Department of Information Technology, Indian Institute of Information Technology, Allahabad, Uttar Pradesh, India
As flexibility and agility become key success factors of competitive oil business industries, the ability to support the short-term decision and prediction making of oil exploration, scheduling, oil availability and yield prediction becomes a critical issue. This research paper presents a rule-based expert knowledge system, i.e. web-based hybrid expert system, called intelligent hybrid decision and prediction system (IHDPS) run on the cyber-enabled .NET Expert System Shell (NESS) technology platform to addresses how engineering knowledge can be dynamically represented and efficiently utilised in oil business industries. The rule-based knowledge system, called web-based IHDPS, is designed and implemented using the rule-based inference, reasoning and decision-making approach. The distinctive technical contributions of IHDPS focus on three critically integrated elements: (1) a spreadsheet software for interpreting and evaluating performance data, (2) a knowledge rule for time-series pattern recognition, and (3) an embedded application component.
Web-based hybrid expert system, Cyber-enabled.NET expert system shell (NESS), Intelligent hybrid decision, prediction system (IHDPS)
