The article established the HDRICE model by modifying the structure of the ORYZA1 model and revising its parameters by field experiments. The HDRICE model consists of the modules of morphological development of rice, ...The article established the HDRICE model by modifying the structure of the ORYZA1 model and revising its parameters by field experiments. The HDRICE model consists of the modules of morphological development of rice, daily dry matter accumulation and partitioning, daily CO2 assimilation of the canopy, leaf area, and tiller development. The model preferably simulated the dynamic rice development because of the thorough integration of the effects of temperature and light on the rates of rice development, photosynthesis, respiration, and. other ecophysiological processes. In addition, this model has attainable grain yield in the test experiment that showed the potential yield of cultivar Xieyou 46 ranged from 11 to 13 tons ha-~. Besides, the model was used to optimize the combinations of the transplanting date, seedling age and density for cultivar Xieyou 46 at Jinhua area, and the population quantitative indices to attain the potential yield such as maximum stems, effective panicles, filled grain number/leaf area, and so on. The result showed that the combination of transplanting date on July 25, seedling age of 35 days and base seedling density of 1.33 x 106ha-1 is the optimum combination for the second hybrid rice production in Jinhua County, China. And the maximum stems, the effective panicles, the filled grain per panicle, the peak of optimum LAI, LAI in later filling stage, and the filled grain number/leaf were 6.03×10^6ha, 3.99×10^6ha, 119.2, 8.59, 5-6, and 0.64, respectively.展开更多
对于风电功率实时预测,如何有效的引入风速信息进行高精度的预测,需要进行深入研究。首先引入灰色理论中的灰色关联的算法,建立基于概率分布指标的量化分析模型(quantitative analysis model based on probability distribution,QAM-PD...对于风电功率实时预测,如何有效的引入风速信息进行高精度的预测,需要进行深入研究。首先引入灰色理论中的灰色关联的算法,建立基于概率分布指标的量化分析模型(quantitative analysis model based on probability distribution,QAM-PD)。其次通过实测风电场数据对模型进行分析,利用灰色关联关系和标准风速功率曲线建立基于灰色关联决策的风电功率实时预测模型(real-time prediction model of wind power based on gray relational decision,RPM-WPGRD)。最后选取中国东北某大规模风电场,对其风电功率进行预测。通过误差分析,相较于完全基于历史风速或者完全基于历史功率的算法,该方法可有效提高预测精度。展开更多
基金supported by the National Natural Science Foundation of China(69673044).
文摘The article established the HDRICE model by modifying the structure of the ORYZA1 model and revising its parameters by field experiments. The HDRICE model consists of the modules of morphological development of rice, daily dry matter accumulation and partitioning, daily CO2 assimilation of the canopy, leaf area, and tiller development. The model preferably simulated the dynamic rice development because of the thorough integration of the effects of temperature and light on the rates of rice development, photosynthesis, respiration, and. other ecophysiological processes. In addition, this model has attainable grain yield in the test experiment that showed the potential yield of cultivar Xieyou 46 ranged from 11 to 13 tons ha-~. Besides, the model was used to optimize the combinations of the transplanting date, seedling age and density for cultivar Xieyou 46 at Jinhua area, and the population quantitative indices to attain the potential yield such as maximum stems, effective panicles, filled grain number/leaf area, and so on. The result showed that the combination of transplanting date on July 25, seedling age of 35 days and base seedling density of 1.33 x 106ha-1 is the optimum combination for the second hybrid rice production in Jinhua County, China. And the maximum stems, the effective panicles, the filled grain per panicle, the peak of optimum LAI, LAI in later filling stage, and the filled grain number/leaf were 6.03×10^6ha, 3.99×10^6ha, 119.2, 8.59, 5-6, and 0.64, respectively.
文摘对于风电功率实时预测,如何有效的引入风速信息进行高精度的预测,需要进行深入研究。首先引入灰色理论中的灰色关联的算法,建立基于概率分布指标的量化分析模型(quantitative analysis model based on probability distribution,QAM-PD)。其次通过实测风电场数据对模型进行分析,利用灰色关联关系和标准风速功率曲线建立基于灰色关联决策的风电功率实时预测模型(real-time prediction model of wind power based on gray relational decision,RPM-WPGRD)。最后选取中国东北某大规模风电场,对其风电功率进行预测。通过误差分析,相较于完全基于历史风速或者完全基于历史功率的算法,该方法可有效提高预测精度。
