Comparison of Hybrid ACO-k-means algorithm and Grub cut for MRI images segmentation

El-Khatib, Samer; Skobtsov, Y.A.; Rodzin, Sergey

doi:10.1016/j.procs.2021.04.150

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…e essence of cluster analysis is to find out the classification basis of data according to the research topic, classify and process the data according to this basis, refine the data into different types of data sets, and ensure that the data in each set has similarity, and there are differences between different sets and then use the data visualization technology to show it to users friendly, which is called cluster analysis [14].…”

Section: Cluster Analysismentioning

confidence: 99%

Application of Data Mining in Network Information Dynamic Push Software

Hong¹

2022

Security and Communication Networks

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In order to solve the problem that it is difficult for each user to obtain the most needed information due to different backgrounds, a method of data mining network information is proposed. The main steps of this method are as follows: (1) designing data mining rules based on association rules; (2) screening candidate sets of network information data mining; (3) candidate set information data mining. The experimental results show that the p value of this method is more than 90.0% and that of the traditional method is only within the range of 30.0%∼70.0%. Obviously, the p value of this method is 20.0%∼60.0% higher than that of the traditional method. This method can effectively solve the problem that it is difficult for each user to obtain the most needed information due to background differences.

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Section: Cluster Analysismentioning

confidence: 99%

Application of Data Mining in Network Information Dynamic Push Software

Hong¹

2022

Security and Communication Networks

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“…e key problem of anomaly detection lies in the establishment of normal usage profiles and how to use this pattern to compare and judge the current user behavior [3]. El-Khatib et al stated that a behavioral pattern refers to a certain regularity in the process of program execution or user operation [4]. Wu et al believe that a lot of practical experience tells us, whether it is the execution of the program or the behavior of the user; there is a close correlation in the system characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Computer User Behavior Anomaly Detection Based on K-Means Algorithm

Yang

Hao

Zhao

et al. 2022

Security and Communication Networks

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As an effective network protection method, computer user behavior anomaly detection can detect unknown attack behaviors. In order to detect user behavior anomalies more efficiently, the authors propose a computer user behavior anomaly detection model based on the K-means algorithm. According to the actual characteristics of single-user behavior, the algorithm uses sliding time window to define transactions and uses the first location strategy to mine behavior patterns. On this basis, the fault-tolerant mode is adopted to compare the current behavior mode with the normal behavior mode, and the anomaly detection results are obtained. Experiments show that using data mining technology, the association rules of user commands, and the mining of sequence patterns, it can effectively discover the user’s behavior pattern, and using sequence matching algorithms such as recursive correlation functions and calculating the similarity between the user’s historical pattern and the current pattern, it provides the possibility to accurately judge user behavior. The following conclusions are obtained through experiments: the model training time is short, the accuracy is high, and it has certain robustness.

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“…It does not rely on the prior confirmation of data categories. Therefore, cluster analysis is another method of learning through observation [3,4].…”

Section: Introductionmentioning

confidence: 99%

Data Optimization Analysis of Integrated Energy System Based on $K$ -Means Algorithm

Guo¹,

Li²,

Sun³

et al. 2022

Wireless Communications and Mobile Computing

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To learn about the practical application of K -environment algorithms in electronic data analysis. To increase the thermal efficiency of boiler combustion and reduce nitrogen oxide emissions, the paper uses a 300 MW circulating liquid bed boiler for a thermal power plant as a research product. The studied and improved optimization methods have been successfully used to optimize the combustion of circulating liquefied boilers. Based on the advantages and disadvantages of biogeographic optimization algorithm and K -means clustering algorithm, this paper combines the two algorithms into a new improved clustering algorithm k -bbo-cluster. According to the operation mode of circulating fluidized bed boiler, the calculation method of boiler combustion thermal efficiency and the generation mechanism of nitrogen oxides, the boiler thermal efficiency model, nitrogen oxide emission concentration model and its comprehensive model are established by using the least square support vector machine method based on Bayesian structure framework. The learning outcomes of the vector machines that support the minimum squares of the Bayesian structure are less than 0.05 by the difference between MSE, MAE, and MAPE. The study of optimizing the combustion of circulating liquefied bed furnaces in this article can effectively improve the thermal efficiency of circulating liquefied bed furnaces and reduce nitrogen oxide emissions. Protection is important.

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Comparison of Hybrid ACO-k-means algorithm and Grub cut for MRI images segmentation

Cited by 9 publications

References 4 publications

Application of Data Mining in Network Information Dynamic Push Software

Application of Data Mining in Network Information Dynamic Push Software

Computer User Behavior Anomaly Detection Based on K-Means Algorithm

Data Optimization Analysis of Integrated Energy System Based on $K$ -Means Algorithm

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Comparison of Hybrid ACO-k-means algorithm and Grub cut for MRI images segmentation

Cited by 9 publications

References 4 publications

Application of Data Mining in Network Information Dynamic Push Software

Application of Data Mining in Network Information Dynamic Push Software

Computer User Behavior Anomaly Detection Based on K-Means Algorithm

Data Optimization Analysis of Integrated Energy System Based on K -Means Algorithm

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Product

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Data Optimization Analysis of Integrated Energy System Based on $K$ -Means Algorithm