CN110309960A - A kind of big data intellectual analysis forecasting system - Google Patents
A kind of big data intellectual analysis forecasting system Download PDFInfo
- Publication number
- CN110309960A CN110309960A CN201910537466.8A CN201910537466A CN110309960A CN 110309960 A CN110309960 A CN 110309960A CN 201910537466 A CN201910537466 A CN 201910537466A CN 110309960 A CN110309960 A CN 110309960A
- Authority
- CN
- China
- Prior art keywords
- big data
- condition
- sensor
- forecasting system
- crops
- 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.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 33
- 238000004519 manufacturing process Methods 0.000 claims abstract description 36
- 239000002689 soil Substances 0.000 claims abstract description 29
- 238000012545 processing Methods 0.000 claims abstract description 24
- 238000004891 communication Methods 0.000 claims abstract description 13
- 238000000034 method Methods 0.000 claims abstract description 13
- 230000003287 optical effect Effects 0.000 claims abstract description 10
- 238000007405 data analysis Methods 0.000 claims abstract description 4
- 238000005286 illumination Methods 0.000 claims description 14
- 230000009286 beneficial effect Effects 0.000 claims description 8
- 238000013461 design Methods 0.000 abstract description 2
- 238000011835 investigation Methods 0.000 description 2
- 229920000742 Cotton Polymers 0.000 description 1
- 244000068988 Glycine max Species 0.000 description 1
- 235000010469 Glycine max Nutrition 0.000 description 1
- 244000017020 Ipomoea batatas Species 0.000 description 1
- 235000002678 Ipomoea batatas Nutrition 0.000 description 1
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 240000006394 Sorghum bicolor Species 0.000 description 1
- 235000011684 Sorghum saccharatum Nutrition 0.000 description 1
- 244000062793 Sorghum vulgare Species 0.000 description 1
- 235000021307 Triticum Nutrition 0.000 description 1
- 244000098338 Triticum aestivum Species 0.000 description 1
- 240000008042 Zea mays Species 0.000 description 1
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 1
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 1
- 238000012271 agricultural production Methods 0.000 description 1
- 235000005822 corn Nutrition 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 235000019713 millet Nutrition 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Animal Husbandry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Mining & Mineral Resources (AREA)
- General Health & Medical Sciences (AREA)
- Marine Sciences & Fisheries (AREA)
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of big data intellectual analysis forecasting system, including processor, soil sensor, optical sensor, temperature sensor, communication interface, big data processing module and database, the processor is electrically connected with soil sensor, optical sensor, temperature sensor, communication interface, big data processing module and database respectively, the implementation method of this big data intellectual analysis forecasting system is the following steps are included: acquisition of information, big data analysis processing, production forecast, treatment advice；Big data intellectual analysis forecasting system design is reasonable, its yield can be predicted according to the growth conditions of crops, be conducive to handle the sale etc. after crop maturity, and treatment advice can be provided for some growth conditions, to achieve the purpose that improve yield.
Description
Technical field
The invention belongs to big data technical field, in particular to a kind of big data intellectual analysis forecasting system.
Background technique
Big data refers to the data that can not be captured, managed and be handled with conventional software tool within the scope of certain time
Set is magnanimity, the Gao Zeng for needing new tupe that could have stronger decision edge, see clearly discovery power and process optimization ability
Long rate and diversified information assets, crops forecast production are the productions that certain method measured in advance is taken before crop harvesting
Amount, China takes region-by-region, is allocated as object, obtains prediction data in the method for different stages of growth point estimated investigation several times, presses
" national agricultural production amount scheme of sample survey " that nineteen eighty-two comes into effect regulation, to wheat, rice, corn, sorghum, millet, sweet potato,
The chief crops such as cotton and the soybean of northeast each province take province to take out county, people's commune (small towns) is taken out in county, the production team is taken out by people's commune (small towns)
Five sections of equidistant sampling methods in plot, plot sample point are taken out in village, the production team (village), are sampled investigation, crops forecast production
There is very important reference value to procurement of agricultural product plan is worked out, still, current crops forecast production is merely able to
Crop maturity is predicted later, also, can not carry out a system according to the gap between the yield and optimum point of production of prediction
The adjustment of column is to improve yield, for this purpose, the present invention proposes a kind of big data intellectual analysis forecasting system.
