Integration of artificial neural networks and Imperialist competitive algorithm

Description

Land leveling is one of the most important steps in soil preparation for agricultural and other purposes. In this regard, different considerations are required to satisfy energy consumption and environmental urges as well as financial aspects. Nowadays, energy conservation is regarded as one of the most important factors in agricultural sector mainly due to its relation to pollution which is a result of fossil fuel (particularly gasoline) usage. New techniques based on artificial intelligence, such as Artificial Neural Network (ANN), integrating Artificial Neural Network and Imperialist Competitive Algorithm (ICA-ANN), or Genetic Algorithms (GA-ANN), or Particle Swarm Optimization (PSO-ANN) have been employed for developing predictive models to estimate the energy related parameters and the results were compared to SPSS and Sensitivity Analysis (SA) results. In this study, several soil properties such as cut/fill volume, compressibility factor, specific gravity, moisture content, slope of the area, sand percent, and swelling index were measured and their effects on energy consumption were investigated.