CN116805160A - 用于训练神经网络以确定代表设备的磨损状态的特征向量的方法 - Google Patents
用于训练神经网络以确定代表设备的磨损状态的特征向量的方法 Download PDFInfo
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- CN116805160A CN116805160A CN202310302880.7A CN202310302880A CN116805160A CN 116805160 A CN116805160 A CN 116805160A CN 202310302880 A CN202310302880 A CN 202310302880A CN 116805160 A CN116805160 A CN 116805160A
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- 239000013598 vector Substances 0.000 title claims abstract description 69
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 57
- 238000012549 training Methods 0.000 title claims abstract description 37
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- 238000012545 processing Methods 0.000 claims abstract description 21
- 238000012544 monitoring process Methods 0.000 claims description 27
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- 238000004590 computer program Methods 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 description 27
- 239000007795 chemical reaction product Substances 0.000 description 18
- 238000010801 machine learning Methods 0.000 description 8
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- 238000012935 Averaging Methods 0.000 description 1
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102022202984.4A DE102022202984B3 (de) | 2022-03-25 | 2022-03-25 | Verfahren zum Trainieren eines neuronalen Netzwerks zum Ermitteln eines Merkmalsvektors, der den Abnutzungszustand einer Vorrichtung repräsentiert |
| DE102022202984.4 | 2022-03-25 |
Publications (1)
| Publication Number | Publication Date |
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| CN116805160A true CN116805160A (zh) | 2023-09-26 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202310302880.7A Pending CN116805160A (zh) | 2022-03-25 | 2023-03-23 | 用于训练神经网络以确定代表设备的磨损状态的特征向量的方法 |
Country Status (2)
| Country | Link |
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| CN (1) | CN116805160A (de) |
| DE (1) | DE102022202984B3 (de) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117765779A (zh) * | 2024-02-20 | 2024-03-26 | 厦门三读教育科技有限公司 | 基于孪生神经网络的儿童绘本智能化导读方法及系统 |
-
2022
- 2022-03-25 DE DE102022202984.4A patent/DE102022202984B3/de active Active
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2023
- 2023-03-23 CN CN202310302880.7A patent/CN116805160A/zh active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117765779A (zh) * | 2024-02-20 | 2024-03-26 | 厦门三读教育科技有限公司 | 基于孪生神经网络的儿童绘本智能化导读方法及系统 |
| CN117765779B (zh) * | 2024-02-20 | 2024-04-30 | 厦门三读教育科技有限公司 | 基于孪生神经网络的儿童绘本智能化导读方法及系统 |
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| Publication number | Publication date |
|---|---|
| DE102022202984B3 (de) | 2023-08-31 |
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