CN110119086B - 一种基于anfis神经网络的番茄温室环境参数智能监测装置 - Google Patents
一种基于anfis神经网络的番茄温室环境参数智能监测装置 Download PDFInfo
- Publication number
- CN110119086B CN110119086B CN201910320157.5A CN201910320157A CN110119086B CN 110119086 B CN110119086 B CN 110119086B CN 201910320157 A CN201910320157 A CN 201910320157A CN 110119086 B CN110119086 B CN 110119086B
- Authority
- CN
- China
- Prior art keywords
- tomato
- yield
- neural network
- tomato greenhouse
- greenhouse
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 235000007688 Lycopersicon esculentum Nutrition 0.000 title claims abstract description 312
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 149
- 230000007613 environmental effect Effects 0.000 title claims abstract description 31
- 238000012806 monitoring device Methods 0.000 title claims abstract description 13
- 240000003768 Solanum lycopersicum Species 0.000 title claims description 305
- 239000002689 soil Substances 0.000 claims abstract description 62
- 238000001514 detection method Methods 0.000 claims abstract description 45
- 238000012544 monitoring process Methods 0.000 claims abstract description 22
- 230000000306 recurrent effect Effects 0.000 claims description 53
- 238000012937 correction Methods 0.000 claims description 23
- 230000004927 fusion Effects 0.000 claims description 23
- 238000000354 decomposition reaction Methods 0.000 claims description 22
- 230000008859 change Effects 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 11
- 238000005070 sampling Methods 0.000 claims description 3
- 241000227653 Lycopersicon Species 0.000 abstract 7
- 230000006870 function Effects 0.000 description 37
- 238000000034 method Methods 0.000 description 27
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 23
- 238000004422 calculation algorithm Methods 0.000 description 13
- 238000012549 training Methods 0.000 description 13
- 230000008569 process Effects 0.000 description 12
- 238000013461 design Methods 0.000 description 11
- 230000004913 activation Effects 0.000 description 8
- 230000000694 effects Effects 0.000 description 8
- 230000006872 improvement Effects 0.000 description 8
- 238000004519 manufacturing process Methods 0.000 description 8
- 230000008901 benefit Effects 0.000 description 7
- 235000013399 edible fruits Nutrition 0.000 description 6
- 230000012010 growth Effects 0.000 description 6
- 238000003973 irrigation Methods 0.000 description 6
- 230000002262 irrigation Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 241000196324 Embryophyta Species 0.000 description 5
- 230000003044 adaptive effect Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 5
- 230000018109 developmental process Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 210000002569 neuron Anatomy 0.000 description 5
- 238000011160 research Methods 0.000 description 5
- 238000012706 support-vector machine Methods 0.000 description 4
- 235000013311 vegetables Nutrition 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 230000033228 biological regulation Effects 0.000 description 3
- 239000003337 fertilizer Substances 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 230000003068 static effect Effects 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 241000860705 Alternaria tomato Species 0.000 description 2
- CIWBSHSKHKDKBQ-JLAZNSOCSA-N Ascorbic acid Chemical compound OC[C@H](O)[C@H]1OC(=O)C(O)=C1O CIWBSHSKHKDKBQ-JLAZNSOCSA-N 0.000 description 2
