Recent Trends in Mathematics
Applied Sciences ISSN 3139-6364 2 issues a year Hybrid open access
About the journal
Recent Trends in Mathematics is a peer-reviewed Online academic Journal dedicated to exploring and disseminating cutting-edge developments, novel concepts, and emerging trends in the field of mathematics. The Journal serves as a platform for mathematicians, researchers, and scholars to share their contributions to the evolving landscape of mathematical sciences. It aims to foster collaboration and inspire innovation in the mathematical community by showcasing the most recent and influential trends in mathematics.
Journal metrics
Counted from this archive, not supplied by anyone.
- 28Articles published
- 10Published in 2026
- 57Authors
- 0Open access
Journal information
- Title
- Recent Trends in Mathematics
- Issues per year
- 2 issues
- P-ISSN
- 3139-6364
- Publisher
- STM Journals
- Starting year
- 2024
- Subject
- Applied Sciences
- Publication format
- Hybrid open access
- Language
- English
- Type
- Peer-reviewed journal (refereed)
Editorial board
-
Editor-in-Chief
Mathematics, Faculty of Science, Marmara University,, Turkey
Latest articles
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Complex Space-Time and the Structure of Relativistic Quantum Theory
Abstract: Relativistic quantum mechanics was developed to reconcile the principles of quantum mechanics with Einstein’s theory of relativity. Despite its success in describing high-energy particles, the theory continues to face unresolved conceptual and mathematical difficulties, particularly in relation to the nature of time, causality, and relativistic consistency. In recent years, the idea of extending space-time into the complex domain has emerged as a useful and potentially meaningful approach to these problems. …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 22–27 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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A Study of Fixed-Point and Best Proximity Point
Abstract: Fixed-point theory plays a fundamental role in nonlinear analysis and has significant applications in optimization, differential equations, and applied mathematics. This study investigates the existence and properties of fixed points and best proximity points for various classes of mappings defined on metric and normed spaces. While fixed-point results guarantee the existence of a point that remains invariant under a given mapping, such points may not exist when the mapping is …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 28–39 Read article