{"created":"2020-09-01T13:03:51.976813+00:00","id":3498,"links":{},"metadata":{"_buckets":{"deposit":"6ce0dcea-456a-4103-82b5-d76c2dea083f"},"_deposit":{"id":"3498","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3498"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3498","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Estimation of Oil Land Area by Using Bayes’ Theorem","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Petroleum exploration is a high risk business. Consulting geologists predicts the probable existence of oil based on the geological evidence such as reservoir rocks, source rocks, sealed rocks, trap, recovery factor and generation timing to obtain a better estimation of oil. To predict the probable existence of oil, it is very hard decisions because exploration of hydrocarbons is a high-risk venture and geological concepts are uncertain with respect to structure, reservoir seal, etc., . Bayes’ theorem is used to compute the prior probability to make the decision of drill the oil or sell the land upon the given user facts. This system also presents the method of computing posterior probabilities from prior probabilities using Bayes’ theorem to get decision tree. By using this system, people in petroleum-exploration field will get the knowledge of the essential factors for them."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"decision support system"},{"interim":"Bayes’ theorem"},{"interim":"prior probabilities"},{"interim":"posterior probabilities"},{"interim":"decision tree"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-24"}],"displaytype":"preview","filename":"psc2010paper (39).pdf","filesize":[{"value":"348 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3498/files/psc2010paper (39).pdf"},"version_id":"f37d1e93-8552-445a-9f3f-07d330c04dfe"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fifth  Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Shwe, Myo Myat"},{"subitem_authors_fullname":"Thein, Naychi Lai Lai"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2010-12-16"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1242"},"item_title":"Estimation of Oil Land Area by Using Bayes’ Theorem","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-24","publish_status":"0","recid":"3498","relation_version_is_last":true,"title":["Estimation of Oil Land Area by Using Bayes’ Theorem"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T06:11:56.851418+00:00"}