Chenyingyi

Prof. Chen is mainly engaged in the cross-application research of computer science and technology and intelligent agriculture, and has carried out long-term research work in the fields of agricultural Internet of Things and digital agricultural model. In particular, he has carried out a lot of frontier exploration work in the fields of prediction model of change of aquatic environmental factors in aquaculture by artificial intelligence algorithm, fish individual and behavior identification, etc.

(1)  Member of Chinese Society of Agricultural Engineering

(2)  Editorial Board of the International Journal of Information Processing in Agriculture

(3)  Member of Youth Workers Committee of China Simulation Society (3rd session)

(4) Member of the special committee of advanced information processing in agriculture, international federation  of information processing

(5)  Senior member of Chinese Society of Artificial Intelligence

Computer Science and Technology, Agricultural Internet of Things, Agricultural Information Technology

（1）Introduction to the Agricultural Internet of Things

（2）Database principles and practices

（3）Principles of Database

（4）Compilation principle

（5）Writing Scientific and Technical Paper

（6）Database Curriculum Design

（7）College Computer Fundamentals, 2014-2015, first semester, Monday, East Campus

（8）Artificial intelligence (ai)

（9）Web page creation

Papers published in recent years

[1]Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review[J]. Archives of Computational Methods in Engineering, 2020:1-32.

[2] Y Chen, Song L, Y Liu, et al. A Review of the Artificial Neural Network Models for Water Quality Prediction[J]. Applied Sciences, 2020, 10(17):5776.

[3] Zhang Q, Liu Y, Gong C, et al. Applications of Deep Learning for Dense Scenes Analysis in Agriculture: A Review[J]. Sensors, 2020, 20(5):1520.

[4] Ylac D, Hy B, Cgac D, et al. A real time expert system for anomaly detection of aerators based on computer vision and surveillance cameras - ScienceDirect[J]. Journal of Visual Communication and Image Representation, 68.

[5] Liu Y, Gong C, Yang L, et al. DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series prediction[J]. Expert Systems with Application, 2020, 143(Apr.):113082.1-113082.12.

[6] Liu Y, Zhang Q, Song L, et al. Attention-based recurrent neural networks for accurate short-term and long-term dissolved oxygen prediction[J]. Computers and Electronics in Agriculture, 2019, 165:104964.

[7] Chen Y, Cheng Q, Cheng Y, et al. Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review[J]. Neural Computation, 2018, 30(11):1-27.

[8] Liu Y, Chen Y, Fang X. A Review of Turbidity Detection Based on Computer Vision[J]. IEEE Access, 2018, PP(99):1-1.

[9] Chen Y, Yu H, Cheng Y,et al. A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture[J]. Plos One, 2018, 13(2):e0192456.

[10] Li, Daoliang, Chen, et al. Three-Dimensional Short-Term Prediction Model of Dissolved Oxygen Content Based on PSO-BPANN Algorithm Coupled with Kriging Interpolation[J]. Mathematical Problems in Engineering Theory Methods & Applications, 2016.

Software works published in recent years

1. Shrimp processing and detection system, 2021SRBJ47475SR

2. Intelligent detection system of water transparency, 2020SRBJ46834

3. Human-machine intelligent question answering system V1.0, 2019SRBJ45712

4. Automatic identification and condition monitoring system of aerator v1.0, 2018SRBJ44234

5. Fish individual recognition and location system based on convolution neural network, 2018SRBJ44278

6. Image file management system based on multi-source data, 2018SRBJ44272

7. Big data analysis system of water quality parameters, 2017SRBJ43727

8. Intelligent push system for aquaculture, 2017SRBJ42701

9. Intelligent feeding system for aquaculture, 2017SRBJ42700

10. Intelligent push system of aquaculture information, 2016SRBJ42701

Patents published in recent years

1.Detection method and system of aerator working state, 201810509219.2

2.Method and device for predicting ammonia nitrogen in water body based on deep confidence network, 201810482608.0

3.Prediction method of regional corn maturity period based on time series LAI curve integral area, 201710539044.5

4.The heating method of shade shed in double sided greenhouse and the double sided greenhouse with automatic heat storage and release, 201510445484.5

5.A kind of shade covering layer based on mushroom vegetable double sided greenhouse and its construction method,201510087860.8

6. A method for diagnosing leaf vegetable diseases,201510073648.6

7.Double sided greenhouse with automatic heat storage and release, 201520550403.3

8.Early warning method and device for lettuce disease in facility,201510102239.4

9.A key frame extraction method for greenhouse vegetable disease monitoring video: extraction system,201410191244.2

10.A prediction method of extreme temperature in Greenhouse,201410042738.4

11.A temperature early warning method in intelligent monitoring system of solar greenhouse environment, 201410286350.9

12.A method of greenhouse vegetable video push for mobile terminal,201410307316.5

13.A method of crop yield estimation based on scale transformation and data assimilation, 201410155913.0

14.Early warning method and system for facility spinach disease,201410225345.7

Representative honor

1.December 18, 2019, State Council of the PRC, the second prize of National Science and Technology Progress Award

2.May 5, 2017, Shandong Provincial People's Government, the first prize of Shandong Science and Technology Award

3.December 1, 2016, Ministry of Agriculture, the first prize of national harvest award for agriculture, animal husbandry and fishery

4.November 1, 2015, Beijing Dabeinong Technology Group Co., Ltd.,the second prize of DaBeiNong Innovation Award

5.February 1, 2015, Ministry of Education, Second prize of science and technology progress award of Ministry of Education