Improving accuracy by combining rule-based and case-based reasoning
Artificial Intelligence
A Survey on Case-Based Planning
Artificial Intelligence Review
Fuzzy Logic: Misconceptions and Clarifications
Artificial Intelligence Review
Artificial Intelligence Review
Digital Image Similarity for Geo-spatial Knowledge Management
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Inductive Learning for Case-Based Diagnosis with Multiple Faults
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
An Automated Hybrid CBR System for Forecasting
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Search and Adaptation in a Fuzzy Object Oriented Case Base
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Defining Similarity Measures: Top-Down vs. Bottom-Up
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Case‐Based Reasoning: an overview
AI Communications
Using case-based reasoning to establish a continuing care information system of discharge planning
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Application of a hybrid intelligent decision support model in logistics outsourcing
Computers and Operations Research
A fuzzy CBR technique for generating product ideas
Expert Systems with Applications: An International Journal
A fuzzy case-based reasoning model for sales forecasting in print circuit board industries
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Integrating radial basis function networks with case-based reasoning for product design
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy Sets and Systems
Hybrid model for learner modelling and feedback prioritisation in exploratory learning
International Journal of Hybrid Intelligent Systems - CIMA-08
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Customized travel information recommendation framework using CBR and collective intelligence
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
A review of conventional and knowledge based systems for machining price quotation
Journal of Intelligent Manufacturing
An intelligent decision support system for IT outsourcing
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
An intelligent decision making system to support e-service management
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Expert Systems with Applications: An International Journal
Journal of Computational Methods in Sciences and Engineering
Hi-index | 12.06 |
Case-Based Reasoning (CBR), a well known Artificial Intelligence (AI) technique, has already proven its effectiveness in numerous industries. In this research, we try to adopt CBR technique in electroplating industry where the final products are electroplated accessory of watches. In order to ensure sufficient profit margin for electroplating manufacturer, it is important to grasp the coating weight of electroplating component accurately so that salespersons can make sure their quotation prices cover the precious metal cost. Apart from quotation accuracy, responsiveness is also a critical competitive edge in electroplating industry. In this connection, developing a quick response decision-making system with considerably reliable price is what electroplating industry needs. To cope with this problem, a hybrid CBR system combined with Rule-based Reasoning (RBR) and Fuzzy Logic (FL) concepts is established. Such system is capable to convert knowledge from experienced staff; simulate the 'mind-set' of decision maker in solving problem through acquisition of specific knowledge and experience; and build up self-learning characteristics. Moreover, this research interprets cases as some objective selection rules, putting CBR in a position much closer to RBR. This innovative concept differentiates from previous CBR researcher work, and will be explained through a practical example. Further, this research also suggested that it is very difficult and not practical to develop a pure CBR system. Applying some subjective guiding rules in CBR can significantly improve the performance of system in the early learning stage.