Özkan, Şafak Gökhan2024-04-232024-04-232023Özkan, Şafak G. (2023). Artificial intelligence versus natural intelligence in mineral processing. Physicochemical Problems of Mineral Processing, 59 (5).1643-1049https://hdl.handle.net/20.500.12846/1136This article aims to introduce the terms NI-Natural Intelligence, AI-Artificial Intelligence, MLMachine Learning, DL-Deep Learning, ES-Expert Systems and etc. used by modern digital world to mining and mineral processing and to show the main differences between them. As well known, each scientific and technological step in mineral industry creates huge amount of raw data and there is a serious necessity to firstly classify them. Afterwards experts should find alternative solutions in order to get optimal results by using those parameters and relations between them using special simulation software platforms. Development of these simulation models for such complex operations is not only time consuming and lacks real time applicability but also requires integration of multiple software platforms, intensive process knowledge and extensive model validation. An example case study is also demonstrated and the results are discussed within the article covering the main inferences, comments and decision during NI use for the experimental parameters used in a flotation related postgraduate study and compares with possible AI use.eninfo:eu-repo/semantics/openAccessNI-natural intelligenceAI-Artificial IntelligenceML-machine learningDL-deep learningES-expert systemsMineral processingArtificial intelligence versus natural intelligence in mineral processingArticle59510.37190/ppmp/167501WOS:0012453307000282-s2.0-85177225193