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首页> 外文期刊>Ecological informatics: an international journal on ecoinformatics and computational ecology >Revealing spatial pattern dynamics in aquatic ecosystem modelling with Multi-Agent Systems in Lake Veluwe
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Revealing spatial pattern dynamics in aquatic ecosystem modelling with Multi-Agent Systems in Lake Veluwe

机译:借助多智能体系统在Veluwe湖中揭示水生生态系统建模中的空间格局动态

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摘要

Aquatic ecosystems are among the most complex due to the highly nonlinearity, randomness, as well as interactive multi-processes in multi-scales Besides, highly limited understanding and very limited measurement data make the modelling of such kind of systems a very challenging task, which needs to combine domain knowledge, available data and other models The concept of Multi-Agent Systems (MAS) in modelling spatial population dynamics of aquatic plant growth is explored in this research due to the capability of MAS in utilizing various information and data, reflecting both the interactions among different entities and entity's own properties Expert biological knowledge. GIS maps and environmental conditions are used as input information and data in the development of MAS model Several different aspects are included plant agents, environmental backgrounds, and animal influences Environmental background factors include flow pattern, light visibility, water temperature, water depth and wind, which are all abiotic factors Plant agents represent different plant species, the ones in this research are Potamogeton peen:in:us (Pp) and Churn aspera (Cs), while animals here refer to water birds Based on biological knowledge and data supplied for Lake Veluwe, the MAS modelling rules were developed Through these MAS rules. agents are linked to environmental and biological processes The resulting spatial pattern dynamics indicates that a multi-agent approach can exhibit complex behaviour even when the individual strategies of each agent are simple The test case for Like Veluwe showed quite good agreement compared to the GIS maps available and the biological knowledge presented Multi-Agent Systems show a promising approach to modelling spatial population dynamics for aquatic plants.
机译:由于高度的非线性,随机性以及多尺度的交互式多过程,水生生态系统是最复杂的系统。此外,高度有限的理解和非常有限的测量数据使此类系统的建模成为一项非常艰巨的任务,需要结合领域知识,可用数据和其他模型本研究探索了在建立水生植物生长空间种群动态模型中使用多智能系统(MAS)的概念,因为MAS具有利用各种信息和数据的能力,既反映了不同实体之间的相互作用以及实体自身的属性专家生物学知识。 GIS地图和环境条件在MAS模型的开发中用作输入信息和数据,其中包括植物代理,环境背景和动物影响等多个方面。环境背景因素包括流量模式,光能见度,水温,水深和风,这些都是非生物因素植物因子代表不同的植物物种,本研究中的植物因子为potamogeton peen:in:us(Pp)和Churn aspera(Cs),而此处的动物指的是水鸟。 Veluwe,通过这些MAS规则开发了MAS建模规则。代理与环境和生物过程相关联产生的空间格局动态表明,即使每个代理的单个策略都很简单,多代理方法也可以表现出复杂的行为。与可用的GIS地图相比,Like Veluwe的测试案例显示出很好的一致性。提出的生物学知识和多智能体系统显示了一种有前途的水生植物种群动态建模方法。

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