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This review highlights advancements in computational methods for complex systems, integrating artificial intelligence (AI) with traditional techniques. These optimized computational approaches significantly improve accuracy and efficiency in materials and energy systems engineering.

Keywords:
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Area of Science:

  • Engineering and Technology
  • Computational Science

Background:

  • Complex systems modeling, simulation, and optimization are crucial in materials, mechanical, and energy engineering.
  • Traditional computational methods have been enhanced by integrating artificial intelligence (AI).

Purpose of the Study:

  • To provide a comprehensive review of recent advancements in computational methods for complex systems.
  • To identify key trends and highlight the integration of AI with traditional computational methods.
  • To suggest novel strategies for materials production and energy systems optimization.

Main Methods:

  • Literature review of contemporary applications of advanced computational algorithms, including AI.
  • Synthesis of state-of-the-art developments in computational modeling, simulation, and optimization.
  • Analysis of improvements in accuracy and efficiency offered by integrated AI and computational methods.

Main Results:

  • Significant improvements in accuracy and efficiency demonstrated through advanced computational methods.
  • Identification of key trends, particularly the integration of AI in computational engineering.
  • Proposals for novel strategies in materials production and energy systems optimization.

Conclusions:

  • Computational methods, especially with AI integration, are critical for advancing engineering and technological solutions.
  • The review offers valuable insights for researchers and practitioners in materials, mechanical, and energy systems.
  • Future research directions are suggested, emphasizing the role of these methods in optimizing material properties for energy applications.