ABSTRACT Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this article, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.

中文翻译：

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使用多尺度时空模式来验证基于空间显式代理的模型

摘要 基于空间显式主体的模型（ABM）已被广泛用于模拟涉及个体主体交互的空间过程的动态。ABM 中嵌入的假设可能会导致模型结果的不确定性。为了确保结果在时空模式方面的可靠性，应进行模型验证。在本文中，我们建议使用多尺度时空模式来验证空间明确的 ABM。我们通过均方根误差 (RMSE) 测量之和，将模型结果的时空模式与多个尺度的观测结果进行比较，评估了媒介传播疾病传播模型的几个规范。结果表明，居住区空间配置和个体免疫状态的规范对于在多个时空尺度上再现观察到的登革热暴发模式非常重要。我们使用多尺度时空模式的方法不仅可以帮助理解模型规范和模型结果之间的动态关联，还可以验证空间明确的 ABM。