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Andrea Adriani, Stefano Serra-Capizzano and Cristina Tablino-Possio
We consider the Helmholtz equation and the fractional Laplacian in the case of the complex-valued unbounded variable coefficient wave number μ" role="presentation" style="position: relative;">??µ
µ
, approximated by finite differences. In a rec...
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Masahito Kumagai, Kazuhiko Komatsu, Masayuki Sato and Hiroaki Kobayashi
Combinatorial clustering based on the Ising model is drawing attention as a high-quality clustering method. However, conventional Ising-based clustering methods using the Euclidean distance cannot handle irregular data. To overcome this problem, this pap...
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Xuhang Xu, Chunshan Liu, Jianghui Li, Yongchun Miao and Lou Zhao
Vessel trajectory prediction is an important step in route planning, which could help improve the efficiency of maritime transportation. In this article, a high-accuracy long-term trajectory prediction algorithm is proposed for oil tankers. The proposed ...
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Weinan Huang, Xiaowen Zhu, Haofeng Xia and Kejian Wu
In wind resource assessment research, mixture models are gaining importance due to the complex characteristics of wind data. The precision of parameter estimations for these models is paramount, as it directly affects the reliability of wind energy forec...
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Konstantinos Gratsos , Stefanos Ougiaroglou and Dionisis Margaris
Partition-based clustering is widely applied over diverse domains. Researchers and practitioners from various scientific disciplines engage with partition-based algorithms relying on specialized software or programming libraries. Addressing the need to b...
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Hengyu Hu, Zhengwei He, Yanfang Ling, Junmin Li, Lu Sun, Bo Li, Junliang Liu and Wuyang Chen
In this paper, a calibration algorithm for forecasting the significant wave height (SWH) in nearshore areas is proposed, based on artificial neural networks. The algorithm has two features: first, it is based on SOM-BRFnn (self-organizing map?radial basi...
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Baoyi Zhang, Zhengwen Jiang, Yiru Chen, Nanwei Cheng, Umair Khan and Jiqiu Deng
The spatial distribution of elements can be regarded as a numerical field of concentration values with a continuous spatial coverage. An active area of research is to discover geologically meaningful relationships among elements from their spatial distri...
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Fuat Kosanoglu
The predictability of wind energy is crucial due to the uncertain and intermittent features of wind energy. This study proposes wind speed forecasting models, which employ time series clustering approaches and deep learning methods. The deep learning (LS...
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Ali Seman and Azizian Mohd Sapawi
In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be obtai...
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Xia Que, Siyuan Jiang, Jiaoyun Yang and Ning An
Many mixed datasets with both numerical and categorical attributes have been collected in various fields, including medicine, biology, etc. Designing appropriate similarity measurements plays an important role in clustering these datasets. Many tradition...
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