Research on Effectiveness Evaluation of Equipment Maintenance Support Based on Simulation

He, Yongle; Hu, Fangyi; Lv, Lingling; Zhou, Chong‐Wen; Xiao, Xiangjie; Wang, Lujun

doi:10.1109/icicas48597.2019.00079

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…erefore, before sample training, the data must be normalized and transformed into a standardized interval [0,1]. e maintenance support effectiveness index is divided into benefit-index and Complexity cost-index, which have the characteristics of the bigger the better and the smaller the better [25]. is paper uses the range method to normalize these two types of indexes.…”

Section: Data Processingmentioning

confidence: 99%

Equipment Maintenance Support Effectiveness Evaluation Based on Improved Generative Adversarial Network and Radial Basis Function Network

Jian-ping

Gao

2021

Complexity

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Due to the lack of maintenance support samples, maintenance support effectiveness evaluation based on the deep neural network often faces the problem of small sample overfitting and low generalization ability. In this paper, a neural network evaluation model based on an improved generative adversarial network (GAN) and radial basis function (RBF) network is proposed to amplify maintenance support samples. It adds category constraint based on category probability vector reordering function to GAN loss function, avoids the simplification of generated sample categories, and enhances the quality of generated samples. It also designs a parameter initialization method based on parameter components equidistant variation for RBF network, which enhances the response of correct feature information and reduces the risk of training overfitting. The comparison results show that the mean square error (MSE) of the improved GAN-RBF model is 5.921 × 10 − 4 , which is approximately 1/2 of the RBF model, 1/3 of the Elman model, and 1/5 of the BP model, while its complexity remains at a reasonable level. Compared with traditional neural network evaluation methods, the improved GAN-RBF model has higher evaluation accuracy, better solves the problem of poor generalization ability caused by insufficient training samples, and can be more effectively applied to maintenance support effectiveness evaluation. At the same time, it also provides a good reference for evaluation research in other fields.

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Section: Data Processingmentioning

confidence: 99%

Equipment Maintenance Support Effectiveness Evaluation Based on Improved Generative Adversarial Network and Radial Basis Function Network

Jian-ping

Gao

2021

Complexity

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“…Previous research of maintenance support effectiveness evaluation mainly started from the point of view of equipment maintenance support elements, objects or system operation, and then carried out effectiveness evaluation. He et al [1] put forward a multi-layer equipment maintenance support effectiveness evaluation index system, and designed a combination weighting method combining improved analytic hierarchy process and principal component analysis, which effectively solved the problem of consistency and subjective randomness of judgment matrix when there were too many indexes in analytic hierarchy process. On the basis of scientific analysis of shipyards and maintenance support resources, Feng et al [2] used the evaluation method based on fuzzy analytic hierarchy process (FAHP) to evaluate the shipbuilding and repair capabilities of shipyards, which effectively improved the efficiency of manufacturing and maintenance resources.…”

Section: Introductionmentioning

confidence: 99%

Overview on Combat-oriented Equipment Maintenance Support Effectiveness Evaluation

Zhen¹

2021

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Under the situation that the army vigorously advocates combat-oriented training, equipment maintenance support effectiveness evaluation must be combat-oriented, so as to obtain meaningful evaluation conclusions. Combined with the current background of combat-oriented training of troops, this paper summarizes the main definitions, evaluation elements, evaluation process and other basic contents of maintenance support effectiveness evaluation, analyzes three key issues: definition of important concepts, construction of index system and application of evaluation methods, combs out representative viewpoints, summarizes the shortcomings and challenges in combat-oriented evaluation, and puts forward prospects for future development. The research results enrich the research content of combat-oriented maintenance support effectiveness evaluation, and have certain guiding significance for the follow-up research.

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Research on Effectiveness Evaluation of Equipment Maintenance Support Based on Simulation

Cited by 2 publications

References 5 publications

Equipment Maintenance Support Effectiveness Evaluation Based on Improved Generative Adversarial Network and Radial Basis Function Network

Equipment Maintenance Support Effectiveness Evaluation Based on Improved Generative Adversarial Network and Radial Basis Function Network

Overview on Combat-oriented Equipment Maintenance Support Effectiveness Evaluation

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