A Method for Evaluating the Capability Adaptability of Equipment Groups Considering Dynamic Weight Adjustment

To address the issues of incomplete indicator coverage and dynamic weights not aligning with changes in the external environment in the evaluation of equipment group capability adaptability—resulting in biased evaluation results and poor applicability—this study proposes an equipment group capability adaptability evaluation method considering dynamic weight adjustment. Firstly, a four-dimensional indicator system encompassing capability requirement adaptability, equipment collaboration adaptability, external environment adaptability, and cycle support adaptability is constructed, and an association model for each indicator is designed. Secondly, an Long Short-Term Memory (LSTM)–Bayesian combined dynamic weight calculation method is proposed to compute the equipment group capability adaptability. Finally, case verification results show that the four-dimensional indicators match phase-specific requirements and the dynamic weights are accurately adjusted with phases, indicating that the method is reasonable and reliable. It can provide technical support for equipment group adaptability decision-making in dynamic scenarios.