Aiming at the problem of complex working mechanism of aeroengine gas path system and difficulty in effective fault diagnosis in actual work,a new fault diagnosis method of aeroengine gas path based on graywolf Optimi...
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Aiming at the problem of complex working mechanism of aeroengine gas path system and difficulty in effective fault diagnosis in actual work,a new fault diagnosis method of aeroengine gas path based on graywolfoptimization Deep Extreme Learning Machine(GWO-DELM) is ***,analyze a large amount of monitoring data of a certain type of aeroengine gas path components,and sort out the health data and fault sample data ***,create the DELM fault diagnosis model by the health data and fault sample data set of the aeroengine gas circuit *** reduce the influence of artificially setting network parameters on the diagnosis results,the gray wolf optimization algorithm(GWO) is used to optimize the DELM network parameters,and the optimal DELM fault diagnosis model GWO-DELM is ***,the GWO-DELM fault diagnosis model is used to study the fault diagnosis verification technology of the aeroengine air circuit system,and the diagnosis results of the ELM,DELM and Multilayer Kernel Extreme Learning Machine(ML-KELM) fault diagnosis models are *** result shows that the fault diagnosis accuracy of the proposed GWO-DELM fault diagnosis model is 96.0%,which is significantly higher than that of the ELM model of 88.0%,the DELM model of 92.0% and the ML-KELM model of 94.0%,the effectiveness of the proposed method is verified,and it has a good application prospect.
INTRODUCTION: The optimization of the teaching evaluation system, as an essential part of teaching reform in higher vocational colleges and universities, is conducive to the development of higher vocational colleges a...
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INTRODUCTION: The optimization of the teaching evaluation system, as an essential part of teaching reform in higher vocational colleges and universities, is conducive to the development of higher vocational colleges and universities' disciplines, making the existing teaching more standardized. OBJECTIVES: Aiming at the problems of inefficiency, incomplete index system, and low assessment accuracy in evaluation methods of higher vocational colleges and universities. METHODS: Proposes a teaching evaluation method for higher vocational colleges and universities with a big data mining algorithm and an intelligent optimizationalgorithm. Firstly, the teaching evaluation index system of higher vocational colleges and universities is downgraded and analyzed by using principal component analysis;then, the random forest hyperparameters are optimized by the grey wolfoptimizationalgorithm, and the teaching evaluation model of higher vocational colleges and universities is constructed;finally, the validity and stability of the proposed method is verified by simulation experimental analysis. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solves the problems of low evaluation accuracy, incomplete system, and low efficiency of teaching evaluation methods in higher vocational colleges.
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