Mohammad Zoynul Abedin, Chi Guotai, Petr Hájek, Tong Zhang
Abstract In small business credit risk assessment, the default and nondefault classes are highly imbalanced. To overcome this problem, this study proposes an extended ensemble approach rooted in the weighted synthetic minority oversampling technique (WSMOTE), which is called WSMOTE-ensemble. The pro...
Mohammad Shamsu Uddin, Guotai Chi, Mazin A. M. Al Janabi, Tabassum Habib
Abstract This paper applies the Random Forest (RF) method for the robust modelling of credit default prediction. This technique has been proven as an efficient classifier and can provide better interpretability in comparison to other classifiers. Using Chines micro‐enterprise credit data set, this s...
Fahmida E. Moula, Chi Guotai, Mohammad Zoynul Abedin
Sanu Arora, Andrew Steed, Rachel Goddard, Kumar Gaurav et al.
Since emerging in Brazil in 1985, wheat blast has spread throughout South America and recently appeared in Bangladesh and Zambia. Here we show that two wheat resistance genes, Rwt3 and Rwt4, acting as host-specificity barriers against non-Triticum blast pathotypes encode a nucleotide-binding leucine...
Mohammad Zoynul Abedin, Guotai Chi, Mohammed Mohi Uddin, Md. Shahriare Satu et al.
This study proposes to address the economic significance of unpaid taxes by using an automatic system for predicting a tax default. Too little attention has been paid to tax default prediction in the past. Moreover, existing approaches tend to apply conventional statistical methods rather than advan...
Mohammad Zoynul Abedin, Chi Guotai, Fahmida–E– Moula, A. S. M. Sohel Azad et al.
Abstract The heart of this study is particularly on risk assessment of financial decision support systems (FDSSs), to advance the model performance and improve classification accuracy. To conquer the downsides of the classical models, statistical intelligence (SI) technologies, for example, multilay...
Guotai Chi, Mohammad Shamsu Uddin, Mohammad Zoynul Abedin, Kunpeng Yuan
Credit risk prediction is essential for banks and financial institutions as it helps them to evade any inappropriate assessments that can lead to wasted opportunities or monetary losses. In recent times, the hybrid prediction model, a combination of traditional and modern artificial intelligence (AI...
Chi GUOTAI, Mohammad Zoynul Abedin, Fahmida E–MOULA
This study proposes an investigation and optimization of Multi-Layer Perceptron (MLP) based artificial neural networks (ANN) credit prediction model, combine with the effect of different ratios of training to testing instances over five real-world credit databases. As an outcome from the alteration ...
Ying Zhou, Mohammad Shamsu Uddin, Tabassum Habib, Guotai Chi et al.
This paper aims to discover a suitable combination of contemporary feature selection techniques and robust prediction classifiers. As such, to examine the impact of the feature selection method on classifier performance, we use two Chinese and three other real-world credit scoring datasets. The util...
Mohammad Mazibar Rahman, Chi Guotai, Anupam Das Gupta, Mahmud Hossain et al.
This study examines the impact of early COVID-19 pandemic on U.S. and European stock indices, implied volatility (IV) indices, and forecasting accuracy of IV indices from daily data of January 2012 to December 2020, using an out-of-sample assessment of COVID-19. Our results show that COVID-19 death ...
Chi Guotai, Zhichong Zhao, Mohammad Zoynul Abedin
The main criteria to establish the credit risk evaluation index system is the indicators default identification ability. There is mutual influence between indices, a single index which has the default identification ability, but if put this indicator into the index system, and it will no longer have...
Sanu Arora, Andrew Steed, Rachel Goddard, Kumar Gaurav et al.
Abstract Since emerging in Brazil in 1985, wheat blast has spread throughout South America and recently appeared in Bangladesh and Zambia. We show that two wheat resistance genes, Rwt3 and Rwt4 , acting as host-specificity barriers against non-Triticum blast pathotypes encode a nucleotide-binding le...
Mohammad Shamsu Uddin, Guotai Chi, Mazin A. M. Al Janabi, Tabassum Habib et al.
Abstract This paper examines the impact of hybridizations on the classification performances of sophisticated machine learning classifiers such as gradient boosting (GB, TreeNet®) and random forest (RF) using multi‐stage hybrid models. The empirical findings confirm that, overall, hybrid model GB ( ...
Chi Guotai, Mohammad Zoynul Abedin, Fahmida E. Moula
In recent years, hybrid models have proven to be a promising approach for the forecasting of credit status, therefore, the aim of this project is to examine the prediction performance of hybrid classifiers. Particularly, the combination of the feature engineering with popular neural network (NN) cla...
Mohammad Zoynul Abedin, Guotai Chi, Meng Bin
This study investigated the presence of month of the year (MOY) effect in Dhaka Stock Exchange (DSE), Bangladesh with the data from 2000 to 2012 of DSE all share index (DSI), and DSE general index (DGEN). DSE indexes were fluctuated more over the last couple of years and the only one previous study ...