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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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Junzhuo Li, Wenyong Li and Guan Lian
A low-cost, timely, and durable long-term approach to resident travel surveys is crucial for authorities to understand the city?s transportation systems and formulate transportation planning and management policies. This paper summarizes commonly used wi...
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Fatma S. Alrayes, Jaber S. Alzahrani, Khalid A. Alissa, Abdullah Alharbi, Hussain Alshahrani, Mohamed Ahmed Elfaki, Ayman Yafoz, Abdullah Mohamed and Anwer Mustafa Hilal
Over the last few years, unmanned aerial vehicles (UAV), also called drones, have attracted considerable interest in the academic field and exploration in the research field of wireless sensor networks (WSN). Furthermore, the application of drones aided ...
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Nitin patidar,Kushboo patidar
The management and analysis of big data has been recognized as one of the majority significant promising requirements in recent years. This is because of the pure volume and growing complexity of data creature created or composed. Existing clustering alg...
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Xiangbing Zhou, Fang Miao and Hongjiang Ma
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Byungwan Jo and Zafar Baloch
In the present case study, the use of an advanced, efficient and low-cost technique for monitoring an urban stream was reported. Physicochemical parameters (PcPs) of Jungnangcheon stream (Seoul, South Korea) were assessed using an Internet of Things (IoT...
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Byungwan Jo, Zafar Baloch
Pág. 1 - 15
In the present case study, the use of an advanced, efficient and low-cost technique for monitoring an urban stream was reported. Physicochemical parameters (PcPs) of Jungnangcheon stream (Seoul, South Korea) were assessed using an Internet of Things (IoT...
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Ale? Krupka
Pág. 68 - 72
The paper deals with a definition of typicalstructure forms, which can be extracted from the surface of sedimentary grains. The co-occurrence features are used for this purpose. To find typical patterns, the K-means clustering technique is...
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Sergii Babichev, Lyudmyla Yasinska-Damri, Igor Liakh and Jirí ?kvor
The development of hybrid models focused on gene expression data processing for the allocation of differentially expressed and mutually correlated genes is one of the current directions in modern bioinformatics. The solution to this problem can allow us ...
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Tran Dinh Khang, Nguyen Duc Vuong, Manh-Kien Tran and Michael Fowler
Clustering is an unsupervised machine learning technique with many practical applications that has gathered extensive research interest. Aside from deterministic or probabilistic techniques, fuzzy C-means clustering (FCM) is also a common clustering tech...
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Libero Nigro and Franco Cicirelli
K-Means is a ?de facto? standard clustering algorithm due to its simplicity and efficiency. K-Means, though, strongly depends on the initialization of the centroids (seeding method) and often gets stuck in a local sub-optimal solution. K-Means, in fact, ...
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Laura Viola, Elisabetta Ronchieri and Claudia Cavallaro
Context?Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence and machine learning techniques to either log files or monit...
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Leonardo Rundo, Carmelo Militello, Giorgio Russo, Antonio Garufi, Salvatore Vitabile, Maria Carla Gilardi and Giancarlo Mauri
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Haviluddin Haviluddin,Yudi Sukmono,Didit Suprihanto,Arif Harjanto,Olivia Angelica Murtioso
Pág. 537 - 546
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Haviluddin Haviluddin,Yudi Sukmono,Didit Suprihanto,Arif Harjanto,Olivia Angelica Murtioso
Pág. 537 - 546
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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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Xiaofei Zhao, Caiyi Hu, Zhao Liu and Yangyang Meng
Many kinds of spatial?temporal data collected by transportation systems, such as user order systems or automated fare-collection (AFC) systems, can be discretized and converted into time-series data. With the technique of time-series data mining, certain...
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Nattakan Supajaidee, Nawinda Chutsagulprom and Sompop Moonchai
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)...
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Ramasubbareddy Somula, Yongyun Cho and Bhabendu Kumar Mohanta
In recent years, the Internet of Things (IoT) has transformed human life by improving quality of life and revolutionizing all business sectors. The sensor nodes in IoT are interconnected to ensure data transfer to the sink node over the network. Owing to...
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