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primary topic: Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis

Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis
type: AcademicArticle
type: Article
date: 2025
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
has document: Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis (Text)
has document: Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis (Other)
subject: TK Electrical engineering. Electronics Nuclear engineering

Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis (Text)
type: Document
has file: 13482_ijasst+IKA+2025+full.pdf
has part: 13482_ijasst+IKA+2025+full.pdf

International Journal of Applied Sciences and Smart Technologies
type: Collection

Ika Arva Arshella
type: Person
given name: Ika Arva
family name: Arshella

Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis (Other)
type: Document
is version of: Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis (Text)
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primary topic: Improving the Accuracy of Prediction of Dissolved Oxygen and Nitrate Level Using LSTM with K-Means Clustering and Spearman Analysis

TK Electrical engineering. Electronics Nuclear engineering
type: Concept