> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > Gianluca Bontempi > Sent: mercredi 7 mars 2007 14:56 > To: [EMAIL PROTECTED] > Subject: [cinbios] 30/3: DI seminar on "Computational > Intelligence in the Chemical Industry" > > > > We would like to inform you that the Computer Science Seminar > Series organised by the Département d'Informatique, ULB will > feature a talk that will be of interest to you. > Dr. Elsa Jordaan of Dow Benelux will present her group's > research on the topic "Computational Intelligence in the > Chemical Industry". > The talk will be held at 12:30 hours on 30 March 2007, > Building NO, Room > 2NO607 at Campus de la Plaine. > ------------------------- > > Title: Computational Intelligence in the Chemical Industry > > Abstract: > > Computation Intelligence has revolutionized the way that > engineers in the process industry solve highly complex > problems. In the past, modeling and optimizing of chemical > processes and materials characteristics were done by > developing a fundamental model or a statistical model. > Fundamental models often required years of research. > Furthermore, the calculations of these models were often too > time-consuming to be used for online optimization and control. > Statistical models, again, required the availability of good > data that could be linearised. Many industrial data sets > turned out to be too noisy and high-dimensional to be solved > with statistical techniques. > The introduction of Neural Networks (NN) as a new tool to > quickly model highly nonlinear processes marked a clear > turning point in the chemical industry. Since then, > computational intelligence methods, like NN, Support Vector > Machines (SVM) and Genetic Programming (GP), have been > applied to a wide variety of problems in the process > industry. These methods have not only become essential in the > set of tools available to solve industrial problems, but also > generated millions of dollars in profit due to improved > process operability. > The list successful applications at the Dow Chemical Company include: > * A NN-application to predict NOx-emissions. > * Outlier detection using SVM. > * A GP-model to predict the biomass concentration in a > batch reactor. > * Using GP to help developing new rheological insights. > * Particle Swarm Optimization (PSO) for optimizing > properties of polymers. > > > About the speaker: > Elsa Jordaan received her PhD in 2002 from the Eindhoven > University of Technology, Netherlands, with a thesis on the > development of robust inferential sensors and industrial > applications of support vector machines. Since then she has > been working as a research specialist in process optimization > at the Dow Chemical Company's manufacturing site in the > Netherlands. She is involved in many projects where nonlinear > modeling or high-dimensional data analysis is required. Other > application areas include industrial statistics, risk > analysis, optimization of energy and feedstock needs, and > freight and logistics cost modelling. Her current area of > research is in the safeguarding of data-driven models in an > online environment. > > > Elsa is author of numerous conference publications, a book > chapter and invited talks on the subject of applications of > computational intelligence in the chemical industry. Dr. > Jordaan is an active member of the IEEE CIS AdHoc Committee > on Technology Transfer and advisory board member of the > Birmingham University (UK) M.Sc Program in Natural Computation. > > ------------------------- > > > -- > Gianluca Bontempi > Universite Libre de Bruxelles > Departement d'Informatique > Machine Learning Group > Boulevard du Triomphe - CP212 > 1050 Bruxelles, Belgium > email: [EMAIL PROTECTED] > Office Phone: +32-2-650 55 91 > Fax: +32 2 650.56.09 > web: http://www.ulb.ac.be/di/mlg > >
