A Monitoring Software Design for Aviation Airborne Computing Platform

Power load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating cost and improving social and economic benefits[1]. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for big data is constructed[2].

Publication Details

Journal
Journal of Electronics and Information Science
Published
2025-01-01
DOI
https://doi.org/10.23977/jeis.2025.100110
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

A Monitoring Software Design for Aviation Airborne Computing Platform

Journal of Electronics and Information Science
Air Traffic Management and Optimization
article

A Monitoring Software Design for Aviation Airborne Computing Platform

article en

Abstract

Power load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating cost and improving social and economic benefits[1]. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for big data is constructed[2].

Journal of Electronics and Information ScienceVol. 10(1)
Openalex Percentile: Top 92%
Air Traffic Management and Optimization
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A Monitoring Software Design for Aviation Airborne Computing Platform · Journal of Electronics and Information Science (2025) | TGRS Research Map | TGRS