Advancing Predictive Analytics: Innovations in AI and Machine Learning for Real-World Applications

Dear Colleagues,

The integration of artificial intelligence (AI) and machine learning (ML) has catalyzed a paradigm shift in predictive analytics, fundamentally transforming data-driven decision-making processes across various industries. This Special Issue is dedicated to showcasing cutting-edge advancements in AI and ML techniques that are driving the development of accurate, scalable, and efficient predictive systems. We welcome original research articles, comprehensive reviews, and insightful case studies that explore innovative methodologies, advanced algorithms, and practical applications of predictive AI models in real-world scenarios.

The scope of this Special Issue encompasses, but is not limited to, the following key areas:

1. Advanced deep learning architectures and neural networks for predictive analytics in critical domains such as healthcare diagnostics, financial forecasting, and smart city infrastructure management.
2. Explainable AI (XAI) frameworks and methodologies aimed at enhancing the interpretability, transparency, and trustworthiness of predictive models in high-stakes decision-making environments.
3. State-of-the-art time-series forecasting techniques leveraging AI for applications in climate modeling, energy consumption optimization, and industrial process automation.
4. Edge computing and cloud-based AI solutions enabling real-time predictive analytics in Internet of Things (IoT) ecosystems and cyber–physical systems.
5. Hybrid AI models that synergistically combine statistical methods, physics-based models, and machine learning approaches to achieve superior predictive performance and domain adaptability.
6. AI-driven anomaly detection systems for cybersecurity threat identification, financial fraud prevention, and predictive maintenance in industrial settings.
7. Reinforcement learning and optimization algorithms for intelligent decision-support systems in robotics, autonomous vehicle navigation, and adaptive control mechanisms.
8. Ethical and responsible AI considerations in predictive modeling, addressing issues of fairness, accountability, and societal impact.

This Special Issue seeks to bridge the critical gap between theoretical innovations and practical implementations of AI-driven predictive systems. We particularly encourage interdisciplinary contributions that demonstrate the transformative potential of AI in forecasting, decision-making processes, and intelligent automation across various sectors. Submissions should emphasize methodological breakthroughs, rigorous comparative evaluations, or compelling case studies with demonstrable real-world impact and practical significance.

Dr. Long Wang
Dr. Chao Huang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• predictive analytics
• artificial intelligence (AI)
• machine learning (ML)
• explainable AI (XAI)
• time-series forecasting