中国科学院自动化研究所机构知识库(CASIA OpenIR): 工业智能技术与系统

CASIA OpenIR > 综合信息系统研究中心 > 工业智能技术与系统

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1. A data-based optimal setting method for the coking flue gas denitration process

[38]

2. Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ens..

[20]

3. Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio..

[15]

4. Very Short-Term Solar Generation Forecasting Based on LSTM with Temporal Attention..

[12]

5. Identification of Power Quality Disturbance Sources using Gradient Boosting Decisi..

[12]

6. Probabilistic Prediction of Solar Generation Based on Stacked Autoencoder and Lowe..

[11]

7. Short-Term Solar Power Generation Forecasting Via Continuous Conditional Random Fi..

[10]

8. An Exposure Fusion-Based Structured Light Approach for the 3D Measurement of a Spe..

[10]

9. Cross-domain few-shot learning approach for lithium-ion battery surface defects cl..

[10]

10. Few-shot learning approach for 3D defect detection in lithium battery

[8]

1. A data-based optimal setting method for the coking flue gas denitration process

[19]

2. Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Ti..

[2]

3. An Exposure Fusion-Based Structured Light Approach for the 3D Measurement of a Spe..

[2]

4. Modeling and Feedforwad Control of Flue Gas Denitration in Coking Reversing Proces..

[1]

5. Intelligent integrated coking flue gas indices prediction

[1]

6. Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio..

[1]

7. Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ens..

[1]

8. Colored Structured Light Patterns with Binocular Cameras for Fast and Low-cost 3-D..

[1]

9. Identification of Power Quality Disturbance Sources using Gradient Boosting Decisi..

[1]

10. A novel approach to obtain optimal exposure for 3D shape reconstruction of high dy..

[1]

1. Modeling and Feedforwad Control of Flue Gas Denitration in Coking Reversing Proces..

[1]

2. Colored Structured Light Patterns with Binocular Cameras for Fast and Low-cost 3-D..

[1]

Authors & Scholar Pages

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