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Hatef Dastour and Quazi K. Hassan
Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread. In such situations, recurring data gaps can lead to unfavora...
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Shutian Deng, Gang Wang, Hongjun Wang and Fuliang Chang
Spain possesses a vast number of poems. Most have features that mean they present significantly different styles. A superficial reading of these poems may confuse readers due to their complexity. Therefore, it is of vital importance to classify the style...
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Guido Bologna
In machine learning, ensembles of models based on Multi-Layer Perceptrons (MLPs) or decision trees are considered successful models. However, explaining their responses is a complex problem that requires the creation of new methods of interpretation. A n...
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Marta Galvani, Chiara Bardelli, Silvia Figini and Pietro Muliere
Bootstrap resampling techniques, introduced by Efron and Rubin, can be presented in a general Bayesian framework, approximating the statistical distribution of a statistical functional ϕ(F)" role="presentation">??(??)?(F)
?
(
F
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, where F is a...
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Germania Vayas-Ortega, Cristina Soguero-Ruiz, Margarita Rodríguez-Ibáñez, José-Luis Rojo-Álvarez and Francisco-Javier Gimeno-Blanes
The search for an unbiased company valuation method to reduce uncertainty, whether or not it is automatic, has been a relevant topic in social sciences and business development for decades. Many methods have been described in the literature, but consensu...
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Ernest Kwame Ampomah, Zhiguang Qin and Gabriel Nyame
Forecasting the direction and trend of stock price is an important task which helps investors to make prudent financial decisions in the stock market. Investment in the stock market has a big risk associated with it. Minimizing prediction error reduces t...
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Hyeong-Tak Lee, Jeong-Seok Lee, Woo-Ju Son and Ik-Soon Cho
Ships are prone to accidents when approaching in a berthing velocity greater than that allowed when determining the risk range corresponding to a port. Therefore, this study develops a machine learning strategy to predict the risk range of an unsafe bert...
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Syed Waqas Haider Shah, Khalid Iqbal and Ahmad Talal Riaz
The Internet-of-Things (IoT) is a paradigm shift from slow and manual approaches to fast and automated systems. It has been deployed for various use-cases and applications in recent times. There are many aspects of IoT that can be used for the assistance...
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Roozbeh Hasanzadeh Nafari, Tuan Ngo, Priyan Mendis
Pág. 1 - 18
Flood is a frequent natural hazard that has significant financial consequences for Australia. In Australia, physical losses caused by floods are commonly estimated by stage-damage functions. These methods usually consider only the depth of the water and ...
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Mei Zhang
Fraud and error are two underlying sources of misstated financial statements. Modern machine learning techniques provide a potential direction to distinguish the two factors in such statements. In this paper, a thorough evaluation is conducted evaluation...
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