BIG DATA APPLICATION IN THE NEYMAN-PEARSON REGRESSION AND DEEP BERNOULLI AND BOLTZMANN FOR IOT BASED SOIL QUALITY PREDICTION

BIG DATA APPLICATION IN THE NEYMAN-PEARSON REGRESSION AND DEEP BERNOULLI AND BOLTZMANN FOR IOT BASED SOIL QUALITY PREDICTION

Purpose. The aim of the work is to enhance the soil quality prediction accuracy and time by using feature selection and classification-based model. Background. Soil quality analysis was handled based on the farmer’s first-hand data mining competence and with the world population expected to increa...

Full description

Bibliographic Details
Main Authors: G. Balaji, P. Vijayakumar
Format: Article
Language:English
Published: Science and Innovation Center Publishing House 2022-02-01
Series:Siberian Journal of Life Sciences and Agriculture
Subjects:
big data
internet of things
linear regression
neyman-pearson correlation
feature selection
deep bernoulli
boltzmann soil quality prediction
Online Access:http://discover-journal.ru/jour/index.php/sjlsa/article/view/428

Internet

http://discover-journal.ru/jour/index.php/sjlsa/article/view/428

Similar Items