{"id":5183,"date":"2015-04-14T13:11:32","date_gmt":"2015-04-14T13:11:32","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=5183"},"modified":"2015-04-14T13:12:03","modified_gmt":"2015-04-14T13:12:03","slug":"predictive-analytics-ensures-ships-stay-in-shipshape-for-cargo-company-041415","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/predictive-analytics-ensures-ships-stay-in-shipshape-for-cargo-company-041415\/5183\/","title":{"rendered":"Predictive Analytics Ensures Ships Stay in Shipshape for Cargo Company"},"content":{"rendered":"RightShip can predict the likelihood of a vessel causing an incident while at sea Melbourne-based cargo company, RightShip, is turning to predictive analytics to more accurately assess if ships are ready to be sent out to sea. RightShip vets vessels for oil, coal and other natural resources companies, having vetted 3 billion tonnes of cargo in 2014. More than 90 per cent of the world&#8217;s trade is shipped through the seas. The cost of oil spills, operational and regulatory issues, as well as numerous other problems at sea, can greatly impact a company&#8217;s bottom line and the environment. <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/predictive-analytics-ensures-ships-stay-in-shipshape-for-cargo-company-041415\/5183\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>RightShip can predict the likelihood of a vessel causing an incident while at sea Melbourne-based cargo company, RightShip, is turning to predictive analytics to more accurately assess if ships are ready to be sent out to sea. RightShip vets vessels for oil, coal and other natural resources companies, having vetted 3 billion tonnes of cargo [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[],"class_list":["post-5183","post","type-post","status-publish","format-standard","hentry","category-industry-news"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5183","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=5183"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5183\/revisions"}],"predecessor-version":[{"id":5185,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5183\/revisions\/5185"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=5183"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=5183"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=5183"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}