An artificial neural network-based approach to optimizing energy efficiency in residential buildings in hot summer and cold winter regions

HIGHLIGHTS

• who: Cold Winter, Regions and Mingyue, Gao from the School of Art and Design, Shaanxi Fashion Engineering University, Xi`an, Shaanxi, China have published the research work: An Artificial Neural Network-Based Approach to Optimizing Energy Efficiency in Residential Buildings in Hot Summer and Cold Winter Regions, in the Journal: Computational Intelligence and Neuroscience 0.8 0.7 Error rate of 25/08/2022
• how: The neuron model with i input data is shown in Figure 2. This paper discusses the problems that the ANN is easy to fall into the local optimal solution optimizes . . .
  

   

  

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