Name
Abstract | ||
|---|---|---|
In this paper, Genetic Algorithms (GAs) are utilized in the investigation, design and development for modelling a given data time series. Genetic algorithms apply operations of reproduction, crossover and mutation to candidate solutions according to their relative fitness scores in the successive populations of candidates. The computer simulation results obtained demonstrate that GAs have the potential to become a powerful tool for time series modelling and forecasting |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/KES.1997.616918 | KES (1) |
Keywords | Field | DocType |
crossover,mutation,forecasting,forecasting theory,time series modelling,reproduction,genetic algorithms,modelling,time series,genetics,computer simulation,time measurement,organisms,genetic algorithm,predictive models,algorithm design and analysis | Crossover,Algorithm design,Computer science,Artificial intelligence,Time series modelling,Forecasting theory,Quality control and genetic algorithms,Genetic algorithm,Machine learning | Conference |
Volume | ISBN | Citations |
1 | 0-7803-3755-7 | 5 |
PageRank | References | Authors |
0.76 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chin Teck Chai | 1 | 5 | 1.77 |
| Chua Hong Chuek | 2 | 5 | 0.76 |
| D. P. Mital | 3 | 27 | 4.92 |
| Tan Thiam Huat | 4 | 5 | 0.76 |