The Application of Data Mining Technology to Big Data

Wang, Jinlong; Liu, Jing; Higgs, Rowan; Zhou, L.; Zhou, Chuanai

doi:10.1109/cse-euc.2017.238

Cited by 2 publications

(1 citation statement)

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“…This paper investigates the influence of atmospheric parameters on signal strength in MW frequency band using a data mining technique for a large quantity of data. However, although many researchers exist on data mining to process big data [7,10,11], the assessment of weather parameters changes and its effect on signal strength is normally not performed on data mining to process the data. The researchers showed that the change of atmospheric parameters is effective at the received signal VHF/UHF [9] whereas the weather parameters changes effect on the AM band requires more research.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the weight of weather parameters on MW signal strength by descriptive data mining

2020

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In this paper, weather parameters and electric field strength are measured in MW frequency band in Dashte_Ghazvin station. The experimental results were analyzed statistically as well as data mining techniques. Finally, the effects of weather parameters on signal strength were analyzed. In the far-field situations, the electric or magnetic field strength individually can be the representative of the electromagnetic wave radiation. In this paper, the electromagnetic radiation was assessed using measured electric field in terms of Volt per meter that changed from 8.50 to 3.32 V/m. The large amount of data provided the possibility of using data mining technique to find the exact relationship between the weather parameters and signal strength as well as the amount of their effects on signal strength. After the acquisition of data during 1 year, preprocessing of data was performed and weights were obtained through correlation. During a period of 1 year, 9,000,000 data was gathered in 2018 from January to December. The data includes the 5 weather parameters and signal strength. The results showed relationships between atmospheric parameters and the electric field strength. Additionally, the correlation analysis used to assess the relationship between each parameter and signal strength proved that the air humidity and air pressure have an inverted linear relationship with the signal level whereas the other variables have a direct linear relationship. The results are useful to design and develop the station before any construction.

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