An evolutionary hybrid method to predict pistachio price

Abstract

Pistachio produce is of great importance in the world and considered as a valuable agricultural produce. This product is important for the economy of the producing countries as well as other importer countries. In this regard, countries which are capable of getting control over this product's market would obtain considerable benefits; one way to do so is predicting market trend or the price of this product and the affecting factors. In this survey, initially, the affecting parameters on pistachio price are identified. Then, using a novel combined intelligent method, the price of this product is predicted. In addition, using analysis of variance method, the results of the proposed method are compared to other intelligent combined methods, such as Feed Forward-Particle Swarm Optimization, Elman-Imperialist Competitive Algorithm, Feed Forward-Imperialist Competitive Algorithm, Elman-Genetic Algorithm, and Feed Forward-Genetic Algorithm. The results of the mentioned comparison indicate that the proposed method owns an excellent performance.

Evolutionary optimization of neural network to predict sediment transport without sedimentation

“…It can be said that classic methods do not have the capacity to estimate the flow velocity that prevents sediment deposition under different conditions, and there is a need for methods with such capacity. Recently, intelligent learning systems including Neural Networks have been applied extensively in water engineering [15][16][17][18][19][20][21]. Nasseri et al [22] developed the feed-forward neural network (FNN) to simulate rainfall fields.…”