- UPYKUZBSLRQECL-UKMVMLAPSA-N Lycopene Natural products CC(=C/C=C/C=C(C)/C=C/C=C(C)/C=C/C1C(=C)CCCC1(C)C)C=CC=C(/C)C=CC2C(=C)CCCC2(C)C UPYKUZBSLRQECL-UKMVMLAPSA-N 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000004720 fertilization Effects 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005312 nonlinear dynamic Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 238000011282 treatment Methods 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- ZZZCUOFIHGPKAK-UHFFFAOYSA-N D-erythro-ascorbic acid Natural products OCC1OC(=O)C(O)=C1O ZZZCUOFIHGPKAK-UHFFFAOYSA-N 0.000 description 1
- JEVVKJMRZMXFBT-XWDZUXABSA-N Lycophyll Natural products OC/C(=C/CC/C(=C\C=C\C(=C/C=C/C(=C\C=C\C=C(/C=C/C=C(\C=C\C=C(/CC/C=C(/CO)\C)\C)/C)\C)/C)\C)/C)/C JEVVKJMRZMXFBT-XWDZUXABSA-N 0.000 description 1
- 241000208292 Solanaceae Species 0.000 description 1
- 229930003268 Vitamin C Natural products 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 150000001746 carotenes Chemical class 0.000 description 1
- 235000005473 carotenes Nutrition 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- HDRXZJPWHTXQRI-BHDTVMLSSA-N diltiazem hydrochloride Chemical compound [Cl-].C1=CC(OC)=CC=C1[C@H]1[C@@H](OC(C)=O)C(=O)N(CC[NH+](C)C)C2=CC=CC=C2S1 HDRXZJPWHTXQRI-BHDTVMLSSA-N 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000009982 effect on human Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000010413 gardening Methods 0.000 description 1
- 239000003630 growth substance Substances 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 230000035876 healing Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012886 linear function Methods 0.000 description 1
- 235000012661 lycopene Nutrition 0.000 description 1
- OAIJSZIZWZSQBC-GYZMGTAESA-N lycopene Chemical compound CC(C)=CCC\C(C)=C\C=C\C(\C)=C\C=C\C(\C)=C\C=C\C=C(/C)\C=C\C=C(/C)\C=C\C=C(/C)CCC=C(C)C OAIJSZIZWZSQBC-GYZMGTAESA-N 0.000 description 1
- 229960004999 lycopene Drugs 0.000 description 1
- 239000001751 lycopene Substances 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 150000007524 organic acids Chemical class 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000000243 photosynthetic effect Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 230000008121 plant development Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000001850 reproductive effect Effects 0.000 description 1
- 239000010865 sewage Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- ZCIHMQAPACOQHT-ZGMPDRQDSA-N trans-isorenieratene Natural products CC(=C/C=C/C=C(C)/C=C/C=C(C)/C=C/c1c(C)ccc(C)c1C)C=CC=C(/C)C=Cc2c(C)ccc(C)c2C ZCIHMQAPACOQHT-ZGMPDRQDSA-N 0.000 description 1
- 230000009105 vegetative growth Effects 0.000 description 1
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 229930003231 vitamin Natural products 0.000 description 1
- 239000011782 vitamin Substances 0.000 description 1
- 235000013343 vitamin Nutrition 0.000 description 1
- 229940088594 vitamin Drugs 0.000 description 1
- NCYCYZXNIZJOKI-UHFFFAOYSA-N vitamin A aldehyde Natural products O=CC=C(C)C=CC=C(C)C=CC1=C(C)CCCC1(C)C NCYCYZXNIZJOKI-UHFFFAOYSA-N 0.000 description 1
- 235000019154 vitamin C Nutrition 0.000 description 1
- 239000011718 vitamin C Substances 0.000 description 1
- 150000003722 vitamin derivatives Chemical class 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Description
Claims (5)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910320157.5A CN110119086B (zh) | 2019-04-19 | 2019-04-19 | 一种基于anfis神经网络的番茄温室环境参数智能监测装置 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910320157.5A CN110119086B (zh) | 2019-04-19 | 2019-04-19 | 一种基于anfis神经网络的番茄温室环境参数智能监测装置 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110119086A CN110119086A (zh) | 2019-08-13 |
CN110119086B true CN110119086B (zh) | 2022-03-18 |
Family
ID=67521188
