Two important applications of rainfall-runoff models are forecasting and simulation. At present, rainfall-runoff models based on artificial intelligence methods are built basically for short-term forecasting purposes and these models are not very effective for simulation purposes. This study explores the applicability and effectiveness of adaptive neuro-fuzzy-system-based rainfall-runoff models...

in the regulated nakdong river, algal proliferations are annually observed in some seasons, with cyanobacteria (microcystis aeruginosa) appearing in summer and diatom blooms (stephanodiscus hantzschii) in winter. this study aims to develop two ecological models forecasting future chlorophyll a at two time-steps (one-week and one-year forecasts), using recurrent neural networks tuned by genetic...

Solar energy is expected to contribute major shares of the future global energy supply. Due to its fluctuating nature an efficient use will require reliable forecast information of its availability in various time and spatial scales depending on the application. The current status of forecasting solar irradiance for energy generation purposes is briefly reviewed with respect to very short-term ...

Solar energy is expected to contribute major shares of the future global energy supply. Due to its fluctuating nature an efficient use will require reliable forecast information of its availability in various time and spatial scales depending on the application. The current status of forecasting solar irradiance for energy generation purposes is briefly reviewed with respect to very short-term ...

We present a case study of the development of an adaptive forecasting system for a leading personal computer (PC) manufacturer in South Korea. It is widely accepted that demand forecasting for products with short product life cycles (PLCs) is difficult, and the PLC of a PC is generally very short. The firm has various types of products, and the volatile demand patterns differ by product. Moreov...

This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population.Themethod constitutes an expansion of the hybridGenetic Programming (hGP)method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and L...

This paper aims models electricity load curves for short-term forecasting purposes. A broad class of multivariate dynamic regression model is proposed to model hourly electricity load. Alternative forecasting models, special cases of our general model, include separate time series regressions for each hour and week day. All the models developed include components that represent trends, seasons ...