Municipal credit rating modelling by neural networks
نویسنده
چکیده
منابع مشابه
Modelling Municipal Rating by Cluster Analysis and Neural Networks
The paper presents the design of the parameters for long-term municipal rating. Modelling of the rating is realized by means of unsupervised methods, because the rating classes are not known a priori. The model design based on statistical methods (neural networks) is represented by cluster analysis (self-organizing feature maps). Key-Words: Credit risk, rating, unsupervised learning, cluster an...
متن کاملDesigning an Expert System for Credit Rating of Real Customers of Banks Using Fuzzy Neural Networks
Currently, in Iran's banking system, non-repayment of facilities has become one of the biggest issues, and due to the lack of a proper system for proper allocation of facilities, they face a number of problems, including the problem of allocation of loans, the problem of failure to repay loans Of the central bank, or the amount of facilities increased from the amount of reimbursement. The solut...
متن کاملSemantic Extraction Using Neural Network Modelling and Sensitivity Analysis
Neural networks have often been faulted as black box systems that do not explain clearly the way it arrives at its conclusions. In this paper, we present three methods of using neural network modelling and sensitivity analysis to extract semantics from the historical data of a given system. First, neural network modelling and sensitivity analysis is used to determine the decision boundaries of ...
متن کاملModelling credit rating by fuzzy adaptive network
Human judgment plays an important role in the rating of enterprise financial conditions. The recently developed fuzzy adaptive network (FAN), which can handle systems whose behaviour is influenced by human judgment, appears to be ideally suited for the modelling of this credit rating problem. In this paper, FAN is used to model the credit rating of small financial enterprises. To illustrate the...
متن کاملFuzzy Adaptive Networks in credit rating and loan approval
Fuzzy adaptive network (FAN) is proposed to help decision makers in credit scores and to assign the amount of loan. By combining with neural networks to incorporate the learning ability, FAN provides an alternative approach for the imprecision and fuzziness of the credit rating system. A loan approval example is given and the performance of FAN is compared with the regression algorithm. The res...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Decision Support Systems
دوره 51 شماره
صفحات -
تاریخ انتشار 2011