对于选定区域的问题研究,模型结构确定之后,最重要的是如何有效地识别模型的参数。在模型参数物理意义的范围内,使模拟结果与实际观测值之间误差最小的参数估计问题本质上属于函数优化的研究范畴,是一个仿真优化问题。在分析环境模型参数优化特点的基础上,综述了环境模型的参数识别方法,重点介绍了新近发展起来的智能搜索算法的应用,并指出了进一步研究的课题和方向。
For a practical problem in the definite region, it is the most important work to identify parameter values efficiently after the structure of environmental model is defined. In fact, the model calibration is a function optimization problem, which searches the best or better parameter values in their acceptable ranges to attain a match between the observed and simulated distribution or distributions of a dependent variable or variables. By analyzing the features of parameter identification of environmental models, a survey on the identification approaches, improvements and applications and some further research contents and directions are presented.