Learning adaptation knowledge to improve case-based reasoning
Artificial Intelligence
Protocols for RFID tag/reader authentication
Decision Support Systems
Expert Systems with Applications: An International Journal
Inventory Record Inaccuracy: An Empirical Analysis
Management Science
Integrating RFID with quality assurance system - Framework and applications
Expert Systems with Applications: An International Journal
DSS for computer security incident response applying CBR and collaborative response
Expert Systems with Applications: An International Journal
Design of a RFID case-based resource management system for warehouse operations
Expert Systems with Applications: An International Journal
Evaluation of sensor readability and thermal relevance for RFID temperature tracking
Computers and Electronics in Agriculture
Introducing attribute risk for retrieval in case-based reasoning
Knowledge-Based Systems
Principal component case-based reasoning ensemble for business failure prediction
Information and Management
A real-time food safety management system for receiving operations in distribution centers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Due to the fact that wine is highly sensitive to storage conditions such as temperature and humidity, it is a challenging task for a regional distribution hub to provide reliable wine storage facilities for maintaining wine quality during storage. This is especially true when an incident occurs unexpectedly that violates the criteria of suitable storage conditions. Improper incident handling and storage conditions may cause damage to the taste of wine, resulting in depreciation of the wine's value. Therefore, controlling and monitoring risk in real-time during wine storage is critical to providing a quick response to prevent the wine quality from deterioration. In this paper, a RFID-based risk control and monitoring system (RCMS), which integrates radio frequency identification (RFID) technology and case-based reasoning (CBR), is proposed for monitoring real-time physical storage conditions and for formulating an immediate action plan for handling incidents. In the retrieval process of the CBR engine, genetic algorithms (GA) are applied to search for case clusters by considering the best combination of multi-dimensional parameters. With the help of RCMS, a shortlist of critical control actions, possible causes of incidents and corresponding actions can be generated to reduce the risk of deteriorating wine quality and possible compensation costs being incurred, while customer satisfaction can be maintained.