Equipment Support Training Level Evaluation Method based on ANFIS

Abstract:

The evaluation of equipment support training is an effective way to improve training efficiency. The main influencing factors of equipment support training are analyzed. Adaptive neural fuzzy inference system (ANFIS) model structure is established and the hybrid-learning algorithm to solve the established model by applying back-propagation and least mean squares procedure is investigated. Then the evaluation model of equipment support training level based on ANFIS is constructed. The training level consistent with the actual training level is achieved by training the proposed model using training data samples, which verifies the correctness and effectiveness of the proposed method. Simulation comparing analysis using the proposed method and BP neutral network is conducted respectively. The superiority of the proposed method is verified by simulation results, which provides an effective method for equipment support training evaluation.

• Periodical: Advanced Materials Research (Volumes 706-708)
• Pages: 1950-1953
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.706-708.1950
• Online since: June 2013
• Authors: Wu Kui Zhao, Cheng Zhang, Yi Bo Wang
• Keywords: Adaptive Neural Fuzzy Inference System (ANFIS), Equipment Support Training, Level Evaluation

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