IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation
IEEE Transactions on Neural Networks
Using Chaotic Neural Network to Forecast Stock Index
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Computationally efficient FLANN-based intelligent stock price prediction system
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Maximum power point tracking (MPPT) system of small wind power generator using RBFNN approach
Expert Systems with Applications: An International Journal
An approach based on ANFIS input selection and modeling for supplier selection problem
Expert Systems with Applications: An International Journal
Information Systems Frontiers
| Hi-index | 12.05 |
This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the performance of three soft-computing models, namely multi-layer perceptrons (MLP), adaptive neuro-fuzzy inference systems (ANFIS) and general growing and pruning radial basis function (GGAP-RBF). It studies their computational time complexity; applies several benchmark matrices to compare their performance, such as generalize rate, recall rate, confusion matrices, and correlation to appreciation. This paper also suggests how equities can be picked systematically by using relative operating characteristics (ROC) curve.