Ranking-order case-based reasoning for financial distress prediction
Knowledge-Based Systems
MISMIS - A comprehensive decision support system for stock market investment
Knowledge-Based Systems
Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting
Knowledge-Based Systems
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Neural Networks
A general regression neural network
IEEE Transactions on Neural Networks
Multiple extreme learning machines for a two-class imbalance corporate life cycle prediction
Knowledge-Based Systems
A novel fruit fly optimization algorithm for the semiconductor final testing scheduling problem
Knowledge-Based Systems
Advances in Engineering Software
Hi-index | 0.01 |
The treatment of an optimization problem is a problem that is commonly researched and discussed by scholars from all kinds of fields. If the problem cannot be optimized in dealing with things, usually lots of human power and capital will be wasted, and in the worst case, it could lead to failure and wasted efforts. Therefore, in this article, a much simpler and more robust optimization algorithm compared with the complicated optimization method proposed by past scholars is proposed; the Fruit Fly Optimization Algorithm. In this article, throughout the process of finding the maximal value and minimal value of a function, the function of this algorithm is tested repeatedly, in the mean time, the population size and characteristic is also investigated. Moreover, the financial distress data of Taiwan's enterprise is further collected, and the fruit fly algorithm optimized General Regression Neural Network, General Regression Neural Network and Multiple Regression are adopted to construct a financial distress model. It is found in this article that the RMSE value of the Fruit Fly Optimization Algorithm optimized General Regression Neural Network model has a very good convergence, and the model also has a very good classification and prediction capability.