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Tai-Jin Song, Sangkey Kim, Billy M. Williams, Nagui M. Rouphail and George F. List
Effective management of highway networks requires a thorough understanding of the conditions under which vehicular crashes occur. Such an understanding can and should inform related operational and resource allocation decisions. This paper presents an ea...
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Chunyang Liu, Jiping Liu, Jian Wang, Shenghua Xu, Houzeng Han and Yang Chen
Point-of-interest (POI) recommendation is one of the fundamental tasks for location-based social networks (LBSNs). Some existing methods are mostly based on collaborative filtering (CF), Markov chain (MC) and recurrent neural network (RNN). However, it i...
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Annisa Darmawahyuni, Siti Nurmaini, Sukemi, Wahyu Caesarendra, Vicko Bhayyu, M Naufal Rachmatullah and Firdaus
The interpretation of Myocardial Infarction (MI) via electrocardiogram (ECG) signal is a challenging task. ECG signals? morphological view show significant variation in different patients under different physical conditions. Several learning algorithms h...
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Santiago Pascual, Joan Serrà and Antonio Bonafonte
Conversion from text to speech relies on the accurate mapping from linguistic to acoustic symbol sequences, for which current practice employs recurrent statistical models such as recurrent neural networks. Despite the good performance of such models (in...
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Boris Pospelov,Evgeniy Rybka,Violeta Togobytska,Ruslan Meleshchenko,Yuliya Danchenko,Tetiana Butenko,Ihor Volkov,Oled Gafurov,Vadym Yevsieiev
Pág. 22 - 29
A method has been constructed for the threshold semi-adaptive scaling transformation. The method provides calculation of recurrent plots, which adequately map the dynamics of real complex dynamic systems in natural and technical spheres. A new scientific...
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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...
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Mykhailo Lohachov, Ryoji Korei, Kazuo Oki, Koshi Yoshida, Issaku Azechi, Salem Ibrahim Salem and Nobuyuki Utsumi
This article investigates approaches for broccoli harvest time prediction through the application of various machine learning models. This study?s experiment is conducted on a commercial farm in Ecuador, and it integrates in situ weather and broccoli gro...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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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...
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Haiqiang Yang and Zihan Li
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The ap...
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Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal...
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Jialun Zhang, Donglin Dong and Longqiang Zhang
Estimating groundwater level (GWL) changes is crucial for the sustainable management of water resources in the face of urbanization and population growth. Existing prediction methods for GWL variations have limitations due to their inability to account f...
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Jeongeun Won, Jiyu Seo, Jeonghoon Lee, Jeonghyeon Choi, Yoonkyung Park, Okjeong Lee and Sangdan Kim
River runoff predictions in ungauged basins are one of the major challenges in hydrology. In the past, the approach using a physical-based conceptual model was the main approach, but recently, a solution using a data-driven model has been evaluated as mo...
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Zhenjiang Wu, Chuiyu Lu, Qingyan Sun, Wen Lu, Xin He, Tao Qin, Lingjia Yan and Chu Wu
In recent years, the groundwater level (GWL) and its dynamic changes in the Hebei Plain have gained increasing interest. The GWL serves as a crucial indicator of the health of groundwater resources, and accurately predicting the GWL is vital to prevent i...
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Li He, Shasha Ji, Kunlun Xin, Zewei Chen, Lei Chen, Jun Nan and Chenxi Song
Hydraulic monitoring data is critical for optimizing drainage system design and predicting system performance, particularly in the establishment of data-driven hydraulic models. However, anomalies in monitoring data, caused by sensor failures and network...
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Ahmad Abdul Chamid, Widowati and Retno Kusumaningrum
Product reviews on the marketplace are interesting to research. Aspect-based sentiment analysis (ABSA) can be used to find in-depth information from a review. In one review, there can be several aspects with a polarity of sentiment. Previous research has...
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Rubén E. Nogales and Marco E. Benalcázar
Gesture recognition is widely used to express emotions or to communicate with other people or machines. Hand gesture recognition is a problem of great interest to researchers because it is a high-dimensional pattern recognition problem. The high dimensio...
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Fatemeh Ghanaati, Gholamhossein Ekbatanifard and Kamrad Khoshhal Roudposhti
In recent years, next location prediction has been of paramount importance for a wide range of location-based social network (LBSN) services. The influence of geographical and temporal contextual information (GTCI) is crucial for analyzing individual beh...
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