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A Review of Membrane Computing Models for Complex Ecosystems and a Case Study on a Complex Giant Panda System

机译:复杂生态系统膜计算模型的综述及复杂巨熊系统的案例研究

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Ecosystem modelling based on membrane computing is emerging as a powerful way to study the dynamics of (real) ecological populations. These models, providing distributed parallel devices, have shown a great potential to imitate the rich features observed in the behaviour of species and their interactions and key elements to understand and model ecosystems. Compared with differential equations, membrane computing models, also known as P systems, can model more complex biological phenomena due to their modularity and their ability to enclose the evolution of different environments and simulate, in parallel, different interrelated processes. In this paper, a comprehensive survey of membrane computing models for ecosystems is given, taking a giant panda ecosystem as an example to assess the model performance. This work aims at modelling a number of species using P systems with different membrane structure types to predict the number of individuals depending on parameters such as reproductive rate, mortality rate, and involving processes as rescue or release. Firstly, the computing models are introduced conceptually, describing the main elements constituting the syntax of these systems and explaining the semantics of the rules involved. Next, various modelled species (including endangered animals, plants, and bacteria) are summarized, and some computer tools are presented. Then, a discussion follows on the use of P systems for ecosystem modelling. Finally, a case study on giant pandas in Chengdu Base is analysed, concluding that the study in this field by using PDP systems can provide a valuable tool to deepen into the knowledge about the evolution of the population. This could ultimately help in the decision-making processes of the managers of the ecosystem to increase the species diversity and modify the adaptability. Besides, the impacts of natural disasters on the population dynamics of the species should also be considered. The analysis performed throughout the paper has taken into consideration this fact in order to increase the reliability of the prospects making use of the models designed.
机译:基于膜计算的生态系统建模是研究(REAL)生态人群动态的强大方法。提供分布式并行器件的这些模型显示出巨大的潜力,以模仿在物种的行为和他们的交互和关键元素中观察到的富特征,以了解和模拟生态系统。与微分方程相比,膜计算模型,也称为P系统,可以模拟更复杂的生物现象,因为它们的模块化和它们封闭不同环境的演变和模拟的能力,并行地不同的相互关联的过程。在本文中,给出了对生态系统膜计算模型的综合调查,采用了巨大的熊猫生态系统作为评估模型性能的示例。这项工作旨在使用具有不同膜结构类型的P系统建模许多物种来预测根据诸如生殖率,死亡率,并涉及救援或释放的过程的参数来预测个体的数量。首先,计算模型在概念上引入,描述构成这些系统的语法的主要元素并解释所涉及的规则的语义。接下来,总结了各种建模物种(包括濒危动物,植物和细菌),并提出了一些计算机工具。然后,讨论使用P系统进行生态系统建模。最后,分析了成都基地巨型熊猫的案例研究,得出结论认为,使用PDP系统的研究可以提供有价值的工具,可以加深关于人口演变的知识。这可能最终有助于生态系统管理人员的决策过程,以增加物种多样性并修改适应性。此外,还应考虑自然灾害对物种人口动态的影响。在本文中进行的分析已经考虑到这一事实,以提高利用所设计模型的前景的可靠性。

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