This systematic review provides a comprehensive overview of tsunami evacuation models. The review covers scientific studies from the last decade (2012–2021) and is explicitly focused on models using an agent-based approach. The PRISMA methodology was used to analyze 171 selected papers, resulting in over 53 studies included in the detailed full-text analysis. This review is divided into two main parts: (1) a descriptive analysis of the presented models (focused on the modeling tools, validation, and software platform used, etc.), and (2) model analysis (e.g., model purpose, types of agents, input and output data, and modeled area). Special attention was given to the features of these models specifically associated with an agent-based approach. The results lead to the conclusion that the research domain of agent-based tsunami evacuation models is quite narrow and specialized, with a high degree of variability in the model attributes and properties. At the same time, the application of agent-specific methodologies, protocols, organizational paradigms, or standards is sparse.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11069-022-05643-x.
Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management.
The paper describes a new approach to the modeling of the individual-based artificial life model based on fuzzy cognitive maps (FCM). The proposed concept focuses on the optimization of artificial intelligence of individuals in multi-agent models and their adaptation to environment. In this process of optimization, emphasis is put on the decision-making method. FCM offers great complexity and learning through evolutionary algorithms. However, too large FCMs suffer from performance issues. Therefore, this paper presents a possibility to replace a decision-making part of large FCM with the analytic hierarchy process (AHP) method, which is widely used, especially for decision support. In comparison with the large FCM model, a combination with AHP provides a model with lower computational demands while keeping nearly the same complexity.
Keywords-fuzzy cognitive maps; analytic hierarchy process; artificial life; individual-based; multi-agent model; decisionmaking2015 International Conference on Intelligent Environments 978-1-4673-6654-0/15 $31.00
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