| Citation: | Huawei JIANG, Lei ZHANG. Multi-index Prediction Model of Wheat Quality Based on Long Short-Term Memory and Generative Adversarial Network[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2865-2872. doi: 10.11999/JEIT190802
|
The change trend of multi-index of wheat reflects the deterioration state of storage quality, while the predicted multi-index data will produce large errors due to its correlation and interaction. For this reason, an improved Long Short-Term Memory and Generative Adversarial Network(LSTM-GAN) model is proposed. The deterioration trend of different time series data of multi-index is predicted by Long Short-Term Memory(LSTM) network, and the improved model may reduce comprehensive prediction error by using Generative Adversarial Network(GAN) according to the correlation of multi-index. Finally, the prediction results obtained by optimizing the objective function and model structure. The experimental analysis shows that the training sequence length and structural parameters of the optimization model can effectively reduce the error of the prediction result. The deterioration of wheat quality under certain conditions will increase the prediction error of multi-index. Therefore, the influence of environmental changes during storage period on multi-index data should be fully considered. The comprehensive error of the LSTM-GAN model is reduced by 9.745% compared with the LSTM prediction and lower than multiple comparison models, which can improve the prediction of wheat quality indexes.
|
KALSA K K, SUBRAMANYAM B, DEMISSIE G, et al. Evaluation of postharvest preservation strategies for stored wheat seed in Ethiopia[J]. Journal of Stored Products Research, 2019, 81: 53–61. doi: 10.1016/j.jspr.2019.01.001
|
|
ZHANG Shuaibing, LÜ Yangyong, WANG Yuli, et al. Physiochemical changes in wheat of different hardnesses during storage[J]. Journal of Stored Products Research, 2017, 72: 161–165. doi: 10.1016/j.jspr.2017.05.002
|
|
陈红松, 陈京九. 基于循环神经网络的无线网络入侵检测分类模型构建与优化研究[J]. 电子与信息学报, 2019, 41(6): 1427–1433. doi: 10.11999/JEIT180691
CHEN Hongsong and CHEN Jingjiu. Recurrent neural networks based wireless network intrusion detection and classification model construction and optimization[J]. Journal of Electronics &Information Technology, 2019, 41(6): 1427–1433. doi: 10.11999/JEIT180691
|
|
XU Peng, DU Rui, ZHANG Zhongbao, et al. Predicting pipeline leakage in petrochemical system through GAN and LSTM[J]. Knowledge-Based Systems, 2019, 175: 50–61. doi: 10.1016/j.knosys.2019.03.013
|
|
MAHASSENI B, LAM M, and TODOROVIC S. Unsupervised video summarization with adversarial lstm networks[C]. 2017 IEEE conference on Computer Vision and Pattern Recognition, Honolulu, USA, 2017: 2982–2991. doi: 10.1109/CVPR.2017.318.
|
|
YANG Yang, ZHOU Jie, AI Jiangbo, et al. Video captioning by adversarial LSTM[J]. IEEE Transactions on Image Processing, 2018, 27(11): 5600–5611. doi: 10.1109/TIP.2018.2855422
|
|
GOODFELLOW I J, POUGET-ABADIE J, MIRZA M, et al. Generative adversarial nets[C]. The 27th International Conference on Neural Information Processing Systems, Montreal, Canada, 2014: 2672–2680.
|
|
曹志义, 牛少彰, 张继威. 基于半监督学习生成对抗网络的人脸还原算法研究[J]. 电子与信息学报, 2018, 40(2): 323–330. doi: 10.11999/JEIT170357
CAO Zhiyi, NIU Shaozhang, and ZHANG Jiwei. Research on face reduction algorithm based on generative adversarial nets with semi-supervised learning[J]. Journal of Electronics &Information Technology, 2018, 40(2): 323–330. doi: 10.11999/JEIT170357
|
|
蒋华伟, 张磊, 周同星. 基于信息熵的小麦储藏品质多指标权重模型研究[J]. 中国粮油学报, 2020, 35(6): 105–113. doi: 10.3969/j.issn.1003-0174.2020.06.016
JIANG Huawei, ZHANG Lei, and ZHOU Tongxing. Research on multi-index weight model of wheat storage quality based on information entropy[J]. Journal of the Chinese Cereals and Oils Association, 2020, 35(6): 105–113. doi: 10.3969/j.issn.1003-0174.2020.06.016
|
|
刘威, 刘尚, 白润才, 等. 互学习神经网络训练方法研究[J]. 计算机学报, 2017, 40(6): 1291–1308. doi: 10.11897/SP.J.1016.2017.01291
LIU Wei, LIU Shang, BAI Runcai, et al. Research of mutual learning neural network training method[J]. Chinese Journal of Computers, 2017, 40(6): 1291–1308. doi: 10.11897/SP.J.1016.2017.01291
|
|
高艳娜. 小麦产后品质变化规律研究[D]. [硕士论文], 河南工业大学, 2010.
GAO Yanna. Study on the changes of postpartum quality in wheat[D]. [Master dissertation], Henan University of Technology, 2010.
|
|
FRIEDMAN L and KOMOGORTSEV O V. Assessment of the effectiveness of seven biometric feature normalization techniques[J]. IEEE Transactions on Information Forensics and Security, 2019, 14(10): 2528–2536. doi: 10.1109/TIFS.2019.2904844
|
|
GREFF K, SRIVASTAVA R K, KOUTNÍK J, et al. LSTM: A search space odyssey[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(10): 2222–2232. doi: 10.1109/TNNLS.2016.2582924
|
|
FANG Tingting and LAHDELMA R. Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system[J]. Applied Energy, 2016, 179: 544–552. doi: 10.1016/j.apenergy.2016.06.133
|
|
XU Jie, XU Chen, ZOU Bin, et al. New incremental learning algorithm with support vector machines[J]. IEEE Transactions on Systems, Man, and Cybernetics; Systems, 2019, 49(11): 2230–2241. doi: 10.1109/tsmc.2018.2791511
|
|
VILLARRUBIA G, DE PAZ J F, CHAMOSO P, et al. Artificial neural networks used in optimization problems[J]. Neurocomputing, 2018, 272: 10–16. doi: 10.1016/j.neucom.2017.04.075
|
|
DING Song, HIPEL K W, and DANG Yaoguo. Forecasting China’s electricity consumption using a new grey prediction model[J]. Energy, 2018, 149: 314–328. doi: 10.1016/j.energy.2018.01.169
|
Figures(3) / Tables(5)
DownLoad:
