A new technique for time series forecasting by using symbiotic organisms search

Symbiotic organisms search (SOS) is a new metaheuristic optimization algorithm proposed by Cheng and Prayogo (Comput Struct 139:98–112, 2014 ). In this paper, SOS has been applied to determine the functional forms of different time series which are used to predict the time series. There are some previous attempts by researchers where genetic algorithm has been used to find the functional form of a time series. Here, we explore this new algorithm in time series analysis. SOS mimics the symbiotic relationships among organisms in the ecosystem. Improvement in SOS in parasitism phase has been proposed here. Also, several types of time series have been tested to compare the performance of the original SOS with its improved version and with already well-established artificial neural network (ANN) in the field of time series forecasting.