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Justin A. Schulte
In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters....
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Justin A. Schulte
In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters....
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Justin A. Schulte
In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters....
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Pingxin Wang, Qiang Liu, Gang Xu and Kangkang Wang
Three-way decision is a class of effective ways and heuristics commonly used in human problem solving and information processing. As an application of three-way decision in clustering, three-way clustering uses core region and fringe region to represent ...
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Ming-Chang Wu, Jing-Shan Hong, Ling-Feng Hsiao, Li-Huan Hsu and Chieh-Ju Wang
Typhoon rainfall is one of the most important water resources in Taiwan. However, heavy rainfall during typhoons often leads to serious disasters. Therefore, accurate typhoon rainfall forecasts are always desired for water resources managers and disaster...
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Huan Niu, Nasim Khozouie, Hamid Parvin, Hamid Alinejad-Rokny, Amin Beheshti and Mohammad Reza Mahmoudi
Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it seems c...
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Jonathan T. Barge and Hatim O. Sharif
This study focused on employing Linear Genetic Programming (LGP), Ensemble Empirical Mode Decomposition (EEMD), and the Self-Organizing Map (SOM) in modeling the rainfall?runoff relationship in a mid-size catchment. Models were assessed with regard to th...
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Jonathan T. Barge, Hatim O. Sharif
Pág. 1 - 20
This study focused on employing Linear Genetic Programming (LGP), Ensemble Empirical Mode Decomposition (EEMD), and the Self-Organizing Map (SOM) in modeling the rainfall?runoff relationship in a mid-size catchment. Models were assessed with regard to th...
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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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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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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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Khaled Fawagreh and Mohamed Medhat Gaber
To make healthcare available and easily accessible, the Internet of Things (IoT), which paved the way to the construction of smart cities, marked the birth of many smart applications in numerous areas, including healthcare. As a result, smart healthcare ...
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Loai Abdallah, Murad Badarna, Waleed Khalifa and Malik Yousef
In the computational biology community there are many biological cases that are considered as multi-one-class classification problems. Examples include the classification of multiple tumor types, protein fold recognition and the molecular classification ...
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Ke Ren, Dezhan Qu, Shaobin Xu, Xufeng Jiao, Liang Tai and Huijie Zhang
Uncertainty analysis of a time-varying ensemble vector field is a challenging topic in geoscience. Due to the complex data structure, the uncertainty of a time-varying ensemble vector field is hard to quantify and analyze. Measuring the differences betwe...
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Jaehyun Lee, Jinho Kim and Woong Ko
Electric load forecasting for buildings is important as it assists building managers or system operators to plan energy usage and strategize accordingly. Recent increases in the adoption of advanced metering infrastructure (AMI) have made building electr...
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Di Jin, Aristotelis Leventidis, Haoming Shen, Ruowang Zhang, Junyue Wu and Danai Koutra
Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researche...
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Yevgeniy Bodyanskiy, Iryna Perova, Polina Zhernova
Pág. 16 - 24
The subject matter of the article is fuzzy clustering of high-dimensional data based on the ensemble approach, provided that a number and shape of clusters are not known. The goal of the work is to create the neuro-fuzzy approach for clustering data when...
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