Summary of the invention
Of the existing technology in order to solve the problems, such as, the present invention provides a kind of big data intellectual analysis forecasting systems, should
The design of big data intellectual analysis forecasting system rationally, can predict its yield according to the growth conditions of crops, favorably
It is handled in the sale etc. after crop maturity, and treatment advice can be provided for some growth conditions, mentioned to reach
The purpose of high yield.
To achieve the goals above, the present invention is to realize by the following technical solutions: a kind of big data intellectual analysis
Forecasting system, including processor, soil sensor, optical sensor, temperature sensor, communication interface, big data processing module
And database, the processor are handled with soil sensor, optical sensor, temperature sensor, communication interface, big data respectively
Module and database are electrically connected, the implementation method of this big data intellectual analysis forecasting system the following steps are included:
Step 1: acquisition of information；Communication interface connects weather forecast system, acquires weather condition, soil sensor, illumination
Sensor and temperature sensor are for acquiring edaphic condition, illumination condition and air temperature conditions, and then processor is by various letters
Breath is deposited into database, and according to the property of crop growth condition, growth conditions is divided into:
1. contingent condition: the edaphic condition that can be changed by artificial means；
2. immutable condition: the weather conditions of artificial means change, including weather condition, illumination item can not be easily passed through
Part and air temperature conditions etc.；
Step 2: big data analysis processing；The yield and various growth conditions data for inputting various crops, at big data
The relationship between the yield and various growth conditions of module analysis processing crops is managed, crop yield prediction model is established；
Step 3: production forecast；Then big data processing module is by collected edaphic condition, weather condition, illumination item
Part and air temperature conditions input crop yield prediction model, predict the yield of crops, obtain forecast production, so
Forecast production and the optimum point of production of the crops are compared afterwards；
Step 4: treatment advice；If differed greatly between forecast production and optimum point of production, big data processing module pair
Than collected edaphic condition and most beneficial for crops growth edaphic condition, obtain between difference, then according to difference
It provides and targetedly suggests.
As a kind of preferred embodiment of the invention, the soil sensor includes soil moisture sensor, soil moisture content biography
The sensors such as sensor, soil temperature sensor and soil salinity sensor.
As a kind of preferred embodiment of the invention, the database is relevant database.
As a kind of preferred embodiment of the invention, the specific aim suggestion in the step 4 refers to be proposed for different crops
Most beneficial for the suggestion of its growth.
As a kind of preferred embodiment of the invention, in the step 4, if it is volume variance caused by immutable condition,
Then provide the suggestion such as safeguard procedures.
Beneficial effects of the present invention: big data intellectual analysis forecasting system includes processor, soil biography in of the invention one
Sensor, optical sensor, temperature sensor, communication interface, big data processing module and database.
1, this big data intellectual analysis forecasting system can pass through acquisition edaphic condition, weather condition, illumination condition and sky
Temperature degree condition entry crop yield prediction model, predicts the yield of crops, so as to predicting earlier
Crop yield is more advantageous to and works out procurement of agricultural product plan, has more very important reference value.
2, this big data intellectual analysis forecasting system can carry out production forecast in each stage of crop growth, pre-
During survey, the difference between forecast production and optimum point of production can be derived that, and obtain the reason of causing difference, then basis
Reason proposes specific aim suggestion, and the yield for being conducive to crops is promoted.
3, this big data intellectual analysis forecasting system in use, with increasing for sample data, can make system
The accuracy of itself is higher and higher, practical.
Detailed description of the invention
Fig. 1 is a kind of functional block diagram of big data intellectual analysis forecasting system；
Fig. 2 is a kind of step flow chart of big data intellectual analysis forecasting system.
Specific embodiment
To be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, below with reference to
Specific embodiment, the present invention is further explained.
