Farhana Akter Sunny, Petr Hájek, Michal Munk, Mohammad Zoynul Abedin et al.
For this study, the researchers conducted a systematic literature review to answer complex questions about the field of blockchain technology. We used an unbiased systematic review process to find works on blockchain-based applications and developed a Python code that searched various online databas...
Shanglei Chai, Wenjun Chu, Zhen Zhang, Zhilong Li et al.
This paper uses weekly data from July 01, 2011 to July 09, 2021 to examine the dynamic nonlinear connectedness between the green bonds, clean energy, and stock price around the COVID-19 outbreak in the global markets. By building a time-varying parameter vector autoregression model (TVP-VAR), the co...
Mohammad Zoynul Abedin, Mahmudul Hasan Moon, M. Kabir Hassan, Petr Hájek
This study proposes an ensemble deep learning approach that integrates Bagging Ridge (BR) regression with Bi-directional Long Short-Term Memory (Bi-LSTM) neural networks used as base regressors to become a Bi-LSTM BR approach. Bi-LSTM BR was used to predict the exchange rates of 21 currencies agains...
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 Ashraful Ferdous Chowdhury, Mohammad Abdullah, Masud Alam, Mohammad Zoynul Abedin et al.
This paper examines the efficiency and asymmetric multifractal features of NFTs, DeFi, cryptocurrencies, and traditional assets using Asymmetric Multifractal Cross-Correlations Analysis covering the period from November 2017 to February 2022. Considering the full sample with a significant variation ...
Md Shajalal, Petr Hájek, Mohammad Zoynul Abedin
Taking backorders on products is a common scenario in inventory and supply chain management systems. The ability to predict the likelihood of backorders can surely minimise a company's losses. Because the number of backorders is much lower than the number of orders that ship on time, applying a pred...
Petr Hájek, Mohammad Zoynul Abedin
Inventory backorder prediction is widely recognized as an important component of inventory models. However, backorder prediction is traditionally based on stochastic approximation, thus neglecting the substantial amount of useful information hidden in historical inventory data. To provide those inve...
Md. Iftekharul Alam Efat, Petr Hájek, Mohammad Zoynul Abedin, Rahat Uddin Azad et al.
Fahmida E. Moula, Chi Guotai, Mohammad Zoynul Abedin
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...
Emon Kalyan Chowdhury, Mohammad Zoynul Abedin
Riya Sureka, Satish Kumar, Sisira Colombage, Mohammad Zoynul Abedin
Mohammad Zoynul Abedin, Petr Hájek, Taimur Sharif, Md. Shahriare Satu et al.
This study investigates customer behaviour and activity in the banking sector and uses various feature transformation techniques to convert the behavioural data into different data structures. Feature selection is then performed to generate feature subsets from the transformed datasets. Several clas...
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...