气候变化领域集成服务门户(CCPortal): EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

CCPortal

DOI	https://doi.org/10.1594/PANGAEA.831723
	EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study
	Broad; Darren R; Dandy; G C; Maier; H R
发布日期	2015-12-17
数据集类型	dataset
英文简介	Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.
语种	英语
国家	国际
学科大类	气候变化
学科子类	气候变化
文献类型	数据集
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/217514
推荐引用方式 GB/T 7714	Broad,Darren R,Dandy,et al. EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study.2015-12-17.https://doi.org/10.1594/PANGAEA.831723.