Log in
Language:

MERAL Myanmar Education Research and Learning Portal

  • Top
  • Universities
  • Ranking
To
lat lon distance
To

Field does not validate



Index Link

Index Tree

Please input email address.

WEKO

One fine body…

WEKO

One fine body…

Item

{"_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": ["user-ucsy"]}, "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", "download_preview_message": "", "file_order": 0, "filename": "psc2010paper (39).pdf", "filesize": [{"value": "348 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 348000.0, "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"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003498", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-24"}, "publish_date": "2019-07-24", "publish_status": "0", "recid": "3498", "relation": {}, "relation_version_is_last": true, "title": ["Estimation of Oil Land Area by Using Bayes’ Theorem"], "weko_shared_id": -1}
  1. University of Computer Studies, Yangon
  2. Conferences

Estimation of Oil Land Area by Using Bayes’ Theorem

http://hdl.handle.net/20.500.12678/0000003498
http://hdl.handle.net/20.500.12678/0000003498
a1971d6e-885f-4f51-9b69-042369957c3d
6ce0dcea-456a-4103-82b5-d76c2dea083f
None
Preview
Name / File License Actions
psc2010paper psc2010paper (39).pdf (348 Kb)
Publication type
Article
Upload type
Publication
Title
Title Estimation of Oil Land Area by Using Bayes’ Theorem
Language en
Publication date 2010-12-16
Authors
Shwe, Myo Myat
Thein, Naychi Lai Lai
Description
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.
Keywords
decision support system, Bayes’ theorem, prior probabilities, posterior probabilities, decision tree
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1242
Journal articles
Fifth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
Back
0
0
views
downloads
See details
Views Downloads

Versions

Ver.1 2020-09-01 13:03:55.130537
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats
  • JSON

Confirm


Back to MERAL


Back to MERAL