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910320157.5A Active CN110119086B (zh) | 2019-04-19 | 2019-04-19 | 一种基于anfis神经网络的番茄温室环境参数智能监测装置 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110119086B (zh) |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110570616B (zh) * | 2019-09-10 | 2020-09-25 | 淮阴工学院 | 一种基于物联网的多点火灾预警*** |
CN111474851B (zh) * | 2020-04-15 | 2022-09-30 | 深圳禄华科技有限公司 | 一种ptc加热智能调节控制的方法及装置 |
CN111998887A (zh) * | 2020-08-25 | 2020-11-27 | 淮阴工学院 | 一种用于参数测量的检测装置 |
CN112903929A (zh) * | 2021-01-13 | 2021-06-04 | 淮阴工学院 | 一种食品质量检测*** |
CN113219871B (zh) * | 2021-05-07 | 2022-04-01 | 淮阴工学院 | 一种养护室环境参数检测*** |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103048266B (zh) * | 2012-12-11 | 2015-06-10 | 江苏大学 | 一种设施番茄氮磷钾胁迫自动识别方法和装置 |
US20170161560A1 (en) * | 2014-11-24 | 2017-06-08 | Prospera Technologies, Ltd. | System and method for harvest yield prediction |
CN105230447B (zh) * | 2015-09-06 | 2017-10-03 | 淮阴工学院 | 番茄灌溉智能控制*** |
US11263707B2 (en) * | 2017-08-08 | 2022-03-01 | Indigo Ag, Inc. | Machine learning in agricultural planting, growing, and harvesting contexts |
-
2019
- 2019-04-19 CN CN201910320157.5A patent/CN110119086B/zh active Active
Also Published As
Publication number | Publication date |
---|---|
CN110119086A (zh) | 2019-08-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110084417B (zh) | 一种基于grnn神经网络的草莓温室环境参数智能监测*** | |
CN110119086B (zh) | 一种基于anfis神经网络的番茄温室环境参数智能监测装置 | |
CN110163254B (zh) | 一种基于递归神经网络的黄瓜温室产量智能化预测装置 | |
CN110109193B (zh) | 一种基于drnn神经网络的茄子温室温度智能化检测装置 | |
CN110119766B (zh) | 一种多组合智能化模型的青椒温室温度智能化预警装置 | |
CN110083190B (zh) | 一种基于减法聚类分类器的青椒温室环境智能监测*** | |
CN110647979B (zh) | 一种基于物联网的温室环境多参数智能化监测*** | |
CN110119169B (zh) | 一种基于最小向量机的番茄温室温度智能预警*** | |
CN112906735B (zh) | 一种食用菌环境大数据检测*** | |
CN110147825B (zh) | 一种基于经验模态分解模型的草莓温室温度智能检测装置 | |
CN110705757B (zh) | 一种基于现场总线网络的多点温度传感器智能监测*** | |
CN110119767B (zh) | 一种基于lvq神经网络的黄瓜温室温度智能化检测装置 | |
CN110069032B (zh) | 一种基于小波神经网络的茄子温室环境智能检测*** | |
CN107169621A (zh) | 一种水体溶解氧预测方法及装置 | |
CN106373022B (zh) | 基于bp-ga的温室农作物种植效率条件优化方法及*** | |
CN110766132B (zh) | 一种基于物联网的果园产量智能预测*** | |
CN109214579B (zh) | 基于bp神经网络的盐碱地稳定性预测方法及*** | |
CN113281465A (zh) | 一种畜禽舍养殖环境有害气体检测*** | |
CN108762084A (zh) | 基于模糊控制决策的水田灌溉***及方法 | |
CN110119165B (zh) | 一种水产养殖池塘溶解氧检测装置 | |
Chen et al. | A water-saving irrigation decision-making model for greenhouse tomatoes based on genetic optimization TS fuzzy neural network | |
CN112906856A (zh) | 一种基于云平台的畜禽舍环境温度检测*** | |
Mao et al. | A variable weight combination prediction model for climate in a greenhouse based on BiGRU-Attention and LightGBM | |
Adeyemo | Soft Computing techniques for weather and Climate change studies | |
Jiao et al. | [Retracted] Prediction Model of Rice Seedling Growth and Rhizosphere Fertility Based on the Improved Elman Neural Network |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right |
Effective date of registration: 20230817 Address after: 230000 B-1015, wo Yuan Garden, 81 Ganquan Road, Shushan District, Hefei, Anhui. Patentee after: HEFEI MINGLONG ELECTRONIC TECHNOLOGY Co.,Ltd. Address before: 223005 Jiangsu Huaian economic and Technological Development Zone, 1 East Road. Patentee before: HUAIYIN INSTITUTE OF TECHNOLOGY |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20240528 Address after: Building 5, Block A, No. 118, Dongnongsheng Street North (Business Community), Jinhai Road, Shengcheng Street, Shouguang City, Weifang City, Shandong Province, 262700 Patentee after: Shouguang Nongfa Agricultural Equipment Co.,Ltd. Country or region after: China Address before: 230000 B-1015, wo Yuan Garden, 81 Ganquan Road, Shushan District, Hefei, Anhui. Patentee before: HEFEI MINGLONG ELECTRONIC TECHNOLOGY Co.,Ltd. Country or region before: China |
|
TR01 | Transfer of patent right |