RISeer: Inspecting the Status and Dynamics of Regional Industrial Structure via Visual Analytics
Restructuring the regional industrial structure (RIS) has the potential to halt economic recession and achieve revitalization. Understanding the current status and dynamics of RIS will greatly assist in studying and evaluating the current industrial structure. Previous studies have focused on qualit...
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| Veröffentlicht in: | IEEE transactions on visualization and computer graphics 2023-01, Vol.29 (1), p.1070-1080 |
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| creator | Chen, Longfei Ouyang, Yang Zhang, Haipeng Hong, Suting Li, Quan |
| description | Restructuring the regional industrial structure (RIS) has the potential to halt economic recession and achieve revitalization. Understanding the current status and dynamics of RIS will greatly assist in studying and evaluating the current industrial structure. Previous studies have focused on qualitative and quantitative research to rationalize RIS from a macroscopic perspective. Although recent studies have traced information at the industrial enterprise level to complement existing research from a micro perspective, the ambiguity of the underlying variables contributing to the industrial sector and its composition, the dynamic nature, and the large number of multivariant features of RIS records have obscured a deep and fine-grained understanding of RIS. To this end, we propose an interactive visualization system, RISeer , which is based on interpretable machine learning models and enhanced visualizations designed to identify the evolutionary patterns of the RIS and facilitate inter-regional inspection and comparison. Two case studies confirm the effectiveness of our approach, and feedback from experts indicates that RISeer helps them to gain a fine-grained understanding of the dynamics and evolution of the RIS. |
| doi_str_mv | 10.1109/TVCG.2022.3209351 |
| format | Article |
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Understanding the current status and dynamics of RIS will greatly assist in studying and evaluating the current industrial structure. Previous studies have focused on qualitative and quantitative research to rationalize RIS from a macroscopic perspective. Although recent studies have traced information at the industrial enterprise level to complement existing research from a micro perspective, the ambiguity of the underlying variables contributing to the industrial sector and its composition, the dynamic nature, and the large number of multivariant features of RIS records have obscured a deep and fine-grained understanding of RIS. To this end, we propose an interactive visualization system, RISeer , which is based on interpretable machine learning models and enhanced visualizations designed to identify the evolutionary patterns of the RIS and facilitate inter-regional inspection and comparison. 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| source | IEEE Electronic Library (IEL) |
| subjects | Biological system modeling Business Data visualization Dynamic structural analysis Economics Forecasting Industries Inspection Interactive systems Machine learning multivariate time series Regeneration Regional development regional industrial structure Spatiotemporal dynamics Time series analysis visualization |
| title | RISeer: Inspecting the Status and Dynamics of Regional Industrial Structure via Visual Analytics |
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