人工智能算法与生态环境模型耦合研究进展

人工智能算法在生态环境领域已有广泛应用,但在揭示自然科学现象规律时存在泛化能力不足、可解释性差等问题。为弥补这些不足,实现优势互补,将人工智能算法与具有物理机制的生态环境模型耦合研究已成为近些年快速发展的一种新型研究方法。本文从应用在生态环境领域的人工智能算法出发,概述了其分类和应用情况,重点梳理了人工智能算法与生态环境模型耦合研究的发展、现状及不足,提出了一个将人工智能与机理模型紧密耦合以重构机理过程的思路,分析了该网络部分参数的理论意义,提高可解释性和泛化能力的可行性,以及模拟机理过程运行的应用前景,并展望了人工智能算法与生态环境模型耦合研究的发展趋势。

Research progress on coupling artificial intelligence and eco-environmental models

Artificial intelligence (AI) has been widely used in the eco-environment field, but with shortcomings in revealing the laws of natural science, such as insufficient generalization ability and poor interpretability. In order to overcome these shortages and tap into complementary advantages, coupling AI and eco-environmental models containing physical mechanism has been a new research method with fast development in recent years. We introduced the classifications of AI used in eco-environmental field, outlined its applications, and mainly illustrated the progresses, status and inadequacies for the coupling research. Based on all the summaries, we proposed a new coupling method of physical mechanism and AI for reconstructing mechanism processes, followed by analyses of theoretical significance of partial parameters, feasibility of better generalization and interpretability, as well as prospection of imitating physical mechanism. At the end of the review, we discussed the trend of the coupling method of AI and eco-environment models.