基于环境因子的设施黄瓜通风控制模型

doi:10.13304/j.nykjdb.2022.0035

中国农业科技导报 ›› 2023, Vol. 25 ›› Issue (12): 103-110.DOI: 10.13304/j.nykjdb.2022.0035

基于环境因子的设施黄瓜通风控制模型

刘鹏菊¹(), 柳平增¹(), 张大磊², 张艳¹, 李辉¹, 刘力宁¹, 丁方军³

^1.山东农业大学信息科学与工程学院农业大数据研究中心，山东泰安 271000
^2.泰山科技学院教务处，山东泰安 271000
^3.山东农业肥业科技有限公司，山东泰安 271000

收稿日期:2022-01-13 接受日期:2022-04-12 出版日期:2023-12-15 发布日期:2023-12-12
通讯作者: 柳平增
作者简介:刘鹏菊 E-mail： 2841430017@qq.com；
基金资助:
山东省重大科技创新工程项目(2019JZZY010713);2019年度山东省重点研发计划项目(2019GNC106103);山东省农业重大应用技术创新项目(SD2019ZZ019);山东省科技特派员项目(2020KJTPY078)

Ventilation Control Model of Cucumber in Facility Based on Environmental Factors

Pengju LIU¹(), Pingzeng LIU¹(), Dalei ZHANG², Yan ZHANG¹, Hui LI¹, Lining LIU¹, Fangjun DING³

^1.Big Data Research Center，College of Information Science and Engineering，Shandong Agricultural University，Shandong Tai’an 271000，China
^2.Office of Academic Affairs，Taishan College of Science and Technology，Shandong Tai ’an 271000，China
^3.Shandong Agricultural Fertilizer Technology Co. ，Ltd. ，Shandong Tai ’an 271000，China

Received:2022-01-13 Accepted:2022-04-12 Online:2023-12-15 Published:2023-12-12
Contact: Pingzeng LIU

摘要/Abstract

摘要：

为实现设施黄瓜温室风口开度大小的精准控制，对温室内温度变化趋势进行了预测研究。将温室风口开度大小状态和温室内外各环境因子作为输入因子，利用逐步回归的方法构建温室温度预测模型，模型决定系数R² 最小为0.941。采用主成分分析方法建立黄瓜长势关系表达式，然后利用Lasso回归构建基于环境因子的设施黄瓜生长模型。将温室温度预测模型与设施黄瓜生长模型相结合，最终构建了设施黄瓜温室专用风口控制模型，实现了温室风口开度大小的自动控制，提升了设施黄瓜温室的智能化管理水平。

关键词: 温室风口, 逐步回归, 预测, Lasso, 自动控制

Abstract:

To precisely control the opening size of the cucumber greenhouse air vents in facilities， this paper studied prediction of temperature change in greenhouse. Taking the opening size and greenhouse tuyere both inside and outside environment factor as input factors， temperature prediction model was built by the method of stepwise regression.The results showed that the minimum determination coefficient R² was 0.941. Principal component analysis was used to establish the expression of cucumber growth potential， and Lasso regression method was used to build the greenhouse cucumber growth model based on environmental factors. Finally， the temperature prediction model was combined with the cucumber growth model to construct special tuyere control model， which realized the automatic control of the tuyere opening size of the greenhouse， and then improved the intelligent management level of the cucumber greenhouse.

Key words: greenhouse tuyere, stepwise regression, predict, Lasso, automatic control

中图分类号:

S626

刘鹏菊, 柳平增, 张大磊, 张艳, 李辉, 刘力宁, 丁方军. 基于环境因子的设施黄瓜通风控制模型[J]. 中国农业科技导报, 2023, 25(12): 103-110.

Pengju LIU, Pingzeng LIU, Dalei ZHANG, Yan ZHANG, Hui LI, Lining LIU, Fangjun DING. Ventilation Control Model of Cucumber in Facility Based on Environmental Factors[J]. Journal of Agricultural Science and Technology, 2023, 25(12): 103-110.

