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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Frank Klawonn and Georg Hoffmann
Clustering algorithms are usually iterative procedures. In particular, when the clustering algorithm aims to optimise an objective function like in k-means clustering or Gaussian mixture models, iterative heuristics are required due to the high non-linea...
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Chao He, Xinghua Zhang, Dongqing Song, Yingshan Shen, Chengjie Mao, Huosheng Wen, Dingju Zhu and Lihua Cai
With the popularization of better network access and the penetration of personal smartphones in today?s world, the explosion of multi-modal data, particularly opinionated video messages, has created urgent demands and immense opportunities for Multi-Moda...
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Yonghai He, Songtao Lv, Nasi Xie, Huilin Meng, Wei Lei, Changyu Pu, Huabao Ma, Ziyang Wang, Guozhi Zheng and Xinghai Peng
This study addressed the complex problems of selecting a constitutive model to objectively characterize asphalt mixtures and accurately determine their viscoelastic properties, which are influenced by numerous variables. Inaccuracies in model or paramete...
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Huiru Zhou, Qiang Lai, Qiong Huang, Dingzhou Cai, Dong Huang and Boming Wu
The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen i...
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Luca Scrucca
Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class significantly outnumber those of the other. This paper examines the impact of class imbalance on the perfo...
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Massimo Pacella, Matteo Mangini and Gabriele Papadia
Considering the issue of energy consumption reduction in industrial plants, we investigated a clustering method for mining the time-series data related to energy consumption. The industrial case study considered in our work is one of the most energy-inte...
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Christos Karras, Aristeidis Karras, Konstantinos C. Giotopoulos, Markos Avlonitis and Spyros Sioutas
In the context of big-data analysis, the clustering technique holds significant importance for the effective categorization and organization of extensive datasets. However, pinpointing the ideal number of clusters and handling high-dimensional data can b...
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Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
This paper provides new models of the attention-based random forests called LARF (leaf attention-based random forest). The first idea behind the models is to introduce a two-level attention, where one of the levels is the ?leaf? attention, and the attent...
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