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In a continuous chemical process, the accuracy and reliability of process and analytical measurements creates the basis for control system performance and ultimately for product uniformity. Measurement results, whether from fast on-line measurement devices or from sample-based laboratory analyses, is the key for selecting the method for process control and(More)
In this study, real-coded genetic algorithms are used in the parameter identification of the macroscopic Chemostat model. The Chemostat model utilized in this work is nonlinear having two distinct operating areas. Thus, the model is identified separately for both operating areas. The process simulator is used to generate data for the parameter(More)
This study introduces a theoretical bioprocess of ideally stirred Chemostat. Chemostat models give an insight to real-life bioprocess systems, in particular biological water treatment. The studied process is very nonlinear due to inhibition of desired reactions by high substrate concentration. The aim of this study is to demonstrate the possibilities of(More)
— The importance of nutritional guidance grows as nutritional problems, such as obesity and type-2 diabetes, are becoming more common. Nutritional guidance is carried out by mapping the nutritional state of an individual using a food diary and by comparing the nutrition intake levels to the recommended reference values. Typically, the expert knowledge of a(More)
The Basic Oxygen Furnace (BOF) is studied in this paper. BOF is a sub process in a blast furnace based steel making process, in which most of carbon is burned away from the pig iron. The carbon is burned away by using pure oxygen, which is blown through a lance into the mixture of pig iron and recycled steel. Previously the splashing in BOF has been mainly(More)
Radial basis function neural networks are used to predict residual stress of case-hardened steel samples in this study. The predictions are carried out based on the non-destructive Barkhausen noise measurement which is a potential method applicable to quality control. Neural network models are identified with the algorithm proposed in the literature and(More)
Evolutionary algorithms are optimization methods which basic idea lies in biological evolution. They suit well for large and complex optimization problems. In this study, genetic algorithms and differential evolution are used for identifying the parameters of the nonlinear fuel cell model. Different versions of the algorithms are used to compare the methods(More)