Maqolada amaldagi mis rudasining flotatsiya texnologik ko'rsatkichlari tahlil qilingan. Kompyuter texnologiyasiyordamida bajarilgan tahlil kamchiliklari muhokama qilingan. Akbastau mis koni misolida flotatsiya texnologik ko'rsatkichlarizamonaviy neyrotarmoq texnologiyasiga tadbiq qilingan. Neirotarmoq texnologiyasini modellashtirishning yutuqlarioddiy diskret statistik texnologik analiz ko'rsatkichlaridan farqi keltirilgan. Karagaylin boiitish fabrikasidaneirotarmoxji tehnologiyasining modeli erdamida misni flotaciya ciklining funciyaga bog'liklik asosiy parametrlarianiqlangan. Flotatsiya jarayoniga ta'sir ko'rsatuvchi salbiy ko'rsatkichlar aniqlangan bo'lib, taqqoslashni baholashfaktorlari orqali shixtalab qayta ishlashning texnologik ko'satkichlari va fabrikadagi texnologik ko'rsatkichalami takomillashtirishgaasoslangan.

Tayanch iboralar: Mis rudasi, flotatsiya, diskriptiv statistika, ko'pfaktorlilik va ob'ektning chiziqsizligi,neyrotarmoqli modellashtirish, funksiya va javobning sirtlari, boyitishning egriliklari.

The article analyzes the existing practice o f analysis o f technological indicators in the flotation o f copper ores. The shortcomingso f the performed analyzes using computer technologies are discussed. On the example o f copper ores o f the Akbastaufield, modem neural network technologies are used to analyze the technological parameters o f the flotation process. The advantageo f application o f neural network modeling is proved in comparison with the traditionally used simple descriptive statisticsfor the analysis o f technological indicators. With the help o f the neural network model, functional interrelations betweenthe parameters in the cycle o f copper flotation o f the Karagailinsk concentration plant are determined. The negative factorsinfluencing the results o f the flotation process are revealed. A comparative quantitative assessment o f the factors ofprocessedbatch for technological indicators is made and the necessity o f improving the technology operating at the factory is justified.

Key words: copper ores, flotation, descriptive statistics, multifactority and nonlinearity o f the object, neural simulation,functions and response surfaces, concentration curves.