Fig. 1 to Fig. 2 is please referred to, the present invention provides a kind of technical solution: a kind of big data intellectual analysis forecasting system, including
Processor 1, soil sensor 2, optical sensor 3, temperature sensor 4, communication interface 5, big data processing module 6 and database
7, the processor 1 handles mould with soil sensor 2, optical sensor 3, temperature sensor 4, communication interface 5, big data respectively
Block 6 and database 7 are electrically connected, the implementation method of this big data intellectual analysis forecasting system the following steps are included:
Step 1: acquisition of information；Communication interface 5 connects weather forecast system, acquires weather condition, soil sensor 2, light
According to sensor 3 and temperature sensor 4 for acquiring edaphic condition, illumination condition and air temperature conditions, then processor 1 will be each
Kind information is deposited into database 7, and according to the property of crop growth condition, growth conditions is divided into:
1. contingent condition: the edaphic condition that can be changed by artificial means；
2. immutable condition: the weather conditions of artificial means change, including weather condition, illumination item can not be easily passed through
Part and air temperature conditions etc.；
Step 2: big data analysis processing；The yield and various growth conditions data for inputting various crops, at big data
The relationship between the yield and various growth conditions of the analysis processing crops of module 6 is managed, crop yield prediction model is established；
Step 3: production forecast；Then big data processing module 6 is by collected edaphic condition, weather condition, illumination item
Part and air temperature conditions input crop yield prediction model, predict the yield of crops, obtain forecast production, so
Forecast production and the optimum point of production of the crops are compared afterwards；
Step 4: treatment advice；If differed greatly between forecast production and optimum point of production, big data processing module 6
Compare collected edaphic condition and most beneficial for crops growth edaphic condition, obtain between difference, then according to difference
Value, which provides, targetedly suggests.
The soil sensor 2 includes soil moisture sensor, soil moisture content sensor, soil temperature sensor and soil
The sensors such as salt sub-sensor.
As a kind of preferred embodiment of the invention, the database 7 is relevant database.
As a kind of preferred embodiment of the invention, the specific aim suggestion in the step 4 refers to be proposed for different crops
Most beneficial for the suggestion of its growth.
As a kind of preferred embodiment of the invention, in the step 4, if it is volume variance caused by immutable condition,
Then provide the suggestion such as safeguard procedures.
Working principle: when using this big data intellectual analysis forecasting system, firstly, by communication interface 5 and weather forecast
System connection acquires weather condition, and soil sensor 2, optical sensor 3 and temperature sensor 4 are for acquiring edaphic condition, light
According to condition and air temperature conditions, then various information are deposited into database 7 by processor 1, according to crop growth condition
Property, growth conditions is divided into: 1. contingent condition: the edaphic condition that can be changed by artificial means；2. immutable condition:
The weather conditions, including weather condition, illumination condition and air temperature conditions etc. of artificial means change can not be easily passed through, it is defeated
Enter the yield and various growth conditions data of various crops, the yield of the analysis processing crops of big data processing module 6 and each
Relationship between kind of growth conditions, establishes crop yield prediction model, and then big data processing module 6 is by collected soil
Condition, weather condition, illumination condition and air temperature conditions input crop yield prediction model, carry out to the yield of crops
Prediction, obtains forecast production, then compares forecast production and the optimum point of production of the crops, if forecast production and most
It differs greatly between good yield, then big data processing module 6 compares collected edaphic condition and grows up most beneficial for crops
Edaphic condition, obtain between difference, then provided according to difference and targetedly suggested, if it is caused by immutable condition
Volume variance, then provide the suggestion such as safeguard procedures, this big data intellectual analysis forecasting system can be by acquiring edaphic condition, day
Gas bar part, illumination condition and air temperature conditions input crop yield prediction model, predict the yield of crops, from
And crop yield can be predicted earlier, it is more advantageous to procurement of agricultural product plan of working out, there is more very important reference
Value, this big data intellectual analysis forecasting system can carry out production forecast in each stage of crop growth, in prediction
In the process, it can be derived that the difference between forecast production and optimum point of production, and obtain the reason of causing difference, then according to reason
It is proposed specific aim suggestion, be conducive to crops yield promoted, this big data intellectual analysis forecasting system in use, with
Increasing for sample data, the accuracy of system itself can be made higher and higher, it is practical.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention, for this field skill
For art personnel, it is clear that invention is not limited to the details of the above exemplary embodiments, and without departing substantially from spirit of the invention or
In the case where essential characteristic, the present invention can be realized in other specific forms.Therefore, in all respects, should all incite somebody to action
Embodiment regards exemplary as, and is non-limiting, the scope of the present invention by appended claims rather than on state
Bright restriction, it is intended that including all changes that fall within the meaning and scope of the equivalent elements of the claims in the present invention
It is interior.Any reference signs in the claims should not be construed as limiting the involved claims.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only wrapped
Containing an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should
It considers the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms those skilled in the art
The other embodiments being understood that.
