Expert systems: artificial intelligence in business
Expert systems: artificial intelligence in business
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Determining mental state from EEG signals using parallel implementations of neural networks
Scientific Programming - On applications analysis
Expert system applications in business: a review and analysis of the literature (1977–1993)
Information and Management
A hybrid intelligent architecture and revising domain knowledge
A hybrid intelligent architecture and revising domain knowledge
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Hybrid Neural Network and Expert Systems
Hybrid Neural Network and Expert Systems
Intelligent Systems for Finance and Business
Intelligent Systems for Finance and Business
Intelligent Hybrid Systems
Sensor Errors Prediction Using Neural Networks
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4 - Volume 4
Decision Support Systems - Special issue: Data mining for financial decision making
Advanced Engineering Informatics
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
A practical approach to credit scoring
Expert Systems with Applications: An International Journal
Hierarchical reinforcement learning with the MAXQ value function decomposition
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Integrating knowledge-based system and neural network techniques for robotic skill acquisition
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Expositing stages of VPRS analysis in an expert system: Application with bank credit ratings
Expert Systems with Applications: An International Journal
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hybrid mining approach in the design of credit scoring models
Expert Systems with Applications: An International Journal
Modelling sovereign credit ratings: Neural networks versus ordered probit
Expert Systems with Applications: An International Journal
Modelling credit rating by fuzzy adaptive network
Mathematical and Computer Modelling: An International Journal
Autonomous learning of sequential tasks: experiments and analyses
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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The main goal of all commercial banks is to collect the savings of legal and real persons and allocate them as credit to industrial, services and production companies. Non repayment of such credits cause many problems to the banks such as incapability to repay the central bank's loans, increasing the amount of credit allocations comparing to credit repayment and incapability to allocate more credits to customers. The importance of credit allocation in banking industry and it's important role in economic growth and employment creation leads the development of many models to evaluate the credit risk of applicants. But many of these models are classic and are incapable to do credit evaluation completely and efficiently. Therefore the demand to use artificial intelligence in this field has grown up. In this paper after providing appropriate credit ranking model and collecting expert's knowledge, we design a hybrid intelligent system for credit ranking using reasoning-transformational models. Expert system as symbolic module and artificial neural network as non-symbolic module are components of this hybrid system. Such models provide the unique features of each components, the reasoning and explanation of expert system and the generalization and adaptability of artificial neural networks. The results of this system demonstrate hybrid intelligence system is more accurate and powerful in credit ranking comparing to expert systems and traditional banking models.