Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes
The aim of this Special Issue is to explore the multifaceted aspects of data-driven intelligent modeling and optimization algorithms for industrial processes. The main goals are to harness the power of data to improve control, decision making, and parameter optimization and to drive industrial syste...
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| Formato: | Online |
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| Idioma: | inglês |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Acesso em linha: | ONIX_20250220_9783725829859_515 |
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| _version_ | 1869524369216110592 |
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| collection | Directory of Open Access Books |
| description | The aim of this Special Issue is to explore the multifaceted aspects of data-driven intelligent modeling and optimization algorithms for industrial processes. The main goals are to harness the power of data to improve control, decision making, and parameter optimization and to drive industrial systems to unprecedented levels of efficiency, reliability, and adaptability. Research areas within this scope include data-driven modeling, intelligent data representation, integrated/hybrid modeling, machine learning and optimization, advanced machine learning algorithms, hybrid models with optimization algorithms, adaptive learning algorithms, intelligent process monitoring, real-time data monitoring and analysis, soft sensing technologies, operation mode perception and recognition, decision support systems, intelligent decision support systems, the integration of optimization algorithms, and human–machine collaboration for improved decision making. These powerful intelligent algorithms use data for control, decision making, and parameter optimization, driving industrial systems to unprecedented levels of efficiency, reliability, and adaptability. By sharing their practice and insights in the development and application of these new technologies, the authors of the articles in this Reprint have demonstrated the value of data-driven intelligent modeling and optimization algorithms for industrial processes, providing readers with valuable ideological inspiration in the field. |
| format | Online |
| id | doab-20.500.12854ir-153151 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1531512025-02-20T13:38:30Z Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes Jin, Li Du, Sheng Huang, Zixin Wan, Xiongbo hot strip rolling looper EPAE production stability root cause traceability work sampling observations analysis proportions correlations interdependence between activities process choreography IOBP data-driven process mining discovery maritime emergency rescue intelligent navigation path planning A* algorithm B-spline interpolation regional search modeling finite elements (EF) NHC core RUM technology UCK cutting tool surface quality stress and strain distribution chip size control chart ATTRIVAR variability variance application interface R Shiny package load frequency control switching system event-triggered model-free adaptive control combined economic emission dispatch (CEED) load shifting demand side management crow search algorithm arithmetic optimization algorithm hybrid energy storage system adaptive sliding-mode controller battery degradation supercapacitor Zeta converter vibration intelligent control piezoelectric structures H2criterion H-infinity criterion ideal solution sequential three-way decisions VIKOR method domain muti-attribute decision making sliding mode control data-driven techniques systematic literature review intelligent algorithms applications data-driven modeling industrial processes machine learning algorithms optimization algorithms adaptive learning thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology The aim of this Special Issue is to explore the multifaceted aspects of data-driven intelligent modeling and optimization algorithms for industrial processes. The main goals are to harness the power of data to improve control, decision making, and parameter optimization and to drive industrial systems to unprecedented levels of efficiency, reliability, and adaptability. Research areas within this scope include data-driven modeling, intelligent data representation, integrated/hybrid modeling, machine learning and optimization, advanced machine learning algorithms, hybrid models with optimization algorithms, adaptive learning algorithms, intelligent process monitoring, real-time data monitoring and analysis, soft sensing technologies, operation mode perception and recognition, decision support systems, intelligent decision support systems, the integration of optimization algorithms, and human–machine collaboration for improved decision making. These powerful intelligent algorithms use data for control, decision making, and parameter optimization, driving industrial systems to unprecedented levels of efficiency, reliability, and adaptability. By sharing their practice and insights in the development and application of these new technologies, the authors of the articles in this Reprint have demonstrated the value of data-driven intelligent modeling and optimization algorithms for industrial processes, providing readers with valuable ideological inspiration in the field. 2025-02-20T13:38:28Z 2025-02-20T13:38:28Z 2025 book ONIX_20250220_9783725829859_515 9783725829859 9783725829866 https://directory.doabooks.org/handle/20.500.12854/153151 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10411 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2986-6 10.3390/books978-3-7258-2986-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725829859 9783725829866 254 Basel open access |
| spellingShingle | hot strip rolling looper EPAE production stability root cause traceability work sampling observations analysis proportions correlations interdependence between activities process choreography IOBP data-driven process mining discovery maritime emergency rescue intelligent navigation path planning A* algorithm B-spline interpolation regional search modeling finite elements (EF) NHC core RUM technology UCK cutting tool surface quality stress and strain distribution chip size control chart ATTRIVAR variability variance application interface R Shiny package load frequency control switching system event-triggered model-free adaptive control combined economic emission dispatch (CEED) load shifting demand side management crow search algorithm arithmetic optimization algorithm hybrid energy storage system adaptive sliding-mode controller battery degradation supercapacitor Zeta converter vibration intelligent control piezoelectric structures H2criterion H-infinity criterion ideal solution sequential three-way decisions VIKOR method domain muti-attribute decision making sliding mode control data-driven techniques systematic literature review intelligent algorithms applications data-driven modeling industrial processes machine learning algorithms optimization algorithms adaptive learning thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title | Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title_full | Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title_fullStr | Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title_full_unstemmed | Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title_short | Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes |
| title_sort | data driven intelligent modeling and optimization algorithms for industrial processes |
| topic | hot strip rolling looper EPAE production stability root cause traceability work sampling observations analysis proportions correlations interdependence between activities process choreography IOBP data-driven process mining discovery maritime emergency rescue intelligent navigation path planning A* algorithm B-spline interpolation regional search modeling finite elements (EF) NHC core RUM technology UCK cutting tool surface quality stress and strain distribution chip size control chart ATTRIVAR variability variance application interface R Shiny package load frequency control switching system event-triggered model-free adaptive control combined economic emission dispatch (CEED) load shifting demand side management crow search algorithm arithmetic optimization algorithm hybrid energy storage system adaptive sliding-mode controller battery degradation supercapacitor Zeta converter vibration intelligent control piezoelectric structures H2criterion H-infinity criterion ideal solution sequential three-way decisions VIKOR method domain muti-attribute decision making sliding mode control data-driven techniques systematic literature review intelligent algorithms applications data-driven modeling industrial processes machine learning algorithms optimization algorithms adaptive learning thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| topic_facet | hot strip rolling looper EPAE production stability root cause traceability work sampling observations analysis proportions correlations interdependence between activities process choreography IOBP data-driven process mining discovery maritime emergency rescue intelligent navigation path planning A* algorithm B-spline interpolation regional search modeling finite elements (EF) NHC core RUM technology UCK cutting tool surface quality stress and strain distribution chip size control chart ATTRIVAR variability variance application interface R Shiny package load frequency control switching system event-triggered model-free adaptive control combined economic emission dispatch (CEED) load shifting demand side management crow search algorithm arithmetic optimization algorithm hybrid energy storage system adaptive sliding-mode controller battery degradation supercapacitor Zeta converter vibration intelligent control piezoelectric structures H2criterion H-infinity criterion ideal solution sequential three-way decisions VIKOR method domain muti-attribute decision making sliding mode control data-driven techniques systematic literature review intelligent algorithms applications data-driven modeling industrial processes machine learning algorithms optimization algorithms adaptive learning thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| url | ONIX_20250220_9783725829859_515 |