Control System and Information Processing for the Sustainability of Landscape and Urban Areas
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 330
Special Issue Editors
Interests: data analysis; anomaly detection; modeling of natural; economic and social phenomena
Interests: biodiversity assessment; urban planning; conservation; ecology; monitoring; decision support tools; green areas; GIS; data analysis; missing data
Special Issue Information
Dear Colleagues,
In the era of constant social and environmental changes, proper management of the development of urban ecosystems and their surroundings should be supported by appropriate decision-making systems. A review of the most important trends in decision support systems is necessary due to their key importance in proper management.
Even the best decision support systems depend on the right inputs. Appropriate data preparation, including proper preprocessing, is a key stage in management in the era of digitization. As part of this Special Issue, we would like to present the most important techniques supporting the proper preparation of data for analysis. In particular, we would like to draw your attention to data integrity testing, which is often incorrectly performed.
This Special Issue aims to promote innovative research and development work on systems and tools supporting processing for the sustainability of landscape and urban areas. Topics of interest include but are not limited to:
- Group decision making;
- Decision support tools;
- Empirical data analysis;
- Data integrity testing;
- Open approach to data;
- Detecting anomalies in data;
- Exploring the potential value of outliers;
- Fuzzy approaches;
- Comparing traditional and modern computational methods;
- Interdisciplinary approaches;
- Missing data.
Dr. Kiersztyn Adam
Dr. Rafał Łopucki
Guest Editors
Manuscript Submission Information
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Keywords
- data analysis
- decision support
- data integrity
- fuzzy numbers
- missing data
