In this study, conditional average estimator neural networks (CAE NNs) were used for an analysis of the common influences of the cooling mode in relation to the ram speed, extrusion ratio, casting speed and casting temperature on the yield strength and the elongation of an extruded profile made from aluminium alloy (AA)6082. The obtained results from the analysis revealed very complex relationships between these parameters. In order to maximise the values for the yield strength and the elongation, the values for the ram speed, extrusion ratio, casting speed and casting temperature should be optimised in relation to the mode of cooling.Key words: AA6082, intermetallic phases, hot extrusion, mechanical properties, neural networks Izvleček V tem delu smo uporabili CAE (ang. conditional average estimator, slo. cenilka pogojnega povprečja) nevronske mreže za analizo skupnega vpliva načina ohlajanja v povezavi s hitrostjo bata, iztiskalnim razmerjem, hitrostjo ulivanja in temperaturo ulivanja na mejo tečenja in raztezek iztiskanega profila iz aluminijeve zlitine 6082. Dobljeni rezultati iz analize so pokazali kompleksen vpliv parametrov na mejo tečenja in raztezek. Da lahko izboljšamo vrednosti meje tečenja in raztezka, moramo vrednosti za hitrost bata, iztiskalnega razmerja, hitrosti ulivanja in temperature ulivanja optimizirati v povezavi z načinom ohlajanja.Ključne besede: AA6082, intermetalne faze, vroče izstiskavanje, mehanske lastnosti, nevronske mreže