Special Journal Issue on Machine Intelligence for Engineering under Uncertainties

The ASME Journal of Computing and Information Science in Engineering is currently accepting manuscripts for a special issue focusing on the topic “Machine Intelligence for Engineering under Uncertainties.” Authors who are interested in having their manuscripts included in the special issue, to be published in December 2022, should submit their manuscripts by January 15, 2022.
 
Machine intelligence (MI) integrates computation, data, models, and algorithms to solve problems that are too complex for humans. During the last three decades, MI has been a highly researched topic and widely used for solving complex real-world engineering problems. The main theme of this special issue is dedicated to the development of MI methods that sheds a new light for solving problems deemed difficult in engineering sciences under uncertainties.

Many real-world engineering design problems can be formulated as optimization. Yet the curse of dimensionality with a large number of design variables, both discrete and continuous, makes the solution searching process difficult.  Furthermore, interpretation of the large amount of simulation and experimental data needs advanced computation, data mining, Big Data analytics, and deep learning methodologies. The stochastic nature of real-world engineering systems makes these analyses even more challenging. Due to their complexity, real-world problems are difficult to solve using derivative-based local optimization algorithms. In the recent past, MI and its branches have been used to solve complex real-world engineering problems that cannot be solved using conventional methods.

This special issue strives to gather the latest developments of MI applications in real-world engineering systems, particularly the ones under uncertainty. On this basis, this special issue includes key applications of MI on different engineering disciplines such as engineering design, monitoring and maintenance, structural systems, applied mechanics, etc.
 
Manuscripts to be included in the special issue should concentrate on theories, methodologies, tools, computational aspects for MI topics and include, but not be limited to, mathematical foundation of machine learning under uncertainties; probabilistic methods and statistical tools for scientific machine learning; neural networks and deep learning with probabilistic reasoning; genetic programming and evolved systems with uncertainties; evolutionary and swarm Intelligence with uncertainties for multi-objective problems; stochastic and robust optimization using intelligent search methods; randomized algorithms (stochastic gradient, compressed sensing, etc.); stochastic surrogate/metamodels with model-form and parameter uncertainties; machine learning based on emerging computing hardware; data-driven statistical inverse problems; data mining, pattern recognition, and data clustering; fuzzy control, optimization, and decision making under uncertainties; applications of MI in product engineering such as engineering mechanics, system dynamics, reliability; and applications of MI in process engineering such as scheduling, system monitoring, maintenance, optimal control.
 
Manuscripts should be submitted electronically to the journal by January 15, 2022, via Journals Connect at journaltool.asme.org. Authors who have an account should log in and select “Submit Paper” at the bottom of the page.  Authors without an account should select “Submissions” and follow the steps.  At the Paper Submittal page, authors should select “ASME Journal of Computing and Information Science in Engineering” and then select the special issue “Machine Intelligence for Engineering under Uncertainties.” Papers received after the deadline or papers not selected for inclusion in the special issue may be accepted for publication in a regular issue. Early submission is highly encouraged.  Please also email the editor-in-chief, Professor Satyandra K. Gupta, at guptask@usc.edu, to alert him that your paper is intended for this special issue.
 
The guest editors for the special issue are Amir H. Gandomi, professor, University of Technology Sydney, Australia, gandomi@uts.edu.au; Marc Mignolet, professor, Arizona State University, USA, marc.mignolet@asu.edu; Christian Soize, professor, Université Gustave Eiffel, France, christian.soize@univ-eiffel.fr; and Yan Wang, professor, Georgia Institute of Technology, USA, yan.wang@me.gatech.edu.
 
For more information on the ASME Journal of Computing and Information Science in Engineering, visit https://asmedigitalcollection.asme.org/computingengineering.  To learn more about the ASME Journal Program, visit www.asme.org/publications-submissions/journals/information-for-authors.