August 4th, 2020 
Daniela Lopez de Luise
IEEE Symposium on Computational Intelligence for Engineering
Solutions (IEEE CIES)
http://ieeessci2020.org/symposiums/cies.html
Part of 2020 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE
1-4 December 2020, online this year, ieeessci2020.org
Deadline is August 7, there will be no extensions
Developments in Engineering are characterized by a growing
complexity, which is balanced by an extensive utilization of
computational resources. This complexity is not only a feature of
engineering systems, processes and products, it is primarily a key
attribute of the respective algorithms for analysis, control and
decision-making to develop those engineering solutions. To cope
with complexity in this broad spectrum of demands, Computational
Intelligence is implemented increasingly in virtually all
engineering disciplines. This emerging approach provides a basis
for developments of a new quality.
This Symposium is focused on the utilization of Computational
Intelligence in this context in the entire field of engineering.
Examples concern the control of processes of various kinds and for
various purposes, monitoring with sensors, smart sensing, system
identification, decision-support and assistance systems,
visualization methods, prediction schemes, the solution of
classification problems, response surface approximations, the
formulation of surrogate models, etc. The engineering application
fields may comprise, for example, bioengineering with prostheses
design and control, civil and mechanical engineering processes,
systems and structures concerned with vehicles, aircraft or
bridges, industrial and systems engineering with design and control
of power systems, electrical and computer engineering with
developments in robotics, etc. All kinds of approaches from the
field of Computational Intelligence are welcome.
As a part of the Symposium special attention is paid to sustainable
engineering solutions to address current and future challenges of
environmental changes and uncertainty. This includes developments
dealing with climate change, environmental processes, disaster
warning and management, infrastructure security, life cycle
analysis and design, etc. Events, disasters and issues under
consideration may be natural such as earthquakes or tsunamis,
man-made such as human failure or terrorist attacks, or a
combination thereof including secondary effects such as failures in
nuclear power plants,which may be critical for systems, the
environment and the society. Developments which include a
comprehensive consideration of uncertainty and techniques of
reliable computing are explicitly invited. These may involve
probabilistic including Bayesian approaches,interval methods, fuzzy
methods, imprecise probabilities and further concepts. In this
context robust design is of particular interest with all its facets
as a basic concept to develop sustainable engineering solutions.
Topics
•Complex engineering systems, structures and processes
•Intelligent analysis, control and decision-making
•Management and processing of uncertainties
•Problem solution in uncertain and noisy environments
•Reliable computing
•Sustainable solutions
•Infrastructure security
•Climate change
•Environmental processes
•Disaster warning and management
•Lifecycle analysis and design
•Automotive systems
•Monitoring
•Smart sensing
•System identification
•Decision-support and assistance systems
•Visualization methods
•Prediction schemes
•Classification methods, cluster analysis
•Response surface approximations and surrogate models
•Sensitivity analysis
•Robust design, reliability-based design, performance-based design
•Risk analysis, hazard analysis, risk and hazard mitigation
•Optimization methods, evolutionary concepts
•Probabilistic and statistical methods
•Simulation methods, Monte-Carlo and quasi Monte-Carlo
•Bayesian approaches / networks
•Artificial Neural Networks
•Imprecise probabilities
•Evidence theory
•p-box approach
•Fuzzy probability theory
•Interval methods
•Fuzzy methods
•Convex modeling
•Information gap theory
Symposium Chairs
Michael Beer
Leibniz University Hannover, Germany
Vladik Kreinovich
University of Texas at El Paso, USA
Rudolf Kruse
Otto-von-Guericke University, Germany
Computer Vision and Machine Learning (CVML) email list www page: https://lists.auth.gr/sympa/info/cvml
