A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China.

ABSTRACT: A challenge of achieving intelligent marine ranching is the prediction of dissolved oxygen (DO). DO directly reflects marine ranching environmental conditions. Through accurate DO predictions, timely human intervention can be made in marine pasture water environments to avoid problems such as reduced yields or marine crop death due to low oxygen concentrations in the water. We use an enhanced semi-naive Bayes model for prediction based on an analysis of DO data from marine pastures in northeastern China from the past three years. Based on the semi-naive Bayes model, this paper takes the possible values of a DO difference series as categories, counts the possible values of the first-order difference series and the difference series of the interval before each possible value, and selects the

SUBMITTER: Sun J 

PROVIDER: S-EPMC8205303 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature