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Differential Cloud Particles Evolution Algorithm Based on Data-Driven Mechanism for Applications of ANN.

Wei Li1

  • 1School of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China.

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A novel optimization algorithm, the differential cloud particles evolution algorithm (CPDD), inspired by matter state changes, enhances engineering problem-solving. CPDD integrates global exploration and local exploitation with a data-driven mechanism for superior performance.

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Area of Science:

  • Computational intelligence
  • Engineering optimization
  • Algorithm design

Background:

  • Computational algorithms often draw inspiration from natural processes like evolution.
  • Engineering optimization problems require efficient and effective solution methods.

Purpose of the Study:

  • To introduce a novel optimization algorithm, the differential cloud particles evolution algorithm (CPDD), inspired by phase transitions in matter.
  • To enhance algorithm performance using a data-driven mechanism for parameter control.

Main Methods:

  • The CPDD algorithm divides the optimization process into fluid and solid stages, balancing global exploration and local exploitation.
  • A data-driven mechanism is employed to optimize control parameters for improved search efficiency.
  • The algorithm's effectiveness is validated using CEC2014 benchmark functions and artificial neural network applications.

Main Results:

  • CPDD demonstrated competitive performance against eight other state-of-the-art intelligent optimization algorithms.
  • Numerical experiments on benchmark functions confirmed the algorithm's effectiveness.
  • Successful application to artificial neural network problems was observed.

Conclusions:

  • The proposed CPDD algorithm offers a competitive approach to solving complex engineering optimization problems.
  • The integration of a data-driven mechanism significantly improves parameter control and overall algorithm performance.
  • CPDD shows promise for applications in areas like artificial neural networks.