individual light-operated terminal equipmentvThe comprehensive environment quantization value of each operation scene grade specifically comprises the following steps: />
Step 3, the edge side computing equipment sets a control strategy grade evaluation matrix according to the prior light control strategyB；
The control strategy grade evaluation matrixBThe method specifically comprises the following steps:
wherein the content of the first and second substances,
is shown asvUnder the level of each operation scene, adoptjThe grade evaluation value of each light control strategy,j=1,2,...,p，pthe number of the prior light control strategies;
the control strategy grade evaluation matrixBIn order to empirically quantify the matrix(s),
comprehensively determining by methods of experience quantification, user setting and the like in combination with factors such as strategy energy efficiency, complexity and the like; and, control strategy grade evaluation matrixBThe method is suitable for all light-operated terminal equipment;
step 4, the edge side computing equipment quantizes the set according to the comprehensive environmentW i And control strategy grade evaluation matrixBIs calculated to obtain the firstiControl strategy grade quantization set of individual light-operated terminal equipmentZ i ；
The control strategy level quantization setZ i The method specifically comprises the following steps:
wherein the content of the first and second substances,
is shown asiThe light-operated terminal equipment adoptsjThe grade quantization value of each light control strategy;
step 5, the edge side computing equipment quantizes the set according to the control strategy gradeZ i Is as followsiThe light control terminal equipment provides a light control strategy and issues the light control strategy to the light control terminal equipment;
when it comes toiWhen the light-operated terminal equipment needs a single light control strategy for control, the edge side computing equipment performs the level quantization set of the control strategyZ i The light control strategy corresponding to the maximum value is selected and issued to the light control terminal equipment;
when it comes toiWhen an individual light-operated terminal device needs two or more light control strategies to perform combined control, the embodiment selects the light control strategies by adopting the BP neural network, and quantizes the control strategy levels into a setZ i Inputting the light control strategy into a BP neural network, outputting two or more light control strategies by the BP neural network, and sending the light control strategies to the light control terminal equipmentPerforming combined control; as shown in fig. 4, the BP neural network includes:N1 input layer of node,N2 hidden layers of nodes,NAn output layer of 3 nodes, wherein the output layer transmits the calculated loss back to the network; the BP neural network is trained offline, a priori navigation-aid light control strategy historical data set is adopted in a training set, a control strategy grade quantization set of the light control terminal equipment is used as input of a training sample, and light control strategy historical data of the light control terminal equipment is used as a label.
While the invention has been described with reference to specific embodiments, any feature disclosed in this specification may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise; all of the disclosed features, or all of the method or process steps, may be combined in any combination, except mutually exclusive features and/or steps.
Claims (4)
1. A navigation light control strategy selection method based on edge calculation is characterized in that the navigation light control strategy selection method is realized based on an edge calculation system and specifically comprises the following steps:
step 1, aiming at the ith light-operated terminal equipment, the edge side computing equipment sets an environmental parameter evaluation matrix A of the light-operated terminal equipment according to the grade of an operating scene i I =1, 2.. K, k is the number of optically controlled end devices;
the environment parameter evaluation matrix A i The method specifically comprises the following steps:
wherein the content of the first and second substances,
representing the t-dimension environmental parameter quantization value of the ith light-operated terminal device application v-th operation scene grade; v =1, 2.. Said, s, s is the number of operational scene levels; t =1,2,3, corresponding respectively to runway direction, operating hours, visibility;
step 2, the edge side computing equipment evaluates the matrix A according to the environmental parameters i Calculating to obtain a comprehensive environment quantization set W of the ith light-operated terminal equipment i ；
The integrated environment quantization set W i The method comprises the following specific steps:
wherein, the first and the second end of the pipe are connected with each other,
the comprehensive environment quantization value representing the ith light-operated terminal device applying the vth operation scene grade specifically is as follows:
step 3, the edge side computing equipment sets a control strategy grade evaluation matrix B according to the prior light control strategy;
the control strategy grade evaluation matrix B specifically comprises:
wherein, the first and the second end of the pipe are connected with each other,
representing a grade evaluation value of a jth light control strategy adopted under the ith operation scene grade, wherein j =1, 2.. And p is the number of the prior light control strategies;
step 4, the edge side computing equipment quantizes the set W according to the comprehensive environment i Calculating with the control strategy grade evaluation matrix B to obtain a control strategy grade quantization set Z of the ith light-operated terminal equipment i ；
The control strategy level quantization set Z i The method comprises the following specific steps:
wherein the content of the first and second substances,
the grade quantization value represents that the ith light control terminal device adopts the jth light control strategy;
step 5, the edge side computing equipment quantizes the set Z according to the control strategy grade i And providing a light control strategy for the ith light control terminal device, and issuing the light control strategy to the light control terminal device.
