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Academic Publication Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models
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Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models
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AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings
Despite the tightening of energy performance standards for buildings in various countries and the increased use of efficient and renewable energy technologies, it is clear that the sector needs to ...
A novel heat load prediction model of district heating system based on hybrid whale optimization algorithm (WOA) and CNN-LSTM with attention mechanism
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Topology modeling and energy efficiency prediction of parallel chillers based on deep learning
To address the insufficient energy efficiency prediction accuracy caused by topological coupling in the parallel operation of multiple chillers, this study proposes a physics-guided spatiotemporal ...
Construction duration prediction for ultra-high-rise buildings using PCA and an improved sparrow-search–optimized BPNN
Construction duration prediction is crucial for the early-stage planning of ultra-high-rise building (UHRB) projects, but its accuracy is often limited by high-dimensional, strongly correlated, and...
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Yes, highly correlated activity was mapped. An entry titled 'Construction duration prediction for ultra-high-rise buildings using PCA and an improved sparrow-search–optimized BPNN' discusses this: Construction duration prediction is crucial for the early-stage planning of ultra-high-rise building (UHRB) projects, but its accuracy is often lim...
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