Operational Reliability Evaluation Method Based on Big Data Technology

Big Data is a data evaluation method makes it possible for by recent breakthroughs in details and interactions modern technology. However, big data evaluation requires a massive quantity of calculating resources making fostering costs of big data technology is not inexpensive for lots of small to tool business. In this paper, we detail the benefits as well as obstacles associated with deploying big data analytics through cloud computing. We suggest that cloud computer can support the storage space as well as computing requirements of big data analytics. This paper provides a detailed overview of cloud computing and deployment of big data analytics in the cloud.

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Reliability Evaluation of Thermal Power Units Operation Based on Grey Fuzzy Theory

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.805-806.725 ◽

2013 ◽

Vol 805-806 ◽

pp. 725-729

Author(s):

Zi Xue Guo ◽

Nan Nan Liu ◽

Xin Lu

Keyword(s):

Evaluation Method ◽

Comprehensive Evaluation ◽

Fuzzy Theory ◽

Evaluation Model ◽

Thermal Power ◽

Fuzzy Comprehensive Evaluation ◽

Reliability Evaluation ◽

Operational Reliability ◽

Evaluation Index System ◽

Comprehensive Evaluation Method

The thermal power units operational reliability is the fundamental guarantee of smooth operation of electricity system. According to the problem of thermal power units operational reliability evaluation, a comprehensive evaluation method is put forward based on grey fuzzy theory. Firstly, this paper establishes an evaluation index system by the analysis of factors affecting the reliability of thermal power units. And then a reliability evaluation model of thermal power units operation is built based on grey fuzzy comprehensive evaluation which combined with the grey cluster theory and the fuzzy algorithm. At last, the numerical example is shown to verify the feasibility of the grey fuzzy comprehensive evaluation method.

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Research on Poverty Alleviation in China Based on Big Data in the Context of COVID-19

CONVERTER ◽

10.17762/converter.289 ◽

2021 ◽

pp. 270-281

Author(s):

Chenguang Zhang, Guifa Teng

Keyword(s):

Big Data ◽

Poverty Alleviation ◽

Evaluation Method ◽

Indicator System ◽

Recommendation Algorithm ◽

Performance Evaluation Method ◽

Calculation Ability ◽

The Impact ◽

Full Volume ◽

Big Data Technology

Objectives: In order to alleviate the impact of COVID-19 on China's poverty alleviation work, this paper proposesa performance evaluation method and a recommendation algorithm for poverty indicator system suitable forChina's national conditions based on big data technology. Methods: The evaluation method combines the preciseadvantages of Bayesian classifier and the full-volume processing characteristics of big data to comprehensivelyevaluate the past poverty alleviation achievements. The recommendation algorithm takes the poverty alleviationdata over the years as the research object and realizes the construction method of the indicator system in therelative poverty stage. Results: The comparison with Pearson's correlation coefficient shows that the newevaluation method has more accurate confidence calculation ability. And compared with the classic ALSrecommendation algorithm, the new recommendation algorithm has a more scientific and reasonablerecommendation effect. Conclusions: Finally, the paper proposes relevant suggestions for the next stage of policyformulation, proves that medical and health conditions play an important role in supporting poverty alleviation.

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A New Rockburst Experiment Data Compression Storage Algorithm based on Big Data Technology

Intelligent Automation & Soft Computing ◽

10.31209/2019.100000111 ◽

2019 ◽

pp. 561-573

Author(s):

Yu Zhang ◽

Yan-Ge Wang ◽

Yan-Ping Bai ◽

Yong-Zhen Li ◽

Zhao-Yong Lv ◽

...

Keyword(s):

Big Data ◽

Data Compression ◽

Experiment Data ◽

Big Data Technology

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Robust Test Method of TSOP PEMs for Space Application

ISTFA 2019: Conference Proceedings from the 45th International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa2019p0513 ◽

2019 ◽

Author(s):

Yasunobu Iwai ◽

Koichi Shinozaki ◽

Daiki Tanaka

Keyword(s):

Evaluation Method ◽

Low Cost ◽

Reliability Evaluation ◽

Test Method ◽

Thermal Shock Test ◽

Space Application ◽

Space Applications ◽

Limit Test ◽

Long Time ◽

Short Time

Abstract Compared with space parts, consumer parts are highly functional, low cost, compact and lightweight. Therefore, their increased usage in space applications is expected. Prior testing and evaluation on space applicability are necessary because consumer parts do not have quality guarantees for space application [1]. However, in the conventional reliability evaluation method, the test takes a long time, and the problem is that the robustness of the target sample can’t be evaluated in a short time. In this report, we apply to the latest TSOP PEM (Thin Small Outline Package Plastic Encapsulated Microcircuit) an evaluation method that combines preconditioning and HALT (Highly Accelerated Limit Test), which is a test method that causes failures in a short time under very severe environmental conditions. We show that this method can evaluate the robustness of TSOP PEMs including solder connections in a short time. In addition, the validity of this evaluation method for TSOP PEM is shown by comparing with the evaluation results of thermal shock test and life test, which are conventional reliability evaluation methods.

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Using Big Data Technology For Prediction Of Quiz Difficulty Level In E-learning Systems

10.34279/0923-008-004-014 ◽

2018 ◽

pp. 176

Author(s):

Hiba A. Abu Alsaad ◽

Rana Riad K. Al Taie

Keyword(s):

Big Data ◽

Learning Systems ◽

Difficulty Level ◽

E Learning ◽

Big Data Technology

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Validity of the “Big Data Tendency in Education” Scale as a Tool Helping to Reach Inclusive Social Development

Sustainability ◽

10.3390/su12135470 ◽

2020 ◽

Vol 12 (13) ◽

pp. 5470 ◽

Cited By ~ 2

Author(s):

Antonio Matas-Terrón ◽

Juan José Leiva-Olivencia ◽

Pablo Daniel Franco-Caballero ◽

Francisco José García-Aguilera

Keyword(s):

Big Data ◽

Inclusive Education ◽

Sustainable Development Goals ◽

Sustainable Society ◽

Education Students ◽

The Sustainable Development ◽

Research Goal ◽

Development Goals ◽

Nonprobability Sample ◽

Big Data Technology

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.

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