CN105404142A - 基于bp神经网络与mbfo算法的铝电解多参数控制方法 - Google Patents
基于bp神经网络与mbfo算法的铝电解多参数控制方法 Download PDFInfo
- Publication number
- CN105404142A CN105404142A CN201510750094.9A CN201510750094A CN105404142A CN 105404142 A CN105404142 A CN 105404142A CN 201510750094 A CN201510750094 A CN 201510750094A CN 105404142 A CN105404142 A CN 105404142A
- Authority
- CN
- China
- Prior art keywords
- bacterium
- function
- aluminium
- algorithm
- decision variable
- 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.)
- Granted
Links
- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 77
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 72
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000004519 manufacturing process Methods 0.000 claims abstract description 20
- 239000004411 aluminium Substances 0.000 claims description 67
- 241000894006 Bacteria Species 0.000 claims description 44
- 210000002569 neuron Anatomy 0.000 claims description 29
- 238000005265 energy consumption Methods 0.000 claims description 25
- 238000012549 training Methods 0.000 claims description 17
- 230000036541 health Effects 0.000 claims description 12
- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical compound [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 claims description 5
- 210000004027 cell Anatomy 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 5
- 238000013459 approach Methods 0.000 claims description 4
- 230000008901 benefit Effects 0.000 claims description 3
- 238000009395 breeding Methods 0.000 claims description 3
- 230000001488 breeding effect Effects 0.000 claims description 3
- 239000003792 electrolyte Substances 0.000 claims description 3
- 239000003016 pheromone Substances 0.000 claims description 3
- 238000009790 rate-determining step (RDS) Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 9
- 230000001580 bacterial effect Effects 0.000 abstract description 8
- 230000002431 foraging effect Effects 0.000 abstract description 5
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 34
- 238000005868 electrolysis reaction Methods 0.000 description 11
- 238000004364 calculation method Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 239000005431 greenhouse gas Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000001537 neural effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011946 reduction process Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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
- G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
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)
- Dairy Products (AREA)
- Feedback Control In General (AREA)
Abstract
Description
Claims (5)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510750094.9A CN105404142B (zh) | 2015-11-06 | 2015-11-06 | 基于bp神经网络与mbfo算法的铝电解多参数控制方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510750094.9A CN105404142B (zh) | 2015-11-06 | 2015-11-06 | 基于bp神经网络与mbfo算法的铝电解多参数控制方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105404142A true CN105404142A (zh) | 2016-03-16 |
CN105404142B CN105404142B (zh) | 2017-12-26 |
Family
ID=55469694
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510750094.9A Active CN105404142B (zh) | 2015-11-06 | 2015-11-06 | 基于bp神经网络与mbfo算法的铝电解多参数控制方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105404142B (zh) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107169829A (zh) * | 2017-05-15 | 2017-09-15 | 重庆壹元电科技有限公司 | 面向拖延用户的移动电源租赁方法及*** |
CN107230295A (zh) * | 2017-07-17 | 2017-10-03 | 重庆壹元电科技有限公司 | 一种面向狂噪症极致用户体验的移动电源租赁管理***及方法 |
CN107511823A (zh) * | 2017-08-29 | 2017-12-26 | 重庆科技学院 | 机器人作业轨迹优化分析的方法 |
CN110129832A (zh) * | 2019-06-21 | 2019-08-16 | 广西大学 | 一种铝电解过程槽电压的多目标优化方法 |
