Comparative analysis of BP neural network and RBF neural network in seismic performance evaluation of pier columns

Liu, Qinglin; Sun, Panxu; Fu, Xueyi; Zhang, Jian; Yang, Hong; H, Gao; Li, Yazhou

doi:10.1016/j.ymssp.2020.106707

Cited by 45 publications

(17 citation statements)

References 11 publications

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“…Accordingly, they used 1676 sets for training. Liu et al (2020) collected a total of 72 sets of actual engineering test data and experimental data. Among them, 60 sets of data are used to prepare a training set, and the remaining sets of data are considered as the prediction set so that the ratio of about 1:5 is achieved.…”

Section: Discussionmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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Studies show that there are shortcomings in applying conventional methods for the emotional evaluation of the aircraft cockpit. In order to resolve this problem, a more efficient cockpit emotion evaluation system is established in the present study to simply and quickly obtain the cockpit emotion evaluation value. To this end, the neural network is applied to construct an emotional model to evaluate the emotional prediction of the interior design of the aircraft cockpit. Moreover, several technologies and the Kansei engineering method are applied to acquire the cockpit interior emotional evaluation data for typical aircraft models. In this regard, the radical basis function neural network (RBFNN), Elman neural network (ENN), and the general regression neural network (GRNN) are applied to construct the sentimental prediction evaluation model. Then, the three models are comprehensively compared through factors such as the model evaluation criteria, network structure, and network parameters. Obtained experimental results indicate that the GRNN not only has the highest classification accuracy but also has the highest stability in comparison to the other two neural networks, so that it is a more appropriate method for the emotional evaluation of the aircraft cockpit. Results of the present study provide decision supports for the emotional evaluation of the cockpit interior space.

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Section: Discussionmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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“…The basic principles of the combination model are to combine a few different single prediction models or some information provided by several single factors in a certain way to get a more integrated and credible model. It will make the single model complementary to each other and improve the prediction accuracy of the model, making the prediction result more ideal (Liu et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Innovation Strategy of Cultivating Innovative Enterprise Talents for Young Entrepreneurs Under Higher Education

Zhang

2021

Front. Psychol.

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A time series model is designed based on the backpropagation neural network to further optimize the innovation and development of new ventures. The specific situation of two factors is primarily analyzed as follows: the supply and demand ratio of enterprise talents and the state of entrepreneurship in the development of new ventures. The results show that the potential demand of future enterprises for big data talents can be obtained by fitting prediction sequences. Based on the Backpropagation–Autoregressive Integrated Moving Average model, the post modeling and prediction are carried out, and the coefficient 0.6235 is obtained by substituting the equation of Pearson's correlation coefficient. The analysis results suggest that the matching needs to be strengthened between the cultivation of innovative talents in universities and the demand trend of big data-related positions in enterprises. Moreover, there is a mismatch between the cultivation of innovative talents and the demand for innovative talents. Meanwhile, the mental health level of young entrepreneurs is concerned. The mental health status of young entrepreneurs is compared with the national norm data through the questionnaire survey and statistical data analysis. The results reveal that the mental health level of young entrepreneurs is significantly lower than that of the national norm, and the proportion of anxiety and depression is 29.4% and 27.5%, respectively. Considering the professional characteristics and competitive environment of young entrepreneurs, busy work and the multiple missions given by society to entrepreneurs are the major reasons for their pressure, and mental health problems are serious.

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“…Since the approximation ability has been proved, they have drawn much attention to various areas, such as classification, nonlinear system modeling, and adaptive control [45][46][47]. Nevertheless, RBF neural networks still face challenges and open problems on how to model nonlinear systems accurately and fast [48,49]. e primary questions for designing RBF neural networks involve two aspects [50]: (1) the construction of a network structure (the hidden layer size and initial parameters); (2) the optimization of all the parameters (centers, radii, and weights).…”

Section: Rbf Neural Network Radial Basis Function (Rbf) Neuralmentioning

confidence: 99%

Evaluation of Cruise Ship Supply Logistics Service Providers with ANP-RBF

Huang

Tan

Guan

2021

Journal of Advanced Transportation

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To overcome challenges like market dynamic configuration, information integration, and quick response, it is necessary to build an efficient, stable, and well-coordinated supply chain relationship for cruise ship supply. This requires building of a solid evaluation index system of logistics service providers (LSPs) in the cruise ship supply chain. In this paper, we introduce an evaluation index system that consists of four dimensions, based on the characteristics of cruise ship supply and the connotation and type of cruise ship supply LSPs. The four dimensions are business level, collaborative capacity, service price, and information level, including ten subcriteria. We first establish an evaluation decision model for the interdependence and feedback relationship between the criteria by using analytic network process (ANP) for weight definition of each index; then, we use Super Decisions software to simulate the results, combine RBF neural network training and validation, and extract implicit knowledge and laws. We propose an incremental algorithm that can effectively avoid the influence of subjective factors and increase the dynamic nature of evaluation. The results show that the ANP-RBF method has strong practicability in the evaluation of cruise ship supply LSPs.

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Comparative analysis of BP neural network and RBF neural network in seismic performance evaluation of pier columns

Cited by 45 publications

References 11 publications

Evaluating aircraft cockpit emotion through a neural network approach

Evaluating aircraft cockpit emotion through a neural network approach

Innovation Strategy of Cultivating Innovative Enterprise Talents for Young Entrepreneurs Under Higher Education

Evaluation of Cruise Ship Supply Logistics Service Providers with ANP-RBF

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