Hong Kong, February 26, 2026 — Acadlore Publishing is pleased to announce the establishment of a new peer-reviewed international journal, the Journal of Hybrid Modelling and Intelligent Engineering Systems (JHMIES). The journal has been created to provide a dedicated scholarly venue for research examining the structured integration of heterogeneous modelling approaches within contemporary engineering systems.

Modelling practices across engineering disciplines are undergoing significant transformation. Modern engineering environments increasingly require the coordinated use of multiple modelling paradigms rather than reliance on a single analytical framework. Data-driven learning models, physics-based representations, optimisation procedures, control strategies, and simulation platforms are frequently combined in order to address the structural complexity, operational variability, and performance constraints that characterise many contemporary engineering systems.

While each modelling paradigm offers particular advantages, the integration of heterogeneous models introduces new methodological questions. Issues such as the coordination of modelling components, the architectural structure of integrated systems, and the influence of modelling design on system reliability and scalability have become central topics of investigation. JHMIES has been established to provide a scholarly platform for research that examines these questions through rigorous analytical, computational, and experimental approaches.

Rather than emphasising isolated algorithmic refinement or purely theoretical modelling detached from engineering practice, the journal focuses on the structural principles through which heterogeneous modelling components are integrated within engineered systems. Particular attention is given to studies demonstrating how modelling architecture influences measurable engineering outcomes, including system stability, operational robustness, resource efficiency, and performance under realistic operating conditions.

Hybrid Modelling in Contemporary Engineering Systems

Contemporary engineering systems increasingly operate at the intersection of physical processes, digital infrastructure, and data-driven intelligence. In areas ranging from manufacturing and energy systems to robotics, transportation infrastructure, and environmental engineering, hybrid modelling has emerged as an important methodological approach for addressing system complexity.

JHMIES therefore welcomes research examining the formulation, integration, and evaluation of hybrid modelling frameworks within engineering contexts. Submissions are expected to present clearly articulated modelling structures, transparent integration logic, and well-defined validation procedures supported by analytical, computational, or experimental evidence.

Areas of interest include, among others:

• integration of data-driven learning models with physics-based representations
• coupling of optimisation procedures, predictive models, and control mechanisms
• hierarchical and multi-model architectures in complex engineering systems
• hybrid modelling within simulation environments and digital twin frameworks
• coordination of modelling components in cyber-physical and industrial systems
• robustness, reliability, and scalability analysis of integrated modelling frameworks
• predictive–prescriptive modelling integration in control and decision systems
• comparative studies evaluating alternative modelling architectures

Both methodological and application-oriented studies are welcomed, provided that submissions demonstrate a clear contribution to modelling methodology or integration architecture.

Editorial Leadership

The founding Editor-in-Chief of JHMIES is Professor Oscar Castillo of the Tijuana Institute of Technology (Instituto Tecnológico de Tijuana), Mexico. Professor Castillo is widely recognised for his influential work in computational intelligence and hybrid intelligent systems.

His research has made substantial contributions to the development of Type-2 fuzzy logic systems, fuzzy control methodologies, and hybrid soft-computing frameworks integrating neural networks, evolutionary algorithms, and fuzzy inference systems. These approaches have been applied extensively in complex engineering environments where uncertainty, nonlinear dynamics, and adaptive system behaviour require modelling strategies that extend beyond conventional analytical techniques.

Over the past two decades, Professor Castillo has authored a large body of highly cited research in areas including fuzzy control systems, neuro-fuzzy and genetic-fuzzy hybrid methods, granular computing, intelligent modelling and optimisation, and extensions of classical fuzzy system theory. His work has played an important role in advancing both the theoretical foundations and the practical applications of hybrid intelligent modelling within engineering systems.

Through extensive international collaboration and long-standing editorial experience, Professor Castillo brings strong academic leadership and global visibility to the development of the journal.

The journal is further supported by an international editorial board composed of researchers from universities and research institutions across multiple regions of the world. The board brings together expertise in computational modelling, systems engineering, intelligent control, industrial optimisation, and applied artificial intelligence, reflecting the interdisciplinary nature of hybrid modelling research.

Advancing Research on Hybrid Modelling in Engineering

Through a rigorous peer-review process, JHMIES aims to promote research that advances understanding of how heterogeneous modelling paradigms can be integrated within engineering systems in a structured and analytically transparent manner.

The journal particularly encourages studies that clarify the relationships between modelling architecture, system design, and operational behaviour. By bringing together contributions from computational modelling, systems engineering, control theory, optimisation, and applied artificial intelligence, JHMIES seeks to provide a forum for scholarly dialogue on the design, evaluation, and practical deployment of hybrid modelling systems.

Call for Papers

The Journal of Hybrid Modelling and Intelligent Engineering Systems now welcomes submissions from researchers worldwide. The journal publishes original research articles, methodological studies, theoretical analyses, systematic reviews, and well-documented empirical or computational investigations related to hybrid modelling in engineering systems.

Topics include, but are not limited to:

• hybrid modelling methodologies combining heterogeneous analytical frameworks
• integration of machine learning models, physics-based representations, and optimisation techniques
• modelling architectures for cyber-physical systems and digital twin environments
• hybrid model-based control and optimisation strategies for engineering systems
• robustness, reliability, and performance evaluation of integrated modelling frameworks
• comparative analyses of alternative modelling architectures
• hybrid modelling applications in manufacturing, energy systems, robotics, infrastructure, and environmental engineering

JHMIES is published quarterly as an open-access journal by Acadlore.

Further information about the journal can be found on the journal website:
https://www.acadlore.com/journals/jhmies

Manuscripts may be submitted through the online submission system:
https://submission.acadlore.com/user/login

Enquiries regarding submissions or editorial matters may be directed to:
jhmies@acadlore.com

About Acadlore

Acadlore is an international academic publisher dedicated to the dissemination of scholarly research across a wide range of disciplines, including engineering, computer science, environmental sciences, management, mathematics, and the physical and social sciences.

Founded in 2022, the publisher has developed a growing portfolio of nearly fifty peer-reviewed academic journals. Several journals published by Acadlore have already been indexed in major international databases, including Scopus and the Web of Science Core Collection, reflecting the publisher’s commitment to rigorous editorial standards and the long-term development of its journals.

Through international editorial boards, transparent editorial processes, and open access dissemination, Acadlore aims to support the global research community and facilitate the exchange of high-quality scientific knowledge.