Title
A new dynamic firefly algorithm for demand estimation of water resources.
Abstract
Firefly algorithm (FA) is an effective optimization technique based on swarm intelligence, which has been successfully applied to various practical engineering problems. In this paper, a new dynamic FA (called NDFA) is proposed for demand estimation of water resources in Nanchang city of China. First, a dynamic parameter strategy is used to avoid manually adjusting the step factor. Second, three estimation models in different forms (linear, exponential and hybrid) are developed in terms of the historical water use and local economic structure. Third, normalization method is utilized to eliminate the influences of different units of data. In the experiments, water use in Nanchang city from 2003 to 2015 is considered as a case study. The data from 2003 to 2012 are used for finding the optimal weights of the models, and the rest of data (2013–2015) are applied to test the models. Computational results show that all five FA variants can achieve promising solutions. The proposed NDFA obtains better performance than four other FA variants, and its prediction accuracy is up to 97.91%. Finally, the water demand in Nanchang city from 2017 to 2020 is predicted.
Year
DOI
Venue
2018
10.1016/j.ins.2018.01.041
Information Sciences
Keywords
Field
DocType
Firefly algorithm (FA),Swarm intelligence,Dynamic parameter,Water demand estimation,Water demand prediction,Optimization
Demand estimation,Mathematical optimization,Normalization (statistics),Exponential function,Swarm intelligence,Firefly algorithm,Water demand,Artificial intelligence,Water resources,Water use,Mathematics,Machine learning
Journal
Volume
ISSN
Citations 
438
0020-0255
29
PageRank 
References 
Authors
0.74
27
6
Name
Order
Citations
PageRank
Hui Wang127717.29
Wenjun Wang230442.81
Zhihua Cui379362.19
xinyu zhou429223.26
Jia Zhao5787.88
Ya Li611715.01