CN111651890A (zh) * | 2020-06-04 | 2020-09-11 | 中南大学 | 基于数据驱动的铝电解数字孪生工厂、控制方法及*** |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6132571A (en) * | 1998-04-30 | 2000-10-17 | Kaiser Aluminum And Chemical Corporation | System for predicting impending anode effects in aluminum cells |
RU2204629C1 (ru) * | 2001-12-28 | 2003-05-20 | Закрытое акционерное общество "ТоксСофт" | Способ управления технологическим процессом в алюминиевом электролизере |
US6609119B1 (en) * | 1997-03-14 | 2003-08-19 | Dubai Aluminium Company Limited | Intelligent process control using predictive and pattern recognition techniques |
CN103103570A (zh) * | 2013-01-30 | 2013-05-15 | 重庆科技学院 | 基于主元相似性测度的铝电解槽况诊断方法 |
CN103345559A (zh) * | 2013-07-10 | 2013-10-09 | 重庆科技学院 | 铝电解过程电解槽工艺能耗的动态演化建模方法 |
CN103808431A (zh) * | 2014-03-03 | 2014-05-21 | 湖南创元铝业有限公司 | 铝电解槽槽温测量方法 |
CN104915960A (zh) * | 2015-06-08 | 2015-09-16 | 哈尔滨工程大学 | 一种基于细菌觅食优化算法的pcnn文本图像分割方法 |
-
2015
- 2015-11-06 CN CN201510750094.9A patent/CN105404142B/zh active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6609119B1 (en) * | 1997-03-14 | 2003-08-19 | Dubai Aluminium Company Limited | Intelligent process control using predictive and pattern recognition techniques |
US6132571A (en) * | 1998-04-30 | 2000-10-17 | Kaiser Aluminum And Chemical Corporation | System for predicting impending anode effects in aluminum cells |
RU2204629C1 (ru) * | 2001-12-28 | 2003-05-20 | Закрытое акционерное общество "ТоксСофт" | Способ управления технологическим процессом в алюминиевом электролизере |
CN103103570A (zh) * | 2013-01-30 | 2013-05-15 | 重庆科技学院 | 基于主元相似性测度的铝电解槽况诊断方法 |
CN103345559A (zh) * | 2013-07-10 | 2013-10-09 | 重庆科技学院 | 铝电解过程电解槽工艺能耗的动态演化建模方法 |
CN103808431A (zh) * | 2014-03-03 | 2014-05-21 | 湖南创元铝业有限公司 | 铝电解槽槽温测量方法 |
CN104915960A (zh) * | 2015-06-08 | 2015-09-16 | 哈尔滨工程大学 | 一种基于细菌觅食优化算法的pcnn文本图像分割方法 |
Non-Patent Citations (4)
Title |
---|
李莹 等: "基于免疫进化细菌觅食算法的多目标无功优化", 《电力科学与工程》 * |
王帆: "面向高维及多目标的协同细菌觅食算法研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
许鑫: "细菌觅食优化算法研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
郭俊 等: "铝电解生产过程的多目标优化", 《中南大学学报(自然科学版)》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107169829A (zh) * | 2017-05-15 | 2017-09-15 | 重庆壹元电科技有限公司 | 面向拖延用户的移动电源租赁方法及*** |
CN107230295A (zh) * | 2017-07-17 | 2017-10-03 | 重庆壹元电科技有限公司 | 一种面向狂噪症极致用户体验的移动电源租赁管理***及方法 |
CN107511823A (zh) * | 2017-08-29 | 2017-12-26 | 重庆科技学院 | 机器人作业轨迹优化分析的方法 |
CN107511823B (zh) * | 2017-08-29 | 2019-09-27 | 重庆科技学院 | 机器人作业轨迹优化分析的方法 |
CN110129832A (zh) * | 2019-06-21 | 2019-08-16 | 广西大学 | 一种铝电解过程槽电压的多目标优化方法 |
CN111651890A (zh) * | 2020-06-04 | 2020-09-11 | 中南大学 | 基于数据驱动的铝电解数字孪生工厂、控制方法及*** |
CN111651890B (zh) * | 2020-06-04 | 2022-04-12 | 中南大学 | 基于数据驱动的铝电解数字孪生工厂、控制方法及*** |
Also Published As
Publication number | Publication date |
---|---|
CN105404142B (zh) | 2017-12-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN112564098B (zh) | 基于时间卷积神经网络的高比例光伏配电网电压预测方法 | |
CN105404926A (zh) | 基于bp神经网络与mbfo算法的铝电解生产工艺优化方法 | |
CN105321000A (zh) | 基于bp神经网络与mobfoa算法的铝电解工艺参数优化方法 | |
CN105404142A (zh) | 基于bp神经网络与mbfo算法的铝电解多参数控制方法 | |
CN113282122B (zh) | 一种商用建筑能耗预测优化方法及*** | |
CN106529818B (zh) | 基于模糊小波神经网络的水质评价预测方法 | |
CN111119282B (zh) | 一种针对供水管网的压力监测点优化布置方法 | |
CN105447567B (zh) | 基于bp神经网络与mpso算法的铝电解节能减排控制方法 | |
CN105302973A (zh) | 基于moea/d算法的铝电解生产优化方法 | |
CN106855957A (zh) | 基于相似日和最小二乘支持向量机的工厂母线负荷预测 | |
Ning et al. | GA-BP air quality evaluation method based on fuzzy theory. | |
CN103605909A (zh) | 一种基于灰色理论及支持向量机的水质预测方法 | |
CN109085752A (zh) | 基于角度支配关系的铝电解偏好多目标优化算法 | |
CN108445756B (zh) | 基于ar支配关系的铝电解节能减排智能控制方法 | |
CN104732067A (zh) | 一种面向流程对象的工业过程建模预测方法 | |
CN105426959A (zh) | 基于bp神经网络与自适应mbfo算法的铝电解节能减排方法 | |
Ge et al. | Solving interval many-objective optimization problems by combination of NSGA-III and a local fruit fly optimization algorithm | |
CN105302976A (zh) | 基于spea2算法的铝电解生产优化方法 | |
