计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 240900069-7.doi: 10.11896/jsjkx.240900069
孙勇乾, 汤守国
SUN Yongqian, TANG Shouguo
摘要： 为提高烟叶复烤后烟叶的质量,提出了一种基于改进蜣螂优化算法(DBO)-BP神经网络的预测模型,旨在准确预测烟叶复烤过程中的烤机出口含水率和温度。首先,采用灰色关联度分析法分析工艺参数对烤机出口含水率和温度的关联程度,为了提高模型的预测精度和稳定性,引入Circle搜索策略来优化蜣螂算法,使其能够更有效地探索解空间,避免陷入局部最优。其次,用改进的蜣螂算法优化BP神经网络的权重和阈值。最后,建立Circle-DBO-BP复烤烤机出口含水率和温度预测模型。通过MATLAB对Circle-DBO-BP模型进行仿真,并与XGBOOST模型、Tent-DBO-BP模型和SSA-BP模型的预测结果进行了比较。实验结果表明,改进后的Circle-DBO-BP模型络在烟叶复烤出口含水率和温度的预测中,MSE分别达到了0.046 7和0.038 4,从而为烟叶复烤过程的控制提供了有力的支持。
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| [1]LI L Q,CHEN S L.Discussion on the Factors Influencing Moisture Content of Redried Tobacco Leaves [J].Crop Research,2012,26(S1):74-77. [2]TAO H.Expounding the Operation Countermeasures of PLC inTobacco Redrying Production Environment[J].Hebei Agricultural Machinery,2017(3):41-42,44. [3]LI B,WANG Z L,WU Y C,et al.Design of the Process Parameters in the Damp Area of the Hot-ordering Process[J].Tianjin Agricultural Sciences,2023,29(S1):105-110. [4]TANG J,ZHOU B,YI B,et al.Influence and Application Re-search of Ambient Temperature and Humidity in Primary Processing on Tobacco Moisture Content Between Key Processes[J].Hubei Agricultural Sciences,2023,62(8):175-181. [5]YAO S S,ZENG X L,WANG H,et al.The Prediction Model of Balanced Moisture Contents as Well as the Analysis of Mildew of Flue-cured Leaves for Yunyan 87[J].Biological Disaster Science,2022,45(4):456-462. [6]ZHANG H.Application of Big Data Technology in Prediction and Control of Moisture at the Drying Outlet[J].Telecom World,2017(6):249-250. [7]JIN F G,WANG Y L,ZHANG P C,et al.Prediction of Inlet Moisture Content to Tobacco Dryer Based on Random Forest and DE-ELM[J].Control Engineering of China,2020,27(3):532-539. [8]LI Z J,LIU B,GAO Y,et al.Establishment and Detection ofMotion Prediction Model Key Processes of Igarette Cutting Process[J].Food & Machinery,2020,36(10):190-195,205. [9]LI X,QU L,TAN M,et al.Automated essay scoring based on the enhanced chimp optimization algorithm-back propagation(ENChOA-BP) and K-means[J].Multimedia Tools and Applications,2024,(prepublish):1-32. [10]ASCHER M,JONATHAN B,JEANINE S,et al.An Ecological Approach to Modeling Vision:Quantifying Form Perception Using the Circle Map Equation[J].Ecological Psychology,2020,32(1):41-57. [11]GENG X L,YANG Z.Scheme Recommendation Based on Grey Correlation Prediction and Trust Cloud Hybrid Algorithm[J].Computer Integrated Manufacturing Systems,2020,26(4):980-988. [12]RACHANA C,DHWANI A,KRITIKA R,et al.Multi-output incremental back-propagation[J].Neural Computing and Applications,2023,35(20):14897-14910. [13]HUANG L E,WU L S,CHEN H W.Image Blur Types and Parameters Estimation Using DCNN Fusion with the LSTM[J].Journal of Basic Science and Engineering,2018,26(5):1092-1100. [14]AKIRA F.Evaluating Classifier Confidence for Surface EMGPattern Recognition[C]//Annual International Conference of the IEEE Engineering in Medicine and Biology Society.2023:1-4. [15]JAGADISH K N,BALASUBRAMANIAN C.Hybrid Gradient Descent Golden Eagle Optimization(HGDGEO) Algorithm-Based Efficient Heterogeneous Resource Scheduling for Big Data Processing on Clouds[J].Wireless Personal Communications,2023,129(2):1175-1195. [16]PAN J C,LI S B,ZHOU P,et al.Dung Beetle Optimization Algorithm Guided by Improved Sine Algorithm[J].Computer Engineering and Applications,2018,26(5):1092-1100. |
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