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Sustainable ecosystem management using optimal control theory: Part 2 (stochastic systems)

机译:使用最优控制理论的可持续生态系统管理:第2部分(随机系统)

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Sustainable development of ecosystems through external ecosystem management is assuming importance for the environmentalists. To that effect, previous work by the authors looked at the option of manipulating population dynamics of the species in an ecosystem to achieve sustainability. Fisher information is used as-the quantifying measure of sustainability and optimal control theory is used to derive the control profiles. However, that work considered only deterministic systems. Uncertainty being prevalent in all systems, particularly in natural systems, this paper extends that work to analyse uncertain systems. Predator-prey models are used to model the species populations and different control philosophies are compared. Ito mean reverting process is used to model the stochastic process, and stochastic maximum principle is used to derive the control profiles. The results for the objective of FI variance minimization qualitatively agree with those for the deterministic system, while the results for the FI maximization objective differ. It is observed that the instability associated with the FI maximization objective for deterministic systems is absorbed by the noise introduced by the uncertainty. Quantitatively, it is observed that the degree of uncertainty, along with its presence, is also important to identify the most appropriate management strategy. (c) 2006 Elsevier Ltd. All rights reserved.
机译:通过外部生态系统管理来实现生态系统的可持续发展对于环境保护主义者而言至关重要。为此,作者先前的工作着眼于操纵生态系统中物种的种群动态以实现可持续性的选择。将Fisher信息用作可持续性的量化度量,并使用最佳控制理论得出控制曲线。但是,该工作仅考虑确定性系统。不确定性在所有系统中都普遍存在,特别是在自然系统中,本文将其工作扩展到分析不确定性系统。使用捕食者-捕食者模型对物种种群进行建模,并比较了不同的控制哲学。 Ito均值恢复过程用于对随机过程进行建模,而随机最大原理用于推导控制曲线。 FI方差最小化目标的结果与确定性系统的结果在质量上一致,而FI最大目标的结果则有所不同。可以看出,不确定性引入的噪声吸收了与确定性系统的FI最大化目标相关的不稳定性。从数量上可以看出,不确定性的程度及其存在对确定最合适的管理策略也很重要。 (c)2006 Elsevier Ltd.保留所有权利。

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