Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor
Using WGENK to generate synthetic daily weather data for modelling of agricultural processes
β Scribed by Leszek Kuchar
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 226 KB
- Volume
- 65
- Category
- Article
- ISSN
- 0378-4754
No coin nor oath required. For personal study only.
β¦ Synopsis
In the paper, the weather generator WGENK producing synthetic daily data of solar radiation, maximum and minimum temperature, and total precipitation is presented. A WGENK model, modification of WGEN model, introduces annual courses of transition probability, Ξ± parameter of Ξ distribution, and correlation's between solar radiation and temperatures described by trigonometric polynomials. The method was tested by comparing statistics of 200 years of generated data with 20 years of observed weather data for five weather stations of southwest of Poland. The absolute correlation errors were decreased about three times in various time period while standard deviation of precipitation has lowered two times compared to original WGEN model; new correlations were examined (at 0.05 level) and accepted in 95% of 2520 tests.
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