Chau Kwokwing
Department of Civil & Structural Engineering, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong, China.
J Environ Manage. 2006 Jul;80(1):47-57. doi: 10.1016/j.jenvman.2005.08.012. Epub 2005 Dec 5.
With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.
随着计算技术的发展，常采用机理模型来模拟沿海环境中的过程。然而，这些预测工具不可避免地高度专业化，涉及某些假设和/或局限性，并且只能由对基础理论有透彻理解的经验丰富的工程师来操作。这导致了对其操作的重大限制，以及模型开发者和使用者在理解和期望上的巨大差距。人工智能（AI）技术的最新进展使得将机器学习能力集成到数值建模系统中成为可能，以弥合差距并减少对人类专家的需求。本文的目的是回顾将不同人工智能技术集成到海岸建模中的最新进展。所研究的算法和方法包括基于知识的系统、遗传算法、人工神经网络和模糊推理系统。更侧重于基于知识的系统，它在模型使用中允许更透明的知识传递以及在校准参数的智能操作方面比其他系统具有明显优势。当然，其他人工智能方法对海岸过程的准确可靠预测也有各自的贡献。由于可以将每种技术的优势结合起来，集成模型可能会非常强大。
