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Pablo de Llano, Carlos Piñeiro, Manuel Rodríguez
Pág. pp. 163 - 198
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the...
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Zhangping Wei and Hai Cong Nguyen
This study presents an encoder?decoder neural network model to forecast storm surges on the US North Atlantic Coast. The proposed multivariate time-series forecast model consists of two long short-term memory (LSTM) models. The first LSTM model encodes t...
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Mayra Salcedo-Gonzalez, Julio Suarez-Paez, Manuel Esteve and Carlos Enrique Palau
This article presents the development of a geo-visualization tool, which provides police officers or any other type of law enforcement officer with the ability to conduct the spatiotemporal predictive geo-visualization of criminal activities in short and...
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Song Hu, Qi Shao, Wei Li, Guijun Han, Qingyu Zheng, Ru Wang and Hanyu Liu
Data-driven predictions of marine environmental variables are typically focused on single variables. However, in real marine environments, there are correlations among different oceanic variables. Additionally, sea?air interactions play a significant rol...
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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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Apostolos Ampountolas
Over the past years, cryptocurrencies have drawn substantial attention from the media while attracting many investors. Since then, cryptocurrency prices have experienced high fluctuations. In this paper, we forecast the high-frequency 1 min volatility of...
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Olalekan Oshodi, Obuks Augustine Ejohwomu, Ibukun Oluwadara Famakin, Paulo Cortez
Pág. 109 - 123
The poor performance of projects is a recurring event in the construction sector. Information gleaned from literature shows that uncertainty in project cost is one of the significant causes of this problem. Reliable forecast of construction cost is usefu...
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Olalekan Oshodi, Obuks Augustine Ejohwomu, Ibukun Oluwadara Famakin, Paulo Cortez
Pág. 109 - 123
The poor performance of projects is a recurring event in the construction sector. Information gleaned from literature shows that uncertainty in project cost is one of the significant causes of this problem. Reliable forecast of construction cost is usefu...
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Fengrui Zhang, Dayong Ning, Jiaoyi Hou, Hongwei Du, Hao Tian, Kang Zhang and Yongjun Gong
Efficiently salvaging shipwrecks is of the utmost importance for safeguarding shipping safety and preserving the marine ecosystem. However, traditional methods find it difficult to salvage shipwrecks in deep water. This article presents a novel salvage t...
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Eva Romano-Moreno, Antonio Tomás, Gabriel Diaz-Hernandez, Javier L. Lara, Rafael Molina and Javier García-Valdecasas
The good performance of the port activities in terminals is mainly conditioned by the dynamic response of the moored ship system at a berth. An adequate definition of the highly multivariate processes involved in the response of a moored ship at a berth ...
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Arne Vogler and Florian Ziel
The present paper considers the problem of choosing among a collection of competing electricity price forecasting models to address a stochastic decision-making problem. We propose an event-based evaluation framework applicable to any optimization proble...
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Hatice Erkekoglu,Aweng Peter Majok Garang,Adire Simon Deng
Pág. 206 - 216
While various linear and nonlinear forecasting models exist, multivariate methods like VAR, Exponential smoothing, and Box-Jenkins? ARIMA methodology constitute the widely used methods in time series. This paper employs series of Turkish private co...
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Daniel Silva Campos, Yara de Souza Tadano, Thiago Antonini Alves, Hugo Valadares Siqueira, Manoel Henrique de Nóbrega Marinho
Pág. e48203
Air pollution is a relevant issue studied worldwide, and its prediction is important for social and economic management. Linear multivariate regression models (LMR) and artificial neural networks (ANN) are widely applied to forecasting concentrations of ...
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Daniel Silva Campos, Yara de Souza Tadano, Thiago Antonini Alves, Hugo Valadares Siqueira, Manoel Henrique de Nóbrega Marinho (Author)
Pág. e48203
Air pollution is a relevant issue studied worldwide, and its prediction is important for social and economic management. Linear multivariate regression models (LMR) and artificial neural networks (ANN) are widely applied to forecasting concentrations of ...
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Afees A. Salisu, Kazeem O. Isah, Alberto Assandri
Pág. 255 - 283
This study examines probable dynamic spillover transmissions between the Nigerian stock and money markets using the multivariate volatility framework that simultaneously accounts for both returns and shock spillovers. Based on relevant pre-tests, the VAR...
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Wessel M. Badenhorst
AbstractAnalysts? earnings and book value forecasts play an important role in price discovery in equity markets. As the role of fair value measurements in accounting increases, the impact on analysts? ability to accurately forecast earnings and book valu...
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Yassine Belasri,Rachid Ellaia
Pág. 384 - 396
Volatility and correlation are important metrics of risk evaluation for financial markets worldwide. The latter have shown that these tools are varying over time, thus, they require an appropriate estimation models to adequately capture their dynamics. M...
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Hong-Li Ren and Pengfei Ren
The impact of Madden?Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function ...
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S. GHOSH,P. K. SEN,U. K. DE
The two sophisticated applied multivariate techniques, ?Principal Component Analysis? and ?Two-group Linear Discriminant Analysis? have been applied in the present work to analyze the pre-monsoon weather in Calcutta (India) and hence to forecast the p...
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Aymane Ahajjam, Jaakko Putkonen, Emmanuel Chukwuemeka, Robert Chance and Timothy J. Pasch
Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weathe...
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