Plenary
Lecture
Statistical Techniques for Virtual Sensors Design using
Neural Networks

Professor Francklin Rivas-Echeverria
Universidad de Los Andes
Laboratorio de Sistemas Inteligentes (LabSIULA)
Merida, VENEZUELA
E-mail: rivas@ula.ve
Abstract:
This plenary speech covers the advantages of having
statistical analysis to input data previous to training
Artificial Neural Networks. It will be also presented
some industrial applications including methodologies for
designing virtual sensors for oil companies.
Shorter training periods, simpler topologies and more
reliable networks can be found. The presented techniques
for variables and patterns selection allow reducing the
data dimension, obtaining quicker training, simpler
topologies and lower prediction errors.
The pattern reduction techniques allow generating a data
partition for training and validation based on
statistical analysis. Additionally, these selection
techniques can be used for reducing the patterns number
in the data when it is very high.
The Outliers detection techniques can be used when great
volumes of data are used for neural networks training
and it is possible to use them for developing algorithms
that detect possible observations significantly
different from the rest of the data. These techniques
can depurate and select those data that provide a better
training.
It is very important the fusion of both disciplines:
Artificial intelligence and Statistical Data Analysis.
The work shows the advantages that it has for the
practical Statistic the Artificial intelligence and vice
versa.
Brief Biography of the Speaker:
Francklin Rivas-Echeverria Systems Engineer, MSc. in
Control Engineering and Applied Science Doctor. Full
professor in Control Systems Department, at Universidad
de Los Andes, Venezuela. He has been invited professor
in the Laboratoire d'Architecture et d'Analyse des
Systemes (LAAS, Toulouse-France) and some Venezuelan and
international Universities. He has also been technical
advisor for “Venezuelan Oil Company” (PDVSA), “Aluminum
Venezuelan Company” (VENALUM), “Steel Venezuelan
Company” (SIDOR), Trolleybus System in Venezuela
(TROLMERIDA). He has created and is the Director of the
Intelligent Systems Laboratory and is the head of the
University consulting unit (UAPIT-ULA). Over 180
publications in high level conferences and journals: the
main topics of his papers are: Artificial Intelligence,
Intelligent Control, Automation Systems and Industrial
Applications. He has applied his results to many fields:
Processes Control and Supervision, Oil production, Steel
production processes, among others. Also, has developed
several tools for automatic control teaching. He is
coauthor of two books concerning Artificial Intelligence
and Nonlinear Systems.
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