Abstract
For evaluating the cooperative combat effectiveness of unmanned aerial vehicles (UAVs), traditional entropy methods have an undue weight coefficient of the index due to its high degree of dispersion, and the interrelationship between the indices are not considered. To deal with this problem, this paper proposes a conditional entropy combination weighting method for evaluating the cooperative combat effectiveness of UAVs. Firstly, with the aim of establishing the UAV cooperative combat index system, the modified Delphi method has been combined with analytic hierarchy process (AHP) and interval estimation. This method has been used for estimating the degree of contribution of each index and to remove the indices that have a low contribution. Secondly, the principle of conditional entropy has been introduced for modifying the entropy method with the consideration of the interrelation between the indices. Finally, the modified entropy and AHP have been combined to assign the final weight in the UAV cooperative combat system. Testing results demonstrate that the index system established by this method is more comprehensive and reasonable as compared to that established by the traditional Delphi method. Compared with the single weighted method, this method is more suitable for the evaluation system of UAVs cooperative combat effectiveness.
Highlights
In recent years, unmanned combat aircrafts are being increasingly used in modern battlefields (Dai and Long 2013)
For evaluating the cooperative combat effectiveness of unmanned aerial vehicles (UAVs), traditional entropy methods have an undue weight coefficient of the index due to its high degree of dispersion, and the interrelationship between the indices are not considered. To deal with this problem, this paper proposes a conditional entropy combination weighting method for evaluating the cooperative combat effectiveness of UAVs
With the aim of establishing the UAV cooperative combat index system, the modified Delphi method has been combined with analytic hierarchy process (AHP) and interval estimation
Summary
In recent years, unmanned combat aircrafts are being increasingly used in modern battlefields (Dai and Long 2013). Considering the influence of the subjective and objective factors in the complex background of UAV cooperative combat comprehensively (Shi et al 2019), the principle of conditional entropy has been introduced into the entropy method, and the index has been weighted by combining the modified entropy method with AHP. Evaluation of Unmanned Aerial Vehicles Cooperative Combat Effectiveness Based on Conditional Entropy Combination Weight Method subjective will of the experts to determine the index system (Guo et al 2014). This method has strong subjectivity and a large uncertainty, and the constructed index system is incomplete.
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