A New Model of Interval-Valued Intuitionistic Fuzzy Weighted Operators and Their Application in Dynamic Fusion Target...

Area of Science:

• Missile Defense Systems
• Artificial Intelligence
• Decision Support Systems

Background:

• Current missile defense target threat assessment methods lack accuracy due to ignoring temporal dynamics and battlefield changes.
• This limitation necessitates advanced methods for real-time, dynamic threat evaluation.

Purpose of the Study:

• To propose a dynamic multi-time fusion target threat assessment method for enhanced missile defense.
• To improve the accuracy and reliability of threat assessment by integrating multi-source uncertain information and temporal data.

Main Methods:

• Developed novel interval-valued intuitionistic fuzzy weighted averaging (IVIFWAA) and geometric averaging (IVIFWGA) operators.
• Introduced an interval-valued intuitionistic fuzzy entropy based on a cosine function (IVIFECF) for attribute weighting.
• Constructed an improved interval-valued intuitionistic fuzzy number distance measurement model and utilized the TOPSIS method for threat ordering.

Main Results:

• The proposed method effectively aggregates multi-source uncertain information across multiple time points and decision-makers.
• The integration of temporal information and attribute weighting significantly enhances assessment discrimination.
• Simulation results demonstrate a marked improvement in the reliability and accuracy of target threat assessment.

Conclusions:

• The dynamic multi-time fusion method offers a significant advancement in missile defense target threat assessment.
• The approach provides a robust framework for handling uncertainty and temporal dynamics in complex battlefield environments.
• This research contributes to more effective and reliable missile defense capabilities.