CN111832817A (zh) | 基于mcp罚函数的小世界回声状态网络时间序列预测方法 | |
CN111222762A (zh) | 太阳能电池板镀膜工艺状态监控及质量控制*** | |
CN112183721B (zh) | 一种基于自适应差分进化的组合水文预测模型的构建方法 | |
CN105420760B (zh) | 基于自适应步长细菌觅食算法的铝电解多参数优化方法 | |
CN105334824A (zh) | 基于nsga-ⅱ算法的铝电解生产优化方法 | |
CN105426960A (zh) | 基于bp神经网络与mbfo算法的铝电解节能减排控制方法 | |
CN109086469A (zh) | 基于递归神经网络与偏好信息的铝电解建模与优化方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160316 Assignee: Guangzhou nuobi Electronic Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052372 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 Application publication date: 20160316 Assignee: Lingteng (Guangzhou) Electronic Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052367 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 Application publication date: 20160316 Assignee: Guangzhou Taipu Intelligent Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052361 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 Application publication date: 20160316 Assignee: GUANGZHOU GUOCHUANG TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052357 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 Application publication date: 20160316 Assignee: GUANGZHOU YIJUN TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052341 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 Application publication date: 20160316 Assignee: GUANGZHOU XINGYIN TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052337 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231220 |
|
EE01 | Entry into force of recordation of patent licensing contract | ||
EE01 | Entry into force of recordation of patent licensing contract | ||
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160316 Assignee: WUZHOU JINZHENGYUAN ELECTRONIC TECH. Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980053985 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20231227 |
|
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160316 Assignee: Liaoning Higher Education Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000653 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240119 Application publication date: 20160316 Assignee: Silk Road Inn (Chongqing) Trading Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000638 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240119 Application publication date: 20160316 Assignee: Hengdian Wuxia Film and Television (Chongqing) Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000634 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240119 |
|
EE01 | Entry into force of recordation of patent licensing contract | ||
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160316 Assignee: Foshan WanChen Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004249 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240415 Application publication date: 20160316 Assignee: FOSHAN ZHENGRONG TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004248 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240415 Application publication date: 20160316 Assignee: FOSHAN DOUQI TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004247 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240415 |
|
EE01 | Entry into force of recordation of patent licensing contract | ||
EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160316 Assignee: Foshan helixing Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004524 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240419 Application publication date: 20160316 Assignee: Foshan qianshun Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004523 Denomination of invention: Multi parameter control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171226 License type: Common License Record date: 20240419 |
|
EE01 | Entry into force of recordation of patent licensing contract |