首页|Researchers from University of California Los Angeles (UCLA) Describe Findings I n Machine Learning (Machine Learning Models of Intermittent Operation of Ro Well head Water Treatment for Salinity Reduction and Nitrate Removal)
Researchers from University of California Los Angeles (UCLA) Describe Findings I n Machine Learning (Machine Learning Models of Intermittent Operation of Ro Well head Water Treatment for Salinity Reduction and Nitrate Removal)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. Accordingto news originating from Los Angeles, C alifornia, by NewsRx correspondents, research stated, “Machinelearning models w ere developed for intermittent multi-mode operation of a wellhead reverse osmosi swater purification and desalination system to predict salt passage, nitrate pa ssage, and permeate flux.The models, based on long short-term memory (LSTM) rec urrent neural network (RNN) architecture,included an attention mechanism to inc rease model performance in proximity of the regulatory limit fornitrate.”
Los AngelesCaliforniaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningUni versity of California Los Angeles (UCLA)
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