2. The method of claim 1, wherein in step 5, when the ith light control terminal device requires a single light control strategy for control, the edge-side computing device quantizes the set of control strategy levels Z i And the light control strategy corresponding to the maximum value is selected and issued to the light control terminal equipment.
3. The method for selecting a navigational light control strategy based on edge calculation as defined in claim 1, wherein in step 5, when the ith light control terminal device requires two or more light control strategies for combined control, the light control strategies are selected by a hierarchical analysis method or a machine learning algorithm to realize the combined control.
4. The method for selecting the aid-to-navigation light control strategy based on the edge calculation according to claim 3, wherein the specific process of selecting the light control strategy by adopting the machine learning algorithm is as follows: selecting a light control strategy by adopting a BP neural network, and quantizing a control strategy grade set Z i And the light control strategy is input into a BP neural network, and two or more than two light control strategies are output by the BP neural network and are issued to the light control terminal equipment to realize combined control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211600968.9A CN115599125B (en) | 2022-12-14 | 2022-12-14 | Navigation aid light control strategy selection method based on edge calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211600968.9A CN115599125B (en) | 2022-12-14 | 2022-12-14 | Navigation aid light control strategy selection method based on edge calculation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115599125A CN115599125A (en) | 2023-01-13 |
| CN115599125B true CN115599125B (en) | 2023-04-07 |
Family
ID=84854117
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211600968.9A Active CN115599125B (en) | 2022-12-14 | 2022-12-14 | Navigation aid light control strategy selection method based on edge calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115599125B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116867144B (en) * | 2023-09-04 | 2024-01-26 | 电子科技大学 | Navigation aid lamp brightness control method based on neural network |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0613110A1 (en) * | 1993-02-26 | 1994-08-31 | Raytheon Company | Airport incursion avoidance system |
| WO2010125198A1 (en) * | 2009-04-30 | 2010-11-04 | Adb Bvba | Illuminated sign for displaying a command and/or notice for taxiing aircraft traffic at an airport |
| CN102567093A (en) * | 2011-12-20 | 2012-07-11 | 广州粤嵌通信科技股份有限公司 | Berth type recognizing method applied in visual berth automatic guiding system |
| CN207969045U (en) * | 2018-03-21 | 2018-10-12 | 大连交通大学 | War preparedness based on wireless communication protocol/emergency airport sailing-assisting lamp system |
| CN109409292A (en) * | 2018-10-26 | 2019-03-01 | 西安电子科技大学 | The heterologous image matching method extracted based on fining characteristic optimization |
| CN110989614A (en) * | 2019-12-18 | 2020-04-10 | 电子科技大学 | Vehicle edge calculation transfer scheduling method based on deep reinforcement learning |
| CN111935171A (en) * | 2020-08-24 | 2020-11-13 | 南方电网科学研究院有限责任公司 | Terminal security policy selection method based on machine learning under edge calculation |
| CN112020183A (en) * | 2020-08-21 | 2020-12-01 | 深圳安航科技有限公司 | Solar navigation-aid light control system for airport |
| CN112597926A (en) * | 2020-12-28 | 2021-04-02 | 广州辰创科技发展有限公司 | Method, device and storage medium for identifying airplane target based on FOD image |
| CN113837097A (en) * | 2021-09-26 | 2021-12-24 | 南京航空航天大学 | Unmanned aerial vehicle edge calculation verification system and method for visual target identification |
| CN115190681A (en) * | 2022-06-14 | 2022-10-14 | 深圳星标科技股份有限公司 | Intelligent navigation aid control system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPWO2017081898A1 (en) * | 2015-11-09 | 2018-08-23 | Ｎｅｃソリューションイノベータ株式会社 | Flight control device, flight control method, and program |
-
2022
- 2022-12-14 CN CN202211600968.9A patent/CN115599125B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0613110A1 (en) * | 1993-02-26 | 1994-08-31 | Raytheon Company | Airport incursion avoidance system |
| WO2010125198A1 (en) * | 2009-04-30 | 2010-11-04 | Adb Bvba | Illuminated sign for displaying a command and/or notice for taxiing aircraft traffic at an airport |
