Gaussian process regression for monitoring and fault detection of wastewater treatment processes - Samuelsson, Oscar; Björk, Anders; Zambrano, Jesús; Carlsson, Bengt (Water science and technology, 2017)
Keywords: Ammonium; Ammonium compounds; Artificial intelligence; Bayesian regression; Case studies; Computer simulation; Data; Detection; Electrical Engineering with specialization in Automatic Control; Elektroteknik med inriktning mot reglerteknik; energi- och miljöteknik; Energy- and Environmental Engineering; Environmental Monitoring - methods; Fault detection; Flow rates; Flow velocity; Gaussian process; Gaussian processes; Interpolation; kernel; Learning algorithms; Machine learning; Maximum likelihood estimation; Missing data; Monitoring; Monitoring methods; Monte Carlo Method; Monte Carlo simulation; Normal Distribution; Parameter estimation; Principal components analysis; process monitoring; Sensors; Signal processing; Statistical methods; Waste Disposal, Fluid - methods; Waste Disposal, Fluid - statistics & numerical data; Waste Water - statistics & numerical data; Wastewater; Wastewater treatment; Wastewater treatment plants; United States--US