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Mathematics publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions. Special Issues are led by Guest Editors, who are experts on the topic and all Special Issue submissions follow MDPI's standard editorial process. The journal’s Editor-in-Chief and/or designated Editorial Board Member will oversee Guest Editor appointments and Special Issue proposals, checking their content for relevance and ensuring the suitability of the material for the journal. The papers published in a Special Issue will be collected and displayed on a dedicated page of the journal’s website. Further information on MDPI's Special Issue policies and Guest Editor responsibilities can be found here. For any inquiries related to a Special Issue, please contact the Editorial Office.

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Advances in Spatial Statistics and Spatial Data Science: Theory, Methods and Applications
edited by Gabriel Marín Díaz
submission deadline 31 May 2027 | Viewed by 40 | Submission Open
Keywords: spatial statistics; spatial data science; geostatistics; spatio-temporal modeling; spatial and spatio-temporal point processes; point pattern analysis; statistical inference and forecasting; spatial machine learning; GeoAI; explainable artificial intelligence; Bayesian spatial models; uncertainty quantification; computational social science; spatial big data
(This special issue belongs to the Section D1: Probability and Statistics)
Theory and Applications of Optimization in Numerical Algorithms
edited by and Joanna Soszynska-Budny
submission deadline 31 May 2027 | Viewed by 34 | Submission Open
Keywords: single- and multi-criteria optimisations; machine learning; high-performance computing; testing and benchmarking; application for ICT, ITS, smart grids; discreet and continuous algorithms; evolutionary algorithms; neural networks
(This special issue belongs to the Section E: Applied Mathematics)
Machine Learning and Statistical Learning with Applications, 2nd Edition
edited by
submission deadline 31 May 2027 | Viewed by 34 | Submission Open
Keywords: ML and SL model algorithm developments; ML and SL applications for predictive science and engineering; physics-informed neural network model development and applications; operator learning model development and applications; ML algorithms and approaches to handling out-of-distribution, data imbalance, data fusion, etc.; federated learning algorithm development and applications; differential privacy-based ML algorithm development and applications; uncertainty quantification for ML and SL algorithms and applications; large-language model development and applications
(This special issue belongs to the Section E: Applied Mathematics)
Mathematical Modelling and Intelligent Optimization for Complex Engineering Systems
edited by Sichen Tao
submission deadline 31 May 2027 | Viewed by 29 | Submission Open
Keywords: mathematical modelling; intelligent optimization; deep learning; AI agents; complex engineering systems; simulation and optimization; digital twins; multi-objective optimization; robust optimization; surrogate models; reinforcement learning; evolutionary computation
(This special issue belongs to the Section E: Applied Mathematics)
Application of Mathematical Modeling, Simulation and Artificial Intelligence to Transportation Systems, 2nd Edition submission deadline 31 May 2027 | Viewed by 24 | Submission Open
Keywords: transportation systems; applied mathematics; mathematical modeling; dynamical systems; simulation; optimization; operations research; stochastic processes; graph theory; network science; traffic flow; intelligent transportation systems; artificial intelligence; machine learning; cellular automata; agent-based modeling; sustainable mobility
(This special issue belongs to the Section D2: Operations Research and Fuzzy Decision Making)
Optimization Problems: Methods and Applications
edited by
submission deadline 20 Jun 2027 | Viewed by 578 | Submission Open
Keywords: continuous optimization; combinatorial optimization; stochastic optimization; robust optimization; sparse optimization; manifold optimization; evolutionary optimization; distributed optimization; nonsmooth optimization; machine learning; data science; artificial intelligence; neural networks
(This special issue belongs to the Section E: Applied Mathematics)
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