TOWARD NEURAL NETWORK-BASED PROFIT OPTIMIZATION UDC 004.032.26
Dragoljub Pokrajac · 2005
A novel technique for profit optimization is proposed. The technique provides recommendations to management, with an objective of maximizing a profit function using a neural network-based decision support system. Applicability of the proposed method is evaluated on simulated precision agriculture data. The obtained profit increase is compared to the known optimum. Experimental results suggest that the neural network-based profit optimization techniques may lead to a significant profit increase; with radial-basis function networks outperforming multi-layer perceptrons. The quality of provided recommendations depends on the possibility of learning regression models on training data from all regions of the attribute space.