1.289   Artículos

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en línea
Xiaofei Zhao, Caiyi Hu, Zhao Liu and Yangyang Meng    
Many kinds of spatial?temporal data collected by transportation systems, such as user order systems or automated fare-collection (AFC) systems, can be discretized and converted into time-series data. With the technique of time-series data mining, certain... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Timothy Tadj, Reza Arablouei and Volkan Dedeoglu    
Data trust in IoT is crucial for safeguarding privacy, security, reliable decision-making, user acceptance, and complying with regulations. Various approaches based on supervised or unsupervised machine learning (ML) have recently been proposed for evalu... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Simone Arena, Giuseppe Manca, Stefano Murru, Pier Francesco Orrù, Roberta Perna and Diego Reforgiato Recupero    
In the industrial domain, maintenance is essential to guarantee the correct operations, availability, and efficiency of machinery and systems. With the advent of Industry 4.0, solutions based on machine learning can be used for the prediction of future f... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yongjie Zhu, Yi Zuo and Tieshan Li    
In the current shipping industry, quantitative measures of ship fuel consumption (SFC) have become one of the most important research topics in environmental protection and energy management related to shipping operations. In particular, the rapid develo... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Zhongya Fan, Huiyun Feng, Jingang Jiang, Changjin Zhao, Ni Jiang, Wencai Wang and Fantang Zeng    
Outliers are often present in large datasets of water quality monitoring time series data. A method of combining the sliding window technique with Dixon detection criterion for the automatic detection of outliers in time series data is limited by the emp... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Trung Duy Pham,Dat Tran,Wanli Ma    
In the biomedical and healthcare fields, the ownership protection of the outsourced data is becoming a challenging issue in sharing the data between data owners and data mining experts to extract hidden knowledge and patterns. Watermarking has been prove... ver más
Revista: Australasian Journal of Information Systems    Formato: Electrónico

 
en línea
D. SINGH    
The aim of this study is to capitalize on the spatial detail of Landsat and the temporal regularity of MODIS acquisitions using a fusion approach (Spatial and Temporal Adaptive Reflectance Fusion Model, STARFM). Specifically, the 30 m Landsat-7 ETM+ (Enh... ver más
Revista: Atmósfera    Formato: Electrónico

 
en línea
Viktoriya Tsyganskaya, Sandro Martinis and Philip Marzahn    
Synthetic Aperture Radar (SAR) is particularly suitable for large-scale mapping of inundations, as this tool allows data acquisition regardless of illumination and weather conditions. Precise information about the flood extent is an essential foundation ... ver más
Revista: Water    Formato: Electrónico

 
en línea
José Francisco Lima, Fernanda Catarina Pereira, Arminda Manuela Gonçalves and Marco Costa    
Linear models, seasonal autoregressive integrated moving average (SARIMA) models, and state-space models have been widely adopted to model and forecast economic data. While modeling using linear models and SARIMA models is well established in the literat... ver más
Revista: Forecasting    Formato: Electrónico

 
en línea
Matthias Arnold and Sina Keller    
Revista: Infrastructures    Formato: Electrónico

 
en línea
Min Hu, Fan Zhang and Huiming Wu    
Various abnormal scenarios might occur during the shield tunneling process, which have an impact on construction efficiency and safety. Existing research on shield tunneling construction anomaly detection typically designs models based on the characteris... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu    
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Konstantinos Psychogyios, Andreas Papadakis, Stavroula Bourou, Nikolaos Nikolaou, Apostolos Maniatis and Theodore Zahariadis    
The advent of computer networks and the internet has drastically altered the means by which we share information and interact with each other. However, this technological advancement has also created opportunities for malevolent behavior, with individual... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Mattia Pellegrino, Gianfranco Lombardo, George Adosoglou, Stefano Cagnoni, Panos M. Pardalos and Agostino Poggi    
With the recent advances in machine learning (ML), several models have been successfully applied to financial and accounting data to predict the likelihood of companies? bankruptcy. However, time series have received little attention in the literature, w... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Xiaoou Li    
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ... ver más
Revista: Information    Formato: Electrónico

 
en línea
Yussuf Ahmed, Muhammad Ajmal Azad and Taufiq Asyhari    
In recent years, there has been a notable surge in both the complexity and volume of targeted cyber attacks, largely due to heightened vulnerabilities in widely adopted technologies. The Prediction and detection of early attacks are vital to mitigating p... ver más
Revista: Information    Formato: Electrónico

 
en línea
Renjie Chen and Nalini Ravishanker    
With the advancement of IoT technologies, there is a large amount of data available from wireless sensor networks (WSN), particularly for studying climate change. Clustering long and noisy time series has become an important research area for analyzing t... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Alan F. Smeaton and Feiyan Hu    
Periodic phenomena are oscillating signals found in many naturally occurring time series. A periodogram can be used to measure the intensities of oscillations at different frequencies over an entire time series, but sometimes, we are interested in measur... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Nikolaos Stasinos, Anestis Kousis, Vangelis Sarlis, Aristeidis Mystakidis, Dimitris Rousidis, Paraskevas Koukaras, Ioannis Kotsiopoulos and Christos Tjortjis    
The impact of COVID-19 and the pressure it exerts on health systems worldwide motivated this study, which focuses on the case of Greece. We aim to assist decision makers as well as health professionals, by estimating the short to medium term needs in Int... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Vaia I. Kontopoulou, Athanasios D. Panagopoulos, Ioannis Kakkos and George K. Matsopoulos    
In the broad scientific field of time series forecasting, the ARIMA models and their variants have been widely applied for half a century now due to their mathematical simplicity and flexibility in application. However, with the recent advances in the de... ver más
Revista: Future Internet    Formato: Electrónico

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