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Special issue on SDEWES 2022

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.

Special issue on Machine Learning and Inverse Problems

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.