WSEAS Transactions on Biology and Biomedicine
Print ISSN: 1109-9518, E-ISSN: 2224-2902
Volume 10, 2013
Knowledge-based Modeling of Multi-factor Processes in Biotechnology and Microbial Ecology
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Abstract: Biotechnological and ecological processes are multi-factor nonlinear system, its dynamic could be considered as sequence of phases. Bacterial growth in batch culture can be modeled as a sequence of four integrated phases: lag phase, exponential or log-phase, stationary phase, and death phase. Ecological processes are connected with the seasonal changes for certain period of time – one season, one year, a decade or a century. Methodologies which can provide their adequate mathematical descriptions are based on the synthesis of local MIMO-models; the transition between phases is realized by using time or state conditions markers in form of IF-THEN rules, expressing complex relations between influential input-output variables. Obtaining of such relations is a nontrivial task. For this reason human expertise and learning capacity of modern AIapproaches is embedded. Main purpose of the presented paper is to demonstrate these opportunities on some multi-factor and multiphase biotechnological processes. The application of knowledge-based system on the multiphase processes is presented in connection with monitoring and inferential measurements systems development.
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Keywords: Knowledge-based systems, intelligent industry, multi-factor nonlinear system, multiphase modeling, artificial intelligence, biotechnology, microbial ecology