Call for papers for Virtual
Special Issue of the Optimization and Engineering Journal on Sustainable
Development of Energy, Water and Environment Systems – SDEWES, dedicated to the
SDEWES 2022 Conferences
The background of this
Virtual Special Issue (VSI) of the Optimization and Engineering (OPTE) journal
are the 2022 Sustainable Development of Energy, Water and Environment Systems
(SDEWES) Conferences. This broad field was discussed by the participants of
three conferences held in 2022 – 3rd Latin American SDEWES Conference (Sao
Paulo), 5th Southeast European SDEWES Conference (Vlorë) and 17th SDEWES
Conference (Paphos).
This VSI aims at bringing
together articles that discuss recent advances of optimization methods and
algorithms that integrate various life supporting systems. Very often a
decision making problem appears in the form of a parameter estimation problem,
it can be formulated as an optimization model, and then solved using different
optimization algorithms and techniques. All papers included in this VSI of the OPTE journal will consider aspects of
numerical analysis, mathematical modeling, and computational methods involved in investigating, planning and implementing sustainable
development. In this context, the guest editors have confidence that
the selected papers and addressed issues will substantially contribute to the
increase of the knowledge body published in the OPTE journal and the VSI
will be a significant platform for researchers to discuss, share, and
disseminate new ideas.
Information on the upcoming SDEWES events and other
related activities can be found in the website of the International Centre for
Sustainable Development of Energy, Water and Environment Systems (SDEWES
Centre) at <www.sdewes.org>.
Proposed date of
submission of final paper:
February 28, 2023 – first version of all papers
July 31, 2023 – final version of all papers
Guest editorial
team of this special volume:
Dr.
Marian Trafczynski, Managing Guest Editor
The
Faculty of Civil Engineering, Mechanics and Petrochemistry
Warsaw
University of Technology, Plock, Poland
e-mail:
Marian.Trafczynski@pw.edu.pl
Prof.
Neven Duić, Guest Editor
Faculty
of Mechanical Engineering and Naval Architecture
University
of Zagreb, Zagreb, Croatia
e-mail: Neven.Duic@fsb.hr
Prof.
Krzysztof Urbaniec, Guest Editor
The
Faculty of Civil Engineering, Mechanics and Petrochemistry
Warsaw
University of Technology, Plock, Poland
e-mail:
k.urbaniec4@upcpoczta.pl
Dr.
Hrvoje Mikulčić, Guest Editor
Xi'an
Jiaotong University, Xi'an, Shaanxi, China / University of Zagreb, Zagreb,
Croatia
e-mail:
Hrvoje.Mikulcic@fsb.hr
Dr.
Slawomir Alabrudzinski, Guest Editor
The
Faculty of Civil Engineering, Mechanics and Petrochemistry
Warsaw
University of Technology, Plock, Poland
e-mail:
Slawomir.Alabrudzinski@pw.edu.pl
Submissions:
The
Special Issue will be limited to the conference participants. A number of
papers with archival quality, presented at the SDEWES2022 conferences, will be after
the conferences selected for recommendation for submission in a Virtual Special
Issue of the Optimization and Engineering journal. The submission procedure
requires the submission of a manuscript to the Optimization and Engineering
(OPTE) journal at https://www.springer.com/journal/11081 and select special
issue “SI: SDEWES2022”. All submissions must be original and may not be under
review by another publication. Interested authors should consult the journal’s
“Instructions for Authors”, at https://www.springer.com/journal/11081/submission-guidelines.
All submitted papers will be reviewed on a peer review basis as soon as they
are received.
Machine Learning and Inverse Problems
Call For
Papers
Guest Editors:
D. Auroux (Universite’ Cote d’Azur, France)
V. Kovanis (Virginia Tech, USA)
H. Kunze (University of Guelph, Canada)
D. La Torre (SKEMA Business School, France)
Submission deadline: November 30, 2023
Description:
This special issue
aims at bringing together articles that discuss recent advances in machine
learning and inverse problems. Machine Learning is a subset of Artificial
Intelligence focusing on computers’ ability to learn from data and to imitate
intelligence human behaviour. A typical inverse problem seeks to find a
mathematical model that admits given observational data as an approximate
solution. Recent contributions in these areas aim at exploring potential
synergies between there two different domains of research. From one hand, in fact, machine learning
algorithms can leverage large collections of training data to directly compute
regularized reconstructions and estimate unknown parameters. From the other
hand, machine learning algorithms can benefit from the vast inverse problem
literature and the existing contributions to the theory of inverse problems,
and they can be used to simulate boundary value data when they are missing.
Both
these domains are of great interest in many application areas, including
biomedical engineering and imaging, remote sensing and seismic imaging,
astronomy, oceanography, atmospheric sciences and meteorology, chemical
engineering and material sciences, computer vision and image processing,
ecology, economics, environmental systems, physical systems. The possibility of
integrating them can generate more precise estimation and allow to estimate
unknown parameters in more complex environments. All papers included in this special issue will
consider aspects of numerical analysis, mathematical modelling, and
computational methods. This call for papers invites contributions from emerging
areas such as quantum inverse problems and quantum machine learning. Potential
topics include, but are not limited to, the following:
· Deep Learning Algorithms
· Inverse Problems Techniques
· Inverse Problems for Ordinary and
Differential Equations
· Optimization Methods in Inverse
Problems and Machine Learning
· Machine Learning
· Neural Networks
· Quantum Inverse Problems
· Quantum Machine Learning
· Shape Optimization
· Inverse Optimization
· Image Analysis
· Regularization Techniques
Important Dates:
Deadline for
submissions: November 30, 2023
1st round of review – comments to authors: January 31, 2024
Revision deadline: March, 2024
Submission of final version: June, 2024
Submission
Procedure:
Please submit to
the Optimization and Engineering (OPTE) journal at https://www.springer.com/mathematics/journal/11081 and select special
issue “SI: Inverse problems 2023”. All submissions must be original and
may not be under review by another publication. Interested authors should
consult the journal’s “Instructions for Authors”, at https://www.springer.com/mathematics/journal/11081. All submitted papers will be
reviewed on a peer review basis as soon as they are received. Accepted papers
will become immediately available at Online First until the complete Special
Issue appears.