Aims and Scope

AUT Journal of Modeling and Simulation

Most research and experiments in the fields of science and engineering have been spending significant efforts to extract rules from various complicated phenomena by observations, recorded data, analytical or experimental derivations and so on (Modeling ). The rules are normally formulated by quantitative expressions (quantitative models) or qualitative expressions (qualitative models). Simulation and Identification provides mechanisms to establish the models and Control provides mechanisms to improve the performance of the system, represented by their models.


Aims & Scope

The AUT Journal of Modeling and Simulation (AJMS) is a Bi-quarterly journal which provides an international forum for researchers, scholars, and engineers in the fields of system modeling, identification, simulation and control to publish high-quality and refereed papers, including the latest theoretical results and their practical applications.

The covered technical areas include, but not limited to:

  • Mathematical Modeling
  • Model-free (experimental) Modeling
  • Applications of modeling and simulation in the following disciplines:
    • Robotic and mechatronic systems
    • Biological and medical systems 
    • Electromagnetic systems
    • Agricultural and environmental systems
    • Industrial, military, aerospace systems
    • Power systems
    • Economic and Financial Systems
    • Social systems  
  • System identification
  • Linear and nonlinear control 
  • Optimization and optimal control
  • Robust control
  • Adaptive control
  • Networked and Cooperative control 
  • Distributed Control
  • Quantum control 
  • Soft computing and control
  • Iterative learning control 
  • Data processing 
  • Process control and instrumentation
  • Control in power electronics
  • Fault detection and isolation
  • Model predictive control
  • Stochastic control and filtering
  • Vibration and Noise Control
  • Neural networks and fuzzy logic
  • Intelligent systems 
  • Hybrid systems
  • Discrete event systems 
  • Multi-agent Systems
  • Communication Systems

Civil and Environmental Engineering:

Applications of

  • Modeling And Simulation:
    • Model Based Techniques
    • Model Free Techniques (Artificial Intelligence, and etc.)
  • Optimization and Control
  • Risk and Uncertainty Analysis
  • Cognitive Intelligence (CI) and Machine Learning
  • Agent Based Modeling
  • Data Analytics
  • Decision Analysis and Multi-attribute Decision Making
  • Sustainability Analysis

in Civil and Environmental Engineering.