Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO
This paper combine the improved PSO algorithm (Analysis of Particle Swarm Optimization Algorithm) with the BP neural network for prediction of Silicon content in hot metal. Firstly, the varying visual mechanism is drawing into the standard PSO through changing the neighbor structure dynamically with...
Saved in:
| Published in: | Functional Materials |
|---|---|
| Date: | 2016 |
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
НТК «Інститут монокристалів» НАН України
2016
|
| Subjects: | |
| Online Access: | https://nasplib.isofts.kiev.ua/handle/123456789/121413 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO / Yang Kai, Zhijun He // Functional Materials. — 2016. — Т. 23, № 3. — С. 463-467. — Бібліогр.: 8 назв. — англ. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| _version_ | 1862668078658093056 |
|---|---|
| author | Yang Kai Zhijun He |
| author_facet | Yang Kai Zhijun He |
| citation_txt | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO / Yang Kai, Zhijun He // Functional Materials. — 2016. — Т. 23, № 3. — С. 463-467. — Бібліогр.: 8 назв. — англ. |
| collection | DSpace DC |
| container_title | Functional Materials |
| description | This paper combine the improved PSO algorithm (Analysis of Particle Swarm Optimization Algorithm) with the BP neural network for prediction of Silicon content in hot metal. Firstly, the varying visual mechanism is drawing into the standard PSO through changing the neighbor structure dynamically with each particles, in order to enhance the local and global searching ability in particle swarm. Afterwards, the improved algorithm is used to optimize the weights and threshold of BP neural network to avoid falling into local extremum. Finally, the prediction model of Si content in hot metal is built based on BP network optimized by Variable neighborhood PSO. The average relative error of the prediction model is 6.7% based on the data from blast furnace.
|
| first_indexed | 2025-12-07T15:24:54Z |
| format | Article |
| fulltext | |
| id | nasplib_isofts_kiev_ua-123456789-121413 |
| institution | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| issn | 1027-5495 |
| language | English |
| last_indexed | 2025-12-07T15:24:54Z |
| publishDate | 2016 |
| publisher | НТК «Інститут монокристалів» НАН України |
| record_format | dspace |
| spelling | Yang Kai Zhijun He 2017-06-14T09:43:36Z 2017-06-14T09:43:36Z 2016 Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO / Yang Kai, Zhijun He // Functional Materials. — 2016. — Т. 23, № 3. — С. 463-467. — Бібліогр.: 8 назв. — англ. 1027-5495 DOI: dx.doi.org/10.15407/fm23.03.463 https://nasplib.isofts.kiev.ua/handle/123456789/121413 This paper combine the improved PSO algorithm (Analysis of Particle Swarm Optimization Algorithm) with the BP neural network for prediction of Silicon content in hot metal. Firstly, the varying visual mechanism is drawing into the standard PSO through changing the neighbor structure dynamically with each particles, in order to enhance the local and global searching ability in particle swarm. Afterwards, the improved algorithm is used to optimize the weights and threshold of BP neural network to avoid falling into local extremum. Finally, the prediction model of Si content in hot metal is built based on BP network optimized by Variable neighborhood PSO. The average relative error of the prediction model is 6.7% based on the data from blast furnace. en НТК «Інститут монокристалів» НАН України Functional Materials Modeling and simulation Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO Article published earlier |
| spellingShingle | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO Yang Kai Zhijun He Modeling and simulation |
| title | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO |
| title_full | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO |
| title_fullStr | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO |
| title_full_unstemmed | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO |
| title_short | Target prediction in blast furnace based on BP network optimized by variable neighborhood PSO |
| title_sort | target prediction in blast furnace based on bp network optimized by variable neighborhood pso |
| topic | Modeling and simulation |
| topic_facet | Modeling and simulation |
| url | https://nasplib.isofts.kiev.ua/handle/123456789/121413 |
| work_keys_str_mv | AT yangkai targetpredictioninblastfurnacebasedonbpnetworkoptimizedbyvariableneighborhoodpso AT zhijunhe targetpredictioninblastfurnacebasedonbpnetworkoptimizedbyvariableneighborhoodpso |