Claims (5)
1. a kind of big data intellectual analysis forecasting system, including processor (1), soil sensor (2), optical sensor (3), temperature
Spend sensor (4), communication interface (5), big data processing module (6) and database (7), which is characterized in that the processor (1)
Respectively with soil sensor (2), optical sensor (3), temperature sensor (4), communication interface (5), big data processing module (6)
Be electrically connected with database (7), the implementation method of this big data intellectual analysis forecasting system the following steps are included:
Step 1: acquisition of information；Communication interface (5) connects weather forecast system, acquires weather condition, soil sensor (2), light
It is used to acquire edaphic condition, illumination condition and air temperature conditions according to sensor (3) and temperature sensor (4), then processor
(1) various information are deposited into database (7), according to the property of crop growth condition, growth conditions are divided into:
1. contingent condition: the edaphic condition that can be changed by artificial means；
2. immutable condition: can not easily pass through artificial means change weather conditions, including weather condition, illumination condition and
Air temperature conditions etc.；
Step 2: big data analysis processing；The yield and various growth conditions data of various crops are inputted, big data handles mould
Relationship between the yield and various growth conditions of block (6) analysis processing crops, establishes crop yield prediction model；
Step 3: production forecast；Then big data processing module (6) is by collected edaphic condition, weather condition, illumination condition
Crop yield prediction model is inputted with air temperature conditions, the yield of crops is predicted, obtains forecast production, then
Forecast production and the optimum point of production of the crops are compared；
Step 4: treatment advice；If differed greatly between forecast production and optimum point of production, big data processing module (6) is right
Than collected edaphic condition and most beneficial for crops growth edaphic condition, obtain between difference, then according to difference
It provides and targetedly suggests.
2. a kind of big data intellectual analysis forecasting system according to claim 1, it is characterised in that: the soil sensor
It (2) include the sensors such as soil moisture sensor, soil moisture content sensor, soil temperature sensor and soil salinity sensor.
3. a kind of big data intellectual analysis forecasting system according to claim 1, it is characterised in that: the database (7)
For relevant database.
4. a kind of big data intellectual analysis forecasting system according to claim 1, it is characterised in that: in the step 4
Specific aim suggestion refers to the suggestion proposed for different crops most beneficial for its growth.
