One of the most significant problems in economic domain is the dispose of human preference and choice forecasting. Recently, the economists have focused their researches to use the fuzzy concepts and the artificial learning procedures in the theory of economic choice. This paper extends the work done in this direction and offers a new algorithm for finding the matrix representation of the fuzzy binary relation which describes a preference relation.

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The aim of our study is to improve the crop planning procedures using neuro-fuzzy concepts. In this paper we design a neuro-fuzzy procedure that offers the suitable maize hybrid, from a set of preferred hybrids, which must be organically farmed in the current year. Our method is a statistical one, on the one hand it processes data provided by the previous years and on the other hand it takes in account the vague character of the environmental factors. Also we present here some experimental results obtained by us on a certain set of real data, results which prove the efficiency of our approach. ARTICLE HISTORY

This paper deals with the stochastic processes with application in the tests laboratory. We designed a stochastic process with discreet times and for that one we made some calculation using real data observed in several physics and mechanics tests. At the same time, we made some remarks concerning the obtained results and we indicated the suitable manner to adapt our approach in a practical case. Also, we prove that our results can improve the process of estimate of the expense required in the laboratory work.