| CN102483890A (en) * | 2009-04-30 | 2012-05-30 | Adb有限责任公司 | Illuminated sign for displaying a command and/or notice for taxiing aircraft traffic at an airport |
| CN102567093A (en) * | 2011-12-20 | 2012-07-11 | 广州粤嵌通信科技股份有限公司 | Berth type recognizing method applied in visual berth automatic guiding system |
| CN207969045U (en) * | 2018-03-21 | 2018-10-12 | 大连交通大学 | War preparedness based on wireless communication protocol/emergency airport sailing-assisting lamp system |
| CN109409292A (en) * | 2018-10-26 | 2019-03-01 | 西安电子科技大学 | The heterologous image matching method extracted based on fining characteristic optimization |
| CN110989614A (en) * | 2019-12-18 | 2020-04-10 | 电子科技大学 | Vehicle edge calculation transfer scheduling method based on deep reinforcement learning |
| CN112020183A (en) * | 2020-08-21 | 2020-12-01 | 深圳安航科技有限公司 | Solar navigation-aid light control system for airport |
| CN111935171A (en) * | 2020-08-24 | 2020-11-13 | 南方电网科学研究院有限责任公司 | Terminal security policy selection method based on machine learning under edge calculation |
| CN112597926A (en) * | 2020-12-28 | 2021-04-02 | 广州辰创科技发展有限公司 | Method, device and storage medium for identifying airplane target based on FOD image |
| CN113837097A (en) * | 2021-09-26 | 2021-12-24 | 南京航空航天大学 | Unmanned aerial vehicle edge calculation verification system and method for visual target identification |
| CN115190681A (en) * | 2022-06-14 | 2022-10-14 | 深圳星标科技股份有限公司 | Intelligent navigation aid control system |
Non-Patent Citations (3)
| Title |
|---|
| Runway Lighting and Lighting Control Systems: Example of The Erzincan Airport;Mustafa ŞAHİN;《Journal of New Results in Science》;第26-40页 * |
| 基于统计学习的机场跑道异物检测;邓慧萍;《中国优秀硕士学位论文全文数据库信》;第I138-6410页 * |
| 面向e-引航的近海边缘计算网络优化与仿真;林彬等;《系统仿真学报》;第1989-1996页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115599125A (en) | 2023-01-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115599125B (en) | Navigation aid light control strategy selection method based on edge calculation | |
| CN106027300B (en) | A kind of intelligent robot Parameter Optimization System and method using neural network | |
| CN110120041A (en) | Pavement crack image detecting method | |
| CN110136141A (en) | A kind of image, semantic dividing method and device towards complex environment | |
| CN105551312A (en) | Airport scene traffic auxiliary assistance system and method | |
| CN113569378A (en) | Simulation scene generation method and device, electronic equipment and storage medium | |
| CN107515530A (en) | A kind of Nonlinear Control Allocation method based on depth autoencoder network | |
| US20230065126A1 (en) | Method and apparatus for generating high-precision map, and storage medium | |
| CN112580512A (en) | Lightweight unmanned aerial vehicle target detection method based on channel cutting | |
| CN104123847A (en) | ACP (artificial societies, computational experiments and parallel execution) method-based traffic signal recommendation system and corresponding method | |
| CN109871778A (en) | Lane based on transfer learning keeps control method | |
| CN106599495B (en) | Optimal slip ratio recognition methods based on glowworm swarm algorithm Optimized BP Neural Network | |
| CN108830032A (en) | A kind of unmanned plane weather warning method neural network based | |
| CN111507499B (en) | Method, device and system for constructing model for prediction and testing method | |
| CN109741329A (en) | A kind of point cloud segmentation method towards electric power corridor scene | |
| CN111768493B (en) | Point cloud processing method based on distribution parameter coding | |
| CN115688004B (en) | Target attribute determining method, medium and device based on Hilbert coding | |
| CN115687953B (en) | Target clustering method, medium and device based on Hilbert coding | |
| CN112164248B (en) | Air traffic complexity evaluation method based on flight intention interactive relation | |
| Wu et al. | Slip rate recognition based on firefly optimization algorithm | |
| CN111914923B (en) | Target distributed identification method based on clustering feature extraction | |
| CN114841630B (en) | SaaS cloud platform data processing method and system based on TOMS system | |
| CN117763727A (en) | Stratospheric airship service life prediction method based on data driving | |
| LI et al. | Simulation Analysis of Airport Parallel Runway Capacity under Different Operating Modes | |
| Li et al. | Research on Lightweight Pedestrian Detection Model in Complex Background |
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 |