Management of water demand by use a new dynamic firefly algorithm: case study, River Hirmand

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 firefly algorithm is applied for demand estimation of water of river Hirmand in Sistan area and comparative with different firefly algorithm for 2006-2017 years. The data from 2006 to 2014 are used for learning and teaching and finding the optimal weights of the model, and the rest of data (2015-2017) are applied to test the models. The results show that all five FA variants can achieve promising solutions. But NDFA obtains better performance than four other FA variants and its prediction accuracy is up to 97.98%. After ensuring the accuracy of the algorithm, water demand of river Hirmand from 2018-2020 is predicted. And risk assessment of the water shortage under three scenarios of high, average, and low inflow levels for this years.

Keywords

• swarm intelligence
• dynamic parameter
• firefly algorithm
• optumization
• predict