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- Title
機械学習による養豚汚水処理施設の性能向上に向けて ─決定木解析による個別施設の硝酸性 窒素等除去特性把握の試み─.
- Authors
田中康男
- Abstract
In Japan, sum total value of NO2 --N concentration, NO3 --N concentration, and 0.4 times of NH4 +-N concentration in effluent of wastewater treatment plant is regulated by Water Pollution Control Low. Though complying the standard value is important task of swine farms, control of the concentration is generally difficult for farmers. This study attempted to obtain prediction models of “NH4 +-N×0.4+NO2 --N +NO3 --N” fluctuation by machine learning method in two swine wastewater treatment plants. Decision tree model which is one of the methods of machine learning were employed to describe a correlation between operational conditions (aeration tank water temperature, pH, and MLSS as inputs) and the concentration as an output, using data collected over about 3 years. Plant operation guidelines were provided by the decision tree models.
- Publication
Japanese Journal of Swine Science / Nihon Yoton Gakkaishi, 2021, Vol 58, Issue 2, p65
- ISSN
0913-882X
- Publication type
Article