scholarly journals Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 530
Author(s):  
Haitao Ding ◽  
Chu Sun ◽  
Jianqiu Zeng
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Information Fusion ◽  
Data Clustering ◽  
Linear Regression Analysis ◽  
Numerical Attributes ◽  
Weighted Clustering ◽  
Feature Fitting ◽  
Feature Information ◽  
Clustering Center

It is necessary to optimize clustering processing of communication big data numerical attribute feature information in order to improve the ability of numerical attribute mining of communication big data, and thus a big data clustering algorithm based on cloud computing was proposed. The cloud extended distributed feature fitting method was used to process the numerical attribute linear programming of communication big data, and the mutual information feature quantity of communication big data numerical attribute was extracted. Combined with fuzzy C-means clustering and linear regression analysis, the statistical analysis of big data numerical attribute feature information was carried out, and the associated attribute sample set of communication big data numerical attribute cloud grid distribution was constructed. Cloud computing and adaptive quantitative recurrent classifiers were used for data classification, and block template matching and multi-sensor information fusion were combined to search the clustering center automatically to improve the convergence of clustering. The simulation results show that, after the application of this method, the information fusion performance of the clustering process was better, the automatic searching ability of the data clustering center was stronger, the frequency domain equalization control effect was good, the bit error rate was low, the energy consumption was small, and the ability of fuzzy weighted clustering retrieval of numerical attributes of communication big data was effectively improved.

scholarly journals Model design for big data clustering analysis of power dispatch automation system based on cloud computing platform

2020 ◽  
Vol 179 ◽  
pp. 01028
Author(s):  
Yu Xiangqian ◽  
Wang Linxin ◽  
Chen Jianhua ◽  
Su Haijun ◽  
Liu Xiaokun
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Clustering Analysis ◽  
Data Clustering ◽  
Automation System ◽  
Model Design ◽  
Technical Tool ◽  
Computing Platform ◽  
Power Dispatch ◽  
Cloud Computing Platform

Cloud computing and big data are closely linked, profoundly affecting the way people live and work. They also have more established applications in power dispatch automation. This paper uses cloud computing as a technical tool to analyze the power dispatch automation system, and discusses the application aspects based on the model construction.

scholarly journals Modified Immune Evolutionary Algorithm for Medical Data Clustering and Feature Extraction under Cloud Computing Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jing Yu ◽  
Hang Li ◽  
Desheng Liu
Keyword(s):  
Cloud Computing ◽  
Feature Extraction ◽  
Big Data ◽  
Data Clustering ◽  
Clustering Algorithm ◽  
Fitness Function ◽  
Medical Data ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Evolutionary Method

Medical data have the characteristics of particularity and complexity. Big data clustering plays a significant role in the area of medicine. The traditional clustering algorithms are easily falling into local extreme value. It will generate clustering deviation, and the clustering effect is poor. Therefore, we propose a new medical big data clustering algorithm based on the modified immune evolutionary method under cloud computing environment to overcome the above disadvantages in this paper. Firstly, we analyze the big data structure model under cloud computing environment. Secondly, we give the detailed modified immune evolutionary method to cluster medical data including encoding, constructing fitness function, and selecting genetic operators. Finally, the experiments show that this new approach can improve the accuracy of data classification, reduce the error rate, and improve the performance of data mining and feature extraction for medical data clustering.

Challenges and Cloud Computing Environments Towards Big Data

2014 ◽  
pp. 203-208
Author(s):  
Kiran Kumar S V N Madupu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Technology Development ◽  
Computing Environments ◽  
Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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