Compare metadata collection and organization in wastewater treatment ... - 9781789061147 products from over 5,000 stores
Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147
Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147
Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147
Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147
Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147

Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147

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Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery SystemsAuthor(s): Kris Villez, Daniel G. Aguado, Janelcy Alferes, Maria Victoria Ruano, Oscar Samuelsson, Queralt Plana\nFormat: Paperback\nPublisher: IWA Publishing, United Kingdom\nImprint: IWA Publishing\nISBN-13: 9781789061147, 978-1789061147\nSynopsis\nThis Scientific Technical Report demonstrates meta-data strategies for water resource recovery facilities (WRRF), including the essential data validation with machine learning and traditional methods. The report is the result of extensive work from many water data experts and a utility focus group, with the dedicated application of WRRF data.\nEmerging trends in artificial intelligence and machine learning project unforeseen possibilities in managing our WRRFs. Hope is built upon the large data volumes collected with high frequency from both existing sensors, as well as new uncoordinated data sources outside the fence. The data variety ho.

Metadata Collection and Organization in Wastewater Treatment ... - 9781789061147

Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery SystemsAuthor(s): Kris Villez, Daniel G. Aguado, Janelcy Alferes, Maria Victoria Ruano, Oscar Samuelsson, Queralt Plana\nFormat: Paperback\nPublisher: IWA Publishing, United Kingdom\nImprint: IWA Publishing\nISBN-13: 9781789061147, 978-1789061147\nSynopsis\nThis Scientific Technical Report demonstrates meta-data strategies for water resource recovery facilities (WRRF), including the essential data validation with machine learning and traditional methods. The report is the result of extensive work from many water data experts and a utility focus group, with the dedicated application of WRRF data.\nEmerging trends in artificial intelligence and machine learning project unforeseen possibilities in managing our WRRFs. Hope is built upon the large data volumes collected with high frequency from both existing sensors, as well as new uncoordinated data sources outside the fence. The data variety ho.

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