An assessment of stingless beehive climate impact using multivariate recurrent neural networks.

• Main Authors: Khairul Anuar, Noor Hafizah, Md. Yunus, Mohd. Amri, Baharudin, Muhammad Ariff, Ibrahim, Sallehuddin, Sahlan, Shafishuhaza, Faramarzi, Mahdi
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science (IAES) 2023
• Subjects: TK Electrical engineering. Electronics Nuclear engineering; TK6570 Mobile Communication System
• Online Access: http://eprints.utm.my/105604/1/NoorHafizahKhairulAnuar2023_AnAssessmentofStinglessBeehiveClimateImpact.pdf; http://eprints.utm.my/105604/; http://dx.doi.org/10.11591/ijece.v13i2.pp2030-2039
• Institution: Universiti Teknologi Malaysia

A healthy bee colony depends on various elements, including a stable habitat, a sufficient source of food, and favorable weather. This paper aims to assess the stingless beehive climate data and examine the precise short-term forecast model for hive weight output. The dataset was extracted from a si...