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The main contribution of this paper is to propose a financial distress prediction method based on WNNs. The financial and non-financial ratios were used to ...
Back propagation algorithm was used to train the WNNs. Principal component analysis (PCA) method was used to reduce the dimension of the inputs of the WNNs.
A financial distress prediction model based on wavelet neural networks (WNNs) that performs well in comparison with other quantitative prediction methods ...
This paper presents a financial distress prediction model based on wavelet neural networks (WNNs). The transfer functions of the neurons in WNNs are wavelet ...
The ability to predict the possibility of finan- cial distress of a company is important for many user groups such as investors, creditors,.
Back propagation algorithm was used to train the WNNs. Principal component analysis (PCA) method was used to reduce the dimension of the inputs of the WNNs.
In this research, a prediction model based on Principal Component Analysis (PCA) and a. Binary Logistics Regression (BLR) model is constructed based on the ...
Missing: WNNs. | Show results with:WNNs.
In the Chinese stock market, the unique special treatment (ST) warning mechanism can signal financial distress for listed companies.
A new fuzzy membership for FSVM combined with CBR is proposed to detect the outliers by their k-nearest neighbors, and then assign them a lower fuzzy ...
Oct 22, 2024 · Wang and Li (2007) conducted a study on Chinese listed companies for analyzing financial distress by applying rough set methodology. The authors ...