CN105426960A - 基于bp神经网络与mbfo算法的铝电解节能减排控制方法 - Google Patents
基于bp神经网络与mbfo算法的铝电解节能减排控制方法 Download PDFInfo
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- CN105426960A CN105426960A CN201510752612.0A CN201510752612A CN105426960A CN 105426960 A CN105426960 A CN 105426960A CN 201510752612 A CN201510752612 A CN 201510752612A CN 105426960 A CN105426960 A CN 105426960A
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- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 49
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 29
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- 238000004134 energy conservation Methods 0.000 title abstract description 3
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- 239000005431 greenhouse gas Substances 0.000 claims abstract description 28
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- TXEYQDLBPFQVAA-UHFFFAOYSA-N tetrafluoromethane Chemical compound FC(F)(F)F TXEYQDLBPFQVAA-UHFFFAOYSA-N 0.000 description 1
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- G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
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- C25C—PROCESSES FOR THE ELECTROLYTIC PRODUCTION, RECOVERY OR REFINING OF METALS; APPARATUS THEREFOR
- C25C3/00—Electrolytic production, recovery or refining of metals by electrolysis of melts
- C25C3/06—Electrolytic production, recovery or refining of metals by electrolysis of melts of aluminium
- C25C3/20—Automatic control or regulation of cells
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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CN201510752612.0A CN105426960B (zh) | 2015-11-06 | 2015-11-06 | 基于bp神经网络与mbfo算法的铝电解节能减排控制方法 |
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CN201510752612.0A CN105426960B (zh) | 2015-11-06 | 2015-11-06 | 基于bp神经网络与mbfo算法的铝电解节能减排控制方法 |
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CN105426960A true CN105426960A (zh) | 2016-03-23 |
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109086469A (zh) * | 2018-03-09 | 2018-12-25 | 重庆科技学院 | 基于递归神经网络与偏好信息的铝电解建模与优化方法 |
CN110093632A (zh) * | 2018-01-30 | 2019-08-06 | 沈阳铝镁设计研究院有限公司 | 在线数字化电解槽健康度评价计算方法 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6745169B1 (en) * | 1995-07-27 | 2004-06-01 | Siemens Aktiengesellschaft | Learning process for a neural network |
US20110196819A1 (en) * | 2010-02-05 | 2011-08-11 | Toyota Motor Engineering & Manufacturing North America, Inc. | Method for approximation of optimal control for nonlinear discrete time systems |
CN102184454A (zh) * | 2011-05-26 | 2011-09-14 | 浙江迦南科技股份有限公司 | 基于神经网络系统的制粒机配方生成方法 |
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 |
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- 2015-11-06 CN CN201510752612.0A patent/CN105426960B/zh active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6745169B1 (en) * | 1995-07-27 | 2004-06-01 | Siemens Aktiengesellschaft | Learning process for a neural network |
US20110196819A1 (en) * | 2010-02-05 | 2011-08-11 | Toyota Motor Engineering & Manufacturing North America, Inc. | Method for approximation of optimal control for nonlinear discrete time systems |
CN102184454A (zh) * | 2011-05-26 | 2011-09-14 | 浙江迦南科技股份有限公司 | 基于神经网络系统的制粒机配方生成方法 |
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 |
Non-Patent Citations (1)
Title |
---|
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 (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110093632A (zh) * | 2018-01-30 | 2019-08-06 | 沈阳铝镁设计研究院有限公司 | 在线数字化电解槽健康度评价计算方法 |
CN109086469A (zh) * | 2018-03-09 | 2018-12-25 | 重庆科技学院 | 基于递归神经网络与偏好信息的铝电解建模与优化方法 |
CN109086469B (zh) * | 2018-03-09 | 2022-11-11 | 重庆科技学院 | 基于递归神经网络与偏好信息的铝电解建模与优化方法 |
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Application publication date: 20160323 Assignee: Guangzhou nuobi Electronic Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052372 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 Application publication date: 20160323 Assignee: Lingteng (Guangzhou) Electronic Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052367 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 Application publication date: 20160323 Assignee: Guangzhou Taipu Intelligent Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052361 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 Application publication date: 20160323 Assignee: GUANGZHOU GUOCHUANG TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052357 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 Application publication date: 20160323 Assignee: GUANGZHOU YIJUN TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052341 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 Application publication date: 20160323 Assignee: GUANGZHOU XINGYIN TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2023980052337 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20231220 |
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Application publication date: 20160323 Assignee: Liaoning Higher Education Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000653 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240119 Application publication date: 20160323 Assignee: Silk Road Inn (Chongqing) Trading Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000638 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240119 Application publication date: 20160323 Assignee: Hengdian Wuxia Film and Television (Chongqing) Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980000634 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240119 |
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Application publication date: 20160323 Assignee: Foshan WanChen Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004249 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240415 Application publication date: 20160323 Assignee: FOSHAN ZHENGRONG TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004248 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240415 Application publication date: 20160323 Assignee: FOSHAN DOUQI TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004247 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240415 |
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Application publication date: 20160323 Assignee: Foshan helixing Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004524 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240419 Application publication date: 20160323 Assignee: Foshan qianshun Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980004523 Denomination of invention: Energy saving and emission reduction control method for aluminum electrolysis based on BP neural network and MBFO algorithm Granted publication date: 20171205 License type: Common License Record date: 20240419 |