Pages that link to "Item:Q2467421"
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The following pages link to Using genetic algorithms grey theory to forecast high technology industrial output (Q2467421):
Displaying 10 items.
- Error and its upper bound estimation between the solutions of GM(1,1) grey forecasting models (Q297636) (← links)
- The necessary and sufficient condition for GM(1, 1) grey prediction model (Q371532) (← links)
- A self-adaptive chaotic differential evolution algorithm using gamma distribution for unconstrained global optimization (Q470812) (← links)
- An optimized grey dynamic model for forecasting the output of high-tech industry in China (Q1718720) (← links)
- Forecasting the success of a new tourism service by a neuro-fuzzy technique (Q1754371) (← links)
- Time series interval forecast using GM(1,1) and NGBM(1,1) models (Q2001177) (← links)
- Grey-Markov prediction model based on background value optimization and central-point triangular whitenization weight function (Q2204814) (← links)
- A nonlinear grey forecasting model with double shape parameters and its application (Q2279463) (← links)
- Fractional-order accumulative linear time-varying parameters discrete grey forecasting model (Q2298645) (← links)
- Time series forecasting using a two-level multi-objective genetic algorithm: a case study of maintenance cost data for tunnel fans (Q2331650) (← links)
