Computer Science ›› 2017, Vol. 44 ›› Issue (5): 89-94.doi: 10.11896/j.issn.1002-137X.2017.05.016

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Hazard Identification Algorithm Based on Deep Extreme Learning Machine

LI Shi-yao, ZHOU Liang and LIU Hu   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Hazard identification plays an important role in aviation safety management.The results of hazard identification must be highly accurate to ensure the safety of the flight.To this end,a hazard identification algorithm based on deep extreme learning machine (HIELM) was proposed,which consists of multiple deep stacked ELMs and a single ELM.There are a parallel structure and different number of hidden nodes among these deep ELMs,and the hazard information is gotten to produce deep features according to the hazard area.In addition,the way of generating input weights has been enhanced with recognition features.The single ELM receives the results as its input.With the help of the improved back propagation algorithm,the network can achieve much better accuracy.The thought that deep ELMs are trained respectively alleviates the memory pressure and the over fitting phenomenon when facing the high-dimensional datasets.

Key words: Hazards identification,Deep learning,Extreme learning machine (ELM),Clas sification

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