Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model
Yan An , Zhihong Zou
,
Yanfei Zhao
DOI:10.1016/j.jes.2014.10.005
Received April 20, 2014,Revised October 11, 2014, Accepted , Available online March 13, 2015
Volume 27,2015,Pages 158-164
An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.
