An accurate and low-cost PM2.5 estimation method based on Artificial Neural Network.
Lixue XiaRong LuoBin ZhaoYu WangHuazhong YangPublished in: ASP-DAC (2015)
Keyphrases
- low cost
- high accuracy
- preprocessing
- highly accurate
- artificial neural networks
- significant improvement
- high precision
- experimental evaluation
- detection method
- highly efficient
- cost function
- probabilistic model
- parameter estimation
- multiscale
- model selection
- optimization algorithm
- detection algorithm
- computational cost
- dynamic programming
- pairwise
- image sequences
- estimation algorithm
- error analysis
- estimation accuracy