Visual Programming of Stochastic Weather Generator and Future Applications on Agroecological Study

来源 :Agricultural Sciences in China | 被引量 : 0次 | 上传用户:vl244
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Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator(VS-WGEN)was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, and weak stationary process were used to generate the daily weather data in software Matlab 6. 0, with the data input from 40 years’ weather data recorded by Beijing Weather Station. The generated data includes daily maximum temperature, minimum temperature, precipitation and solar radiation. It has been verified that the weather data generated by the VS-WGEN were more accurate than that by the old WGEN, when twenty new model parameters were included. VS-WGEN has wide software applications, such as pest risk analysis, pest forecast and management. It can be implemented in hardware development as well, such as weather control in weather chamber and greenhouse for researches on ecological adaptation of crop varieties to a given location over time and space. Overall, VS-WGEN is a very useful to Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator (VS-WGEN) was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, and weak stationary process were used to generate the The weather data recorded by Beijing Weather Station. The generated data includes daily maximum temperature, minimum temperature, precipitation and solar radiation. It has been verified that the weather data generated by the VS-WGEN were more accurate than that by the old WGEN, when twenty new model parameters were included. VS-WGEN has wide software applications, such as pest risk analysis, pest forecast and management. It can be implemented in hardware development as well, such as weather control in weather chamber and greenhouse for researches on ecological adaptation of crop varieties to a given location over time and space. Overall, VS-WGEN i s a very useful to
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