A comparative study of statistical failure prediction models for brittle materials

The study aims to compare the classification power of three statistical failure prediction models for evaluating financial performance of Saudi Listed Firms. The study sample consisted of 122 listed industrial companies in the Saudi Stock Exchange for the period from 2014 to 2016. Altman model 1968, Kida model and Zmijewski are used as examples of statistical failure prediction models to evaluate the classification power of the given models to assess the financial performance of firms listed on Saudi Stock Exchange. The results showed that Zmijewski model was more powerful in predicting the financial performance of Saudi listed firms than Altman model (1986) and Kida model. The results showed that there are a statistical relationships between some ratios included in the three models and the financal performance of industrial companies, which was measured by EPS. The study recommended users of financial statements of Saudi listed companies to use Zmijewski ?model, which performs well in evaluating their finacial position to be used when making the ?financial decisions.

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Comparative study of prediction models forpublic bicycle demand in Seoul

Journal of the Korean Data and Information Science Society ◽

10.7465/jkdi.2021.32.3.585 ◽

2021 ◽

Vol 32 (3) ◽

pp. 585-592

Author(s):

Soah Min ◽

Yoonsuh Jung

Keyword(s):

Comparative Study ◽

Prediction Models

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A comparative study of different prediction models in predicting human resource demands

Journal of Computational Methods in Sciences and Engineering ◽

10.3233/jcm-215788 ◽

2021 ◽

pp. 1-11

Author(s):

Bo Huang

Keyword(s):

Neural Network ◽

Human Resources ◽

Comparative Study ◽

Human Resource ◽

Prediction Models ◽

Back Propagation ◽

Back Propagation Neural Network ◽

Prediction Methods ◽

Bpnn Model ◽

Good Agreement

This study analyzed three prediction models: ID model, GM (1,1) model and back-propagation neural network (BPNN) model. Firstly, the principles of the three models were introduced, and the prediction methods of the three models were analyzed. Then, taking enterprise A as an example, the demand for human resources was predicted, and the prediction results of the three models were compared. The results showed that the maximum and minimum errors were 240 people and 12 people respectively in the prediction results of the ID3 model and 64 people and 37 people respectively in the prediction results of the GM (1, 1) model; the errors of the BPNN model were smaller than ten people, and the minimum value of the BPNN model was three people, which was in good agreement with the actual value. The prediction of the human resource demand of enterprise A in the future five years with the BPNN model suggested that the demand for employees would growing rapidly. The results show that the BPNN model has better reliability and can be popularized and applied in practice.

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