图/表 7

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指标 Index	Y	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
Y	1
X₁	0.987	1
X₂	-0.819	-0.856	1
X₃	0.738	0.756	-0.704	1
X₄	-0.177	-0.177	-0.021	0.07	1
X₅	0.778	0.789	-0.664	0.513	-0.482	1
X₆	-0.634	-0.657	0.764	-0.555	-0.049	-0.575	1
X₇	0.295	0.297	-0.306	0.271	-0.051	0.281	-0.269	1
X₈	0.109	0.122	-0.154	0.109	-0.022	0.142	-0.177	-0.147	1
X₉	0.842	0.802	-0.806	0.671	-0.013	0.567	-0.567	0.351	0.059	1

指标 Index	Y	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
Y	1
X₁	0.987	1
X₂	-0.819	-0.856	1
X₃	0.738	0.756	-0.704	1
X₄	-0.177	-0.177	-0.021	0.07	1
X₅	0.778	0.789	-0.664	0.513	-0.482	1
X₆	-0.634	-0.657	0.764	-0.555	-0.049	-0.575	1
X₇	0.295	0.297	-0.306	0.271	-0.051	0.281	-0.269	1
X₈	0.109	0.122	-0.154	0.109	-0.022	0.142	-0.177	-0.147	1
X₉	0.842	0.802	-0.806	0.671	-0.013	0.567	-0.567	0.351	0.059	1

风口开度Opening size/%	回归自变量Regression independent variable
风口开度Opening size/%	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
0	20.388	5.084	11.127	1.510	14.771	12.126	1.308	1.385	3.542
25	15.705	22.809	5.077	13.338	6.074	20.151	1.423	1.523	7.074
50	14.171	5.278	10.296	2.985	2.357	4.846	1.116	1.177	2.380
75	3.551	6.218	1.835	2.801	2.902	5.543	1.110	1.108	2.275
100	5.978	8.135	2.024	3.564	5.510	6.482	1.054	1.076	2.605

风口开度Opening size/%	回归自变量Regression independent variable
风口开度Opening size/%	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉
0	20.388	5.084	11.127	1.510	14.771	12.126	1.308	1.385	3.542
25	15.705	22.809	5.077	13.338	6.074	20.151	1.423	1.523	7.074
50	14.171	5.278	10.296	2.985	2.357	4.846	1.116	1.177	2.380
75	3.551	6.218	1.835	2.801	2.902	5.543	1.110	1.108	2.275
100	5.978	8.135	2.024	3.564	5.510	6.482	1.054	1.076	2.605

风口开度Opening size/%	变量名称 Variable	非标准化系数Denormalization coefficient		标准化系数Normalization coefficient	显著性 Significance
风口开度Opening size/%	变量名称 Variable	回归系数 Regression coefficient	标准误差 Standard Error	标准化系数Normalization coefficient	显著性 Significance
0	常量Constant	1.772	2.107	—	0.401
	X₁	0.560	0.043	0.557	0.000
	X₃	0.105	0.011	0.311	0.000
	X₅	0.412	0.063	0.231	0.000
	X₆	0.036	0.006	0.204	0.000
	X₉	0.026	0.002	0.253	0.000
	X₂	0.071	0.010	0.157	0.000
	X₄	-0.313	0.057	-0.065	0.000
25	常量Constant	-4.117	0.979	—	0.000
	X₁	0.909	0.026	0.898	0.000
	X₉	0.054	0.003	0.364	0.000
	X₂	0.070	0.006	0.284	0.000
50	常量Constant	-0.217	0.815	—	0.490
	X₁	0.799	0.013	0.800	0.000
	X₉	0.085	0.003	0.305	0.000
	X₂	0.102	0.007	0.241	0.000
	X₅	-0.061	0.008	-0.130	0.000
	X₄	-0.077	0.012	-0.058	0.000
	X₈	0.003	0.001	0.033	0.000
75	常量Constant	-0.799	0.651	—	0.220
	X₁	0.842	0.012	0.787	0.000
	X₉	0.066	0.002	0.319	0.000
	X₂	0.054	0.005	0.143	0.000
	X₇	-0.134	0.025	-0.044	0.000
	X₈	-0.002	0.001	-0.034	0.000
	X₄	-0.035	0.009	-0.040	0.000

基于环境因子的设施黄瓜通风控制模型

Ventilation Control Model of Cucumber in Facility Based on Environmental Factors

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参考文献 28

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Metrics

主成分 Principal component	特征值 Eigenvalue	贡献率 Contribution/%	累计贡献率 Cumulative contribution/%
P1	5.751	95.845	95.845
P2	0.221	3.688	99.530
P3	0.019	0.312	99.842
P4	0.007	0.110	99.952
P5	0.006	0.048	100.00
P6	5.431e-6	9.052e-5	100.00

因变量Dependent variable	自变量Variable	估计值Estimate	标准误差Std. Error	显著性Significance
黄瓜长势 Cucumber growth	常数项Intercept	-4.48	1.024 275 8	P<0.001
	X₁₀	0.952	0.018 762 4	P<0.001
	X₁₁	0.043	0.007 364 2	P<0.001
	X₁₂	0.060	0.013 774 9	P<0.001

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