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Amna Al-Sayed, Mashael M. Khayyat and Nuha Zamzami
Different data types are frequently included in clinical data. Applying machine learning algorithms to mixed data can be difficult and impact the output accuracy and quality. This paper proposes a hybrid model of unsupervised and supervised learning tech...
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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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Zhongao Lu, Lijun Qi, Hao Zhang, Junjie Wan and Jiarui Zhou
Obtaining canopy area, crown width, position, and other information from UAV aerial images and adjusting spray parameters in real-time according to this information is an important way to achieve precise pesticide application in orchards. However, the na...
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Zari Farhadi, Hossein Bevrani, Mohammad-Reza Feizi-Derakhshi, Wonjoon Kim and Muhammad Fazal Ijaz
Nowadays, in the topics related to prediction, in addition to increasing the accuracy of existing algorithms, the reduction of computational time is a challenging issue that has attracted much attention. Since the existing methods may not have enough eff...
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Rencheng Liu, Saqib Ali, Syed Fakhar Bilal, Zareen Sakhawat, Azhar Imran, Abdullah Almuhaimeed, Abdulkareem Alzahrani and Guangmin Sun
Nowadays, customer churn has been reflected as one of the main concerns in the processes of the telecom sector, as it affects the revenue directly. Telecom companies are looking to design novel methods to identify the potential customer to churn. Hence, ...
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Xiao Chu, Xianghua Tan and Weili Zeng
Performing clustering analysis on a large amount of historical trajectory data can obtain information such as frequent flight patterns of aircraft and air traffic flow distribution, which can provide a reference for the revision of standard flight proced...
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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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Usman Sammani Sani, Owais Ahmed Malik and Daphne Teck Ching Lai
Wireless network parameters such as transmitting power, antenna height, and cell radius are determined based on predicted path loss. The prediction is carried out using empirical or deterministic models. Deterministic models provide accurate predictions ...
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Zhicheng Deng, Xiangting You, Zhaoyang Shi, Hong Gao, Xu Hu, Zhaoyuan Yu and Linwang Yuan
The study of urban functional zoning is not only important for analyzing urban spatial structure but also for optimizing urban management and promoting scientific urban planning. Different areas undertaking different urban functions correspond to differe...
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Qinggang Gao, Joseph Molloy and Kay W. Axhausen
We studied trip purpose imputation using data mining and machine learning techniques based on a dataset of GPS-based trajectories gathered in Switzerland. With a large number of labeled activities in eight categories, we explored location information usi...
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