scholarly journals Safety Risk Assessment of Tourism Management System Based on PSO-BP Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wenru Guo
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Management System ◽  
Evaluation Model ◽  
Risk Index ◽  
Security Risk ◽  
Bp Network ◽  
Model Based ◽  
Tourism Management ◽  
Better Than

With the development of science and technology, system management is gradually applied to tourism management. How to correctly assess the security risks of the tourism management system has become an important means to maintain passenger information. The security risk index of the travel management system is input into the PSO-BP network as a sample, and the corresponding risk value of the index is used as the network output. The results show that the error results, accuracy (96.53%), training time (216 s), number of iterations (275 times), and convergence speed are all better than traditional BP network. The relative error of PSO-BP network (0.32%) is better than that of BP network, with 300 iterations, and the error is close to 10–5. The average evaluation accuracy of S based on PSO-BP network is 99.72%, and the average time consumed is 2.512 s. It is superior to the evaluation model based on fuzzy set and entropy weight theory and the evaluation model based on gray correlation analysis and radial basis function neural network. In conclusion, the security risk assessment of the tourism management system based on PSO-BP network can effectively assess the security risk of the tourism management system.

The Coal Mine Flooding Emergency Ability Evaluation Based on GA-WNN

2012 ◽  
Vol 452-453 ◽  
pp. 782-788
Author(s):  
Jin Feng Wang ◽  
Li Jie Feng ◽  
Zhao Hui Li
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Coal Mine ◽  
Evaluation Model ◽  
Wavelet Neural Network ◽  
Time Frequency ◽  
Model Based ◽  
Time Frequency Localization ◽  
Mine Flooding ◽  
Ability Evaluation

For the coal resources working which are affected by the coal mine flooding seriously, this paper make an analysis on the factors which affect the coal mine flooding emergency ability evaluation model based on GA-WNN is established through the wavelet neural network value which is optimized with genetic algorithm. This model combined the global optimization ability of genetic algorithm with the time-frequency localization of wavelet neural network. This combination can make up for many defects (for example, the neural network structure should be given artificially, the function can got local minimum easily and so on). Therefore, the local mine flooding emergency ability evaluation model based on genetic algorithm and wavelet neural network have higher reliability and calculation ability, and is beneficial to the pre-control management for coal mine flooding rescue.

A Model Based on BP Neural Network for Audible Noise Prediction

2014 ◽  
Vol 986-987 ◽  
pp. 1356-1359
Author(s):  
You Xian Peng ◽  
Bo Tang ◽  
Hong Ying Cao ◽  
Bin Chen ◽  
Yu Li
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Transmission Lines ◽  
Bp Neural Network ◽  
Prediction Models ◽  
Absolute Error ◽  
Research Area ◽  
Noise Prediction ◽  
Bp Network ◽  
Model Based

Audible noise prediction is a hot research area in power transmission engineering in recent years, especially come down to AC transmission lines. The conventional prediction models at present have got some problems such as big errors. In this paper, a prediction model is established based on BP network, in which the input variables are the four factors in the international common expression of power line audible noise and the noise value is the output. Take multiple measured power lines as an example, a train is made by the BP network and then the prediction model is set up in the hidden layer of the network. Using the trained model, the audible noise values are predicted. The final results show that the average absolute error in absolute terms of the values by the audible noise prediction model based on BP neural network is 1.6414 less than that predicted by the GE formula.

Research on the Security Risk Assessment of Military Vehicles Based on Could Gravity Center Valuation

2014 ◽  
Vol 556-562 ◽  
pp. 6568-6572
Author(s):  
Hai Tian ◽  
Xiao Ting Jiang ◽  
Wu Jun Zhang
Keyword(s):  
Risk Assessment ◽  
Quantitative Evaluation ◽  
Evaluation Model ◽  
Qualitative Evaluation ◽  
Security Risk ◽  
Gravity Center ◽  
Military Vehicles ◽  
Security Risk Assessment

In view of the complexity forces of security risk assessment of military vehicles, could gravity center valuation was studied. First the concept, purpose and meaning, main steps of security risk assessment of military vehicles was analyzed, and then the algorithm in detail of security risk assessment of military vehicles based on could gravity center valuation was given out, finally was validated by an example. Verification results show that this method is the subjective qualitative evaluation with quantitative evaluation model, solve the fuzziness and the randomness of the assessment, as the security risk assessment of military vehicles provides a set of effective methods.

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