{"id":197,"date":"2022-06-29T11:13:34","date_gmt":"2022-06-29T11:13:34","guid":{"rendered":"http:\/\/wastewatercare.com\/?page_id=197"},"modified":"2023-05-03T06:45:24","modified_gmt":"2023-05-03T06:45:24","slug":"our-solution","status":"publish","type":"page","link":"http:\/\/wastewatercare.com\/our-solution\/","title":{"rendered":"Our Solution"},"content":{"rendered":"<p>[vc_row][vc_column][vc_empty_space height=&#8221;50px&#8221;][\/vc_column][\/vc_row][vc_row][vc_column width=&#8221;1\/6&#8243;][\/vc_column][vc_column width=&#8221;2\/3&#8243;][vc_row_inner][vc_column_inner width=&#8221;2\/3&#8243;][vc_column_text]Promotes proactive approach to reduce failures, reduce costs, mitigate risk, increase confidence and optimize operation and expenditure in Waste Water Treatment Plant (WWTP).<\/p>\n<p>Using a variety of recurrent neural networks (RNNs) that are capable of learning long-term dependencies<\/p>\n<p>Can measure variables of treatment plant, environmental conditions, and use them to predict the amount of concentration of ammonia \ud835\udc41\ud835\udc3b4+ and nitrate \ud835\udc41\ud835\udc423\u2212 in effluent few hours ahead.<\/p>\n<p>By implanting preventive and proactive based on our prediction system, we offer reduced failures, reduced costs, mitigate risk, increase confidence and optimize operation and expenditure.[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/3&#8243;][vc_single_image image=&#8221;198&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221;][\/vc_column_inner][\/vc_row_inner][\/vc_column][vc_column width=&#8221;1\/6&#8243;][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space height=&#8221;50px&#8221;][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_empty_space height=&#8221;50px&#8221;][\/vc_column][\/vc_row][vc_row][vc_column width=&#8221;1\/6&#8243;][\/vc_column][vc_column width=&#8221;2\/3&#8243;][vc_row_inner][vc_column_inner width=&#8221;2\/3&#8243;][vc_column_text]Promotes proactive approach to reduce failures, reduce costs, mitigate risk, increase confidence and optimize operation and expenditure in Waste Water Treatment Plant (WWTP). Using a variety of recurrent neural networks (RNNs) that are capable of learning long-term dependencies Can measure variables of treatment plant, environmental conditions, and use them to predict [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-197","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/pages\/197","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/comments?post=197"}],"version-history":[{"count":3,"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/pages\/197\/revisions"}],"predecessor-version":[{"id":248,"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/pages\/197\/revisions\/248"}],"wp:attachment":[{"href":"http:\/\/wastewatercare.com\/wp-json\/wp\/v2\/media?parent=197"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}