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      New artificial network model to estimate biological activity of peat humic acids.

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          Abstract

          This article focuses on new method to estimate biological activity of peat humic acids (HAs) using artificial neural network (ANN) to process spectroscopic measurements in infrared and visible ranges. Conventional approaches generally rely on biological models and direct detection of chemical substances related to bioactivity. These methods proved to be accurate and reliable, but at the expense of speed and simplicity.

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          Author and article information

          Journal
          Environ Res
          Environmental research
          Elsevier BV
          1096-0953
          0013-9351
          Dec 2020
          : 191
          Affiliations
          [1 ] Siberian State Medical University, Tomsk, 634050, Russia. Electronic address: gmv2@rambler.ru.
          [2 ] National Research Tomsk Polytechnic University, Tomsk, 634050, Russia.
          [3 ] Siberian State Medical University, Tomsk, 634050, Russia; Institute of Monitoring of Climatic and Ecological Systems RAS, Russia.
          [4 ] Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk NRMC, Tomsk, 634050, Russia.
          [5 ] Siberian State Medical University, Tomsk, 634050, Russia.
          [6 ] Siberian State Medical University, Tomsk, 634050, Russia; National Research Tomsk Polytechnic University, Tomsk, 634050, Russia.
          Article
          S0013-9351(20)30896-3
          10.1016/j.envres.2020.109999
          32784018
          ba158ce1-9a0b-40af-988a-f96a1374b6e4
          History

          Network model,Peat,Visible and infrared spectroscopy,Macrophages,Humic acids,Biological activity

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