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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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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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Nilupulee Nathawitharana,Damminda Alahakoon,Sumith Matharage
Humans are used to expressing themselves with written language and language provides a medium with which we can describe our experiences in detail incorporating individuality. Even though documents provide a rich source of information, it becomes very di...
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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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Natalya Y Shelkova
Pág. 16
Wage distributions in economies with mandated minimum wage exhibit both wage dispersion and wage clustering known as the minimum wage spike. The paper builds a search-theoretic model that reconciles the two phenomena simultaneously under the assumptions ...
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Xuhua Xia
A self-organizing map (SOM) is an artificial neural network algorithm that can learn from the training data consisting of objects expressed as vectors and perform non-hierarchical clustering to represent input vectors into discretized clusters, with vect...
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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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Tran Dinh Khang, Manh-Kien Tran and Michael Fowler
Clustering is an unsupervised machine learning method with many practical applications that has gathered extensive research interest. It is a technique of dividing data elements into clusters such that elements in the same cluster are similar. Clustering...
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Peide Liu, Muhammad Munir, Tahir Mahmood and Kifayat Ullah
Similarity measures, distance measures and entropy measures are some common tools considered to be applied to some interesting real-life phenomena including pattern recognition, decision making, medical diagnosis and clustering. Further, interval-valued ...
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Pei-Yin Chen and Jih-Jeng Huang
Image clustering involves the process of mapping an archive image into a cluster such that the set of clusters has the same information. It is an important field of machine learning and computer vision. While traditional clustering methods, such as k-mea...
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Ashkan Zarnani, Soheila Karimi and Petr Musilek
Information about forecast uncertainty is vital for optimal decision making in many domains that use weather forecasts. However, it is not available in the immediate output of deterministic numerical weather prediction systems. In this paper, we investig...
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Paulene Govender, Michael J. Brooks, Alan P. Matthews
Clustering of solar irradiance patterns was used in conjunction with cloud cover forecasts from Numerical Weather Predictions for day-ahead forecasting of irradiance. Beam irradiance as a function of time during daylight was recorded over a one-year peri...
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Anwar Said, Syed Waqas Haider Shah, Hasan Farooq, Adnan Noor Mian, Ali Imran and Jon Crowcroft
Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive ca...
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Anwar Said, Syed Waqas Haider Shah, Hasan Farooq, Adnan Noor Mian, Ali Imran and Jon Crowcroft
Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive ca...
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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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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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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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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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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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Yunseong Lee, Chanhong Park, Taeyoung Kim, Yeongyoon Choi, Kiseon Kim, Dongho Kim, Myung-Sik Lee and Dongkeun Lee
Source enumeration is an important procedure for radio direction-of-arrival finding in the multiple signal classification (MUSIC) algorithm. The most widely used source enumeration approaches are based on the eigenvalues themselves of the covariance matr...
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