Journal of Computational Methods in Sciences and Engineering CALL FOR PAPERS Managing Complex Computational Challenges A huge body of methods for making large-scale simulations and analyses are produced, which are more computationally efficient, enabling a wide range of research to be less time- and memory-intensive. The proposed methods and systems can synthesize domains that integrate many concepts from deep learning, machine learning, AI and other computational techniques. Keeping the scientific value while designing computational approaches that leverage increased computational power is essential. Developing one system identifies a few significant features or facets. However, generating a large model uses innumerable parameters and infinite indicators to bring broad models that analyse multidimensional patterns and function as generic with permissible customisation. The future computational system can build newer interfaces with computers on one side, people, technologies, and domains on the other, and produce modalities. Robust techniques with insights create solution spaces with fewer computational complexities. Advanced big data analytics offer solutions to research questions in many different disciplines. Computational techniques coupled with intelligence are more successful for complex processes in many domains, and the refining activities lead to domain precision. In recent years efficient machine learning models have been recorded that solve many complex issues in other fields. Many approaches in research currently warrant intensive computational methods and have become more inevitable to solve research questions. Research can generate unique and highly objective scalable solutions to the complexity and understanding of how the different propositions can help product possible systems to solve the tasks with domain knowledge. Complexity reduction leads to robustness, structured results, higher accuracy, and resolved issues and is mainly achieved by applying computational methods. The proposed special issue will address many agendas codified in the above description and, more specifically, but not limited to the below themes. Neural models Spatio-temporal data modelling DL approaches to analyse patterns Convolutional Long Short-Term Memory network Data Transfer Framework Data security Data correlational dependencies Knowledge-driven machine learning Information and Systems Intelligence Computational Modelling Intelligent agent-supported processing Intelligent control systems Domain-specific smart models and architectures Complex data and sparse modelling Semantics-induced segmentation and clustering Edge Intelligence The important dates Submission of Papers: May 31, 2023 Acceptance/Rejection Notification: June 30, 2023 Revised version: August 15, 2023 Issue Publication: (will be notified later) Special Issue Editors Pit Pichappan, PhD, Senior Scientist Digital Information Research Labs Chennai. India Ezendu Ariwa, PhD, Professor Warwick University UK Fouzi Harrag, PhD Associate Professor Computer Science Ferhat Abbas University Setif, Algeria For further queries, please contact- pichappan@dirf.org For Author guidelines, please visit before submission- https://www.iospress.com/catalog/journals/journal-of-computational-methods-i... Submission of papers https://www.socio.org.uk/SIMCCC/openconf/openconf.php