5. a kind of big data intellectual analysis forecasting system according to claim 1, it is characterised in that: in the step 4,
If it is volume variance caused by immutable condition, the suggestion such as safeguard procedures is provided.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910537466.8A CN110309960A (en) | 2019-06-20 | 2019-06-20 | A kind of big data intellectual analysis forecasting system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910537466.8A CN110309960A (en) | 2019-06-20 | 2019-06-20 | A kind of big data intellectual analysis forecasting system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110309960A true CN110309960A (en) | 2019-10-08 |
Family
ID=68076549
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910537466.8A Pending CN110309960A (en) | 2019-06-20 | 2019-06-20 | A kind of big data intellectual analysis forecasting system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110309960A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111401613A (en) * | 2020-03-06 | 2020-07-10 | 黑龙江力苗科技开发有限公司 | Greenhouse crop yield forecasting method |
| CN111985728A (en) * | 2020-09-07 | 2020-11-24 | 浪潮软件股份有限公司 | Method for establishing organic sorghum yield prediction model |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104766135A (en) * | 2015-03-25 | 2015-07-08 | 中国农业科学院农业信息研究所 | Method, device and system for predicting crop yield |
| CN106060174A (en) * | 2016-07-27 | 2016-10-26 | 昆山阳翎机器人科技有限公司 | Data analysis based agricultural guidance system |
| CN107807540A (en) * | 2017-10-16 | 2018-03-16 | 吉林农业大学 | A kind of agriculture intelligent platform based on image procossing |
| CN109508824A (en) * | 2018-11-07 | 2019-03-22 | 西京学院 | A kind of detection of crop growth situation and yield predictor method |
-
2019
- 2019-06-20 CN CN201910537466.8A patent/CN110309960A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104766135A (en) * | 2015-03-25 | 2015-07-08 | 中国农业科学院农业信息研究所 | Method, device and system for predicting crop yield |
| CN106060174A (en) * | 2016-07-27 | 2016-10-26 | 昆山阳翎机器人科技有限公司 | Data analysis based agricultural guidance system |
| CN107807540A (en) * | 2017-10-16 | 2018-03-16 | 吉林农业大学 | A kind of agriculture intelligent platform based on image procossing |
| CN109508824A (en) * | 2018-11-07 | 2019-03-22 | 西京学院 | A kind of detection of crop growth situation and yield predictor method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111401613A (en) * | 2020-03-06 | 2020-07-10 | 黑龙江力苗科技开发有限公司 | Greenhouse crop yield forecasting method |
| CN111985728A (en) * | 2020-09-07 | 2020-11-24 | 浪潮软件股份有限公司 | Method for establishing organic sorghum yield prediction model |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Channe et al. | Multidisciplinary model for smart agriculture using internet-of-things (IoT), sensors, cloud-computing, mobile-computing & big-data analysis | |
| JP6753936B2 (en) | Information processing equipment and information processing system | |
| Fan et al. | The future of Internet of Things in agriculture: Plant high-throughput phenotypic platform | |
| CN107219827B (en) | Rice food full-industry chain information system, establishment method and application | |
| CN104381205B (en) | A kind of sheep growth monitoring and information service cloud platform integrated system based on Internet of Things | |
| CN109738435B (en) | Buckwheat growth monitoring diagnosis and yield prediction method | |
| CN106406178A (en) | Greenhouse crop growth information real-time peer-to-peer monitoring device and monitoring method | |
| Shinde et al. | Review paper on prediction of crop disease using IoT and machine learning | |
| CN106131770B (en) | A kind of data fusion method of the wireless sensor network for greenhouse | |
| CN110109193A (en) | A kind of eggplant greenhouse temperature intellectualized detection device based on DRNN neural network | |
| CN110309960A (en) | A kind of big data intellectual analysis forecasting system | |
| CN116664332B (en) | Agricultural production monitoring system based on digital twinning | |
| CN110119169A (en) | A kind of tomato greenhouse temperature intelligent early warning system based on minimum vector machine | |
| CN117391482B (en) | Greenhouse temperature intelligent early warning method and system based on big data monitoring | |
| CN110514248A (en) | A kind of intelligence based on big data, automation agricultural data acquisition system | |
| CN115018105A (en) | Winter wheat meteorological yield prediction method and system | |
| CN116661530B (en) | Intelligent control system and method in edible fungus industrial cultivation | |
| CN115115126A (en) | Crop disaster loss and yield prediction system and method based on knowledge graph | |
| CN116703083B (en) | Controllable agricultural cultivation management system and method based on artificial intelligence | |
| CN116776290A (en) | Tobacco big data model construction method | |
| CN114460080A (en) | Rice disease and pest intelligent monitoring system | |
| CN110414859B (en) | 5T evaluation method for rice storage operation based on Internet of things technology | |
| AU2021105327A4 (en) | A computer implemented and IoT based method for increasing crop production using machine learning model | |
| CN112581302A (en) | Agricultural thing allies oneself with management monitoring system | |
| CN116182945B (en) | Controllable agricultural greenhouse environment monitoring system and method based on wireless sensor network |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191008 |
|
| RJ01 | Rejection of invention patent application after publication |