Publisher's Synopsis
Empirical modeling has been a significant methodology for the analysis of different problems across numerous areas/fields of knowledge. As it is known, this type of modeling is particularly helpful when parametric models, due to various reasons, cannot be constructed. Based on different methodologies and approaches, empirical modeling assists the analyst to attain primary understanding of the relationships that happen among the different variables that belong to a particular system or process. In some cases, the results from empirical models can be used to make decisions about those variables, with the intent of resolving a given problem. This 1st volume of Encyclopaedia of Advanced Data Analysis and Modeling in Chemical Engineering covers state of the art research and real world studies to integrate empirical investigation into different design processes. This work describes theoretical and practical framework and relates it to the empirical models we use in the data analysis. It is assumed that models based on well-defined parameters and distribution functions cannot be formulated due to incomplete data/information. This type of modeling also assumes that variables belong to sample spaces where uncertainty is present. EM can be used to represent real-life problems that require non-analytical methods. Examples of areas/fields where EM has proven useful include industry, science, technology, engineering, medicine, biology, and management. It should also be said that more powerful computers are of immense aid when researchers use EM, especially in those situations where high uncertainty exists. This book will be of valuable to Chemical Engineers who apply designed experiments to optimize petroleum extraction; Manufacturing Engineers who apply experimental data to optimize machine operation; and Industrial Engineers who might use data to determine the optimal number of operators required in a manual assembly process as well as an assisting tool for engineering and applied science students to incorporate empirical investigation into such design processes.
