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Konstantinos Dolaptsis, Xanthoula Eirini Pantazi, Charalampos Paraskevas, Selçuk Arslan, Yücel Tekin, Bere Benjamin Bantchina, Yahya Ulusoy, Kemal Sulhi Gündogdu, Muhammad Qaswar, Danyal Bustan and Abdul Mounem Mouazen
Irrigation plays a crucial role in maize cultivation, as watering is essential for optimizing crop yield and quality, particularly given maize?s sensitivity to soil moisture variations. In the current study, a hybrid Long Short-Term Memory (LSTM) approac...
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Shifeng Chen, Jialin Wang and Ketai He
The popularization of the internet and the widespread use of smartphones have led to a rapid growth in the number of social media users. While information technology has brought convenience to people, it has also given rise to cyberbullying, which has a ...
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Ive Botunac, Jurica Bosna and Maja Matetic
Investment decision-makers increasingly rely on modern digital technologies to enhance their strategies in today?s rapidly changing and complex market environment. This paper examines the impact of incorporating Long Short-term Memory (LSTM) models into ...
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Gaurav Narkhede, Anil Hiwale, Bharat Tidke and Chetan Khadse
Day by day pollution in cities is increasing due to urbanization. One of the biggest challenges posed by the rapid migration of inhabitants into cities is increased air pollution. Sustainable Development Goal 11 indicates that 99 percent of the world?s u...
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Amal Al Ali, Ahmed M. Khedr, Magdi El Bannany and Sakeena Kanakkayil
Despite the obvious benefits and growing popularity of Machine Learning (ML) technology, there are still concerns regarding its ability to provide Financial Distress Prediction (FDP). An accurate FDP model is required to avoid financial risk at the lowes...
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Yue Zhang, Zimo Zhou, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi
Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance...
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Federico Ricci, Luca Petrucci, Francesco Mariani and Carlo Nazareno Grimaldi
The control of internal combustion engines is becoming increasingly challenging to the customer?s requirements for growing performance and ever-stringent emission regulations. Therefore, significant computational efforts are required to manage the large ...
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Kejing Zhao, Jinliang Zhang and Qing Liu
The reasonable pricing of options can effectively help investors avoid risks and obtain benefits, which plays a very important role in the stability of the financial market. The traditional single option pricing model often fails to meet the ideal expect...
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Junhao Wu, Yuan Hu, Daqing Wu and Zhengyong Yang
Changes in the consumption price of aquatic products will affect demand and fishermen?s income. The accurate prediction of consumer price index provides important information regarding the aquatic product market. Based on the non-linear and non-smooth ch...
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Abdallah Ghourabi, Mahmood A. Mahmood and Qusay M. Alzubi
Despite the rapid evolution of Internet protocol-based messaging services, SMS still remains an indisputable communication service in our lives until today. For example, several businesses consider that text messages are more effective than e-mails. This...
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Yuelei Xiao and Qing Nian
Location prediction has attracted much attention due to its important role in many location-based services. The existing location prediction methods have large trajectory information loss and low prediction accuracy. Hence, they are unsuitable for vehicl...
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Yong Han, Cheng Wang, Yibin Ren, Shukang Wang, Huangcheng Zheng and Ge Chen
The accurate prediction of bus passenger flow is the key to public transport management and the smart city. A long short-term memory network, a deep learning method for modeling sequences, is an efficient way to capture the time dependency of passenger f...
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Shuai Ma, Yafeng Wu, Hua Zheng and Linfeng Gou
Aiming at engine health management, a novel hybrid prediction method is proposed for exhaust gas temperature (EGT) prediction of gas turbine engines. This hybrid model combines a nonlinear autoregressive with exogenous input (NARX) model and a moving ave...
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Thabang Mathonsi and Terence L. van Zyl
Hybrid methods have been shown to outperform pure statistical and pure deep learning methods at forecasting tasks and quantifying the associated uncertainty with those forecasts (prediction intervals). One example is Exponential Smoothing Recurrent Neura...
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Yong Han, Tongxin Peng, Cheng Wang, Zhihao Zhang and Ge Chen
Accurate prediction of citywide short-term metro passenger flow is essential to urban management and transport scheduling. Recently, an increasing number of researchers have applied deep learning models to passenger flow prediction. Nevertheless, the tas...
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Kossai Fakir, Chouaib Ennawaoui and Mahmoud El Mouden
Among the levers carried in the era of Industry 4.0, there is that of using Artificial Intelligence models to serve the energy interests of industrial companies. The aim of this paper is to estimate the active electrical power generated by industrial uni...
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Agaraoli Aravazhi
Recent developments in machine learning and deep learning have led to the use of multiple algorithms to make better predictions. Surgical units in hospitals allocate their resources for day surgeries based on the number of elective patients, which is mos...
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Hyunsun Song and Hyunjun Choi
Various deep learning techniques have recently been developed in many fields due to the rapid advancement of technology and computing power. These techniques have been widely applied in finance for stock market prediction, portfolio optimization, risk ma...
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Hongkang Chen, Tieding Lu, Jiahui Huang, Xiaoxing He and Xiwen Sun
Changes in sea level exhibit nonlinearity, nonstationarity, and multivariable characteristics, making traditional time series forecasting methods less effective in producing satisfactory results. To enhance the accuracy of sea level change predictions, t...
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Yizhi Wang, Jia Liu, Lin Xu, Fuliang Yu and Shanjun Zhang
Streamflow modelling is one of the most important elements for the management of water resources and flood control in the context of future climate change. With the advancement of numerical weather prediction and modern detection technologies, more and m...
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