In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation for...In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation forecasts in Vietnam in current stage. The study introduces the within-sample and the out-of-samples one-step-ahead forecast errors which have positive correlation and approximate to a linear function with positive slope in prediction models by GP. We also build Vector Autoregression (VAR) model to forecast CPI in quaterly data and compare with the models created by GP. The experimental results show that the Genetic Programming can produce the prediction models having better accuracy than Vector Autoregression models. We have no relavant variables (m2, ex) of monthly data in the VAR model, so no prediction results exist to compare with models created by GP and we just forecast CPI basing on models of GP with previous data of CPI.展开更多
A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadr...A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadratic programming is given. This model has extensive representation. It is a new kind of aggregative method of group forecasting. By taking the suitable combining form of the forecasting models and seeking the optimal parameter, the optimal combining form can be obtained and the forecasting accuracy can be improved. The effectiveness of this model is demonstrated by an example.展开更多
为评估从数值预报、客观方法到主观预报产品各环节对天气预报准确率的贡献,研发了天气预报全流程检验评估程序库(Meteorological Evaluation Program Library,简称为MetEva)。MetEva以检验算法的全流程覆盖和检验结果的可对比性为目标,...为评估从数值预报、客观方法到主观预报产品各环节对天气预报准确率的贡献,研发了天气预报全流程检验评估程序库(Meteorological Evaluation Program Library,简称为MetEva)。MetEva以检验算法的全流程覆盖和检验结果的可对比性为目标,采用包含基础层和功能层的分层架构,基于统一的数据结构,设计了模块化的检验计算流程。围绕数据读取、数据合并与匹配、样本选取、样本分组、检验计算和结果输出等6个主要步骤,MetEva提供了6类400项功能函数。MetEva集成了5类54种检验算法,涵盖了大部分世界气象组织推荐和国内业务规范要求的检验算法,并对其计算流程进行改进,同时采用矩阵计算方式和并行算法来提升检验程序的计算效率。以温度和降水预报的检验评估为例,简要说明了MetEva的功能和使用方法,展示了MetEva在精细化检验评估方面的应用价值。该程序库已开源发布,可有效支撑全国各级气象部门开展天气预报全流程检验评估工作。展开更多
Assessment of the current status of Lake Baikal proved to be based on changes in natural (“preindustrial”) chemical content in basic abiotic and biological compartments of the Lake geosystem. This approach was used ...Assessment of the current status of Lake Baikal proved to be based on changes in natural (“preindustrial”) chemical content in basic abiotic and biological compartments of the Lake geosystem. This approach was used to evaluate background “base-line levels” of 6 major and about 50 minor and trace ele-ments in the Lake Baikal water body using a number of most reliable data re-ported within 1992-2012. In terms of environment geochemistry Baikal is one of the purest water reservoirs on the Earth. A simple mass balance model was proposed for assessing possible anthropogenic impact on Baikal water geo-chemistry. Estimations of change trends showed that only for Na+, SO42-, Cl- and Mo growth rate of their average concentrations in the Lake occurred to be 1%, 3%, 7% and 2% in every 10 years. Space-time monitoring schedules for all water body compartments of the Lake are proposed as well as similar moni-toring programs for tributaries, precipitations, bottom sediments, aquatic biota.展开更多
文摘In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation forecasts in Vietnam in current stage. The study introduces the within-sample and the out-of-samples one-step-ahead forecast errors which have positive correlation and approximate to a linear function with positive slope in prediction models by GP. We also build Vector Autoregression (VAR) model to forecast CPI in quaterly data and compare with the models created by GP. The experimental results show that the Genetic Programming can produce the prediction models having better accuracy than Vector Autoregression models. We have no relavant variables (m2, ex) of monthly data in the VAR model, so no prediction results exist to compare with models created by GP and we just forecast CPI basing on models of GP with previous data of CPI.
文摘A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadratic programming is given. This model has extensive representation. It is a new kind of aggregative method of group forecasting. By taking the suitable combining form of the forecasting models and seeking the optimal parameter, the optimal combining form can be obtained and the forecasting accuracy can be improved. The effectiveness of this model is demonstrated by an example.
文摘为评估从数值预报、客观方法到主观预报产品各环节对天气预报准确率的贡献,研发了天气预报全流程检验评估程序库(Meteorological Evaluation Program Library,简称为MetEva)。MetEva以检验算法的全流程覆盖和检验结果的可对比性为目标,采用包含基础层和功能层的分层架构,基于统一的数据结构,设计了模块化的检验计算流程。围绕数据读取、数据合并与匹配、样本选取、样本分组、检验计算和结果输出等6个主要步骤,MetEva提供了6类400项功能函数。MetEva集成了5类54种检验算法,涵盖了大部分世界气象组织推荐和国内业务规范要求的检验算法,并对其计算流程进行改进,同时采用矩阵计算方式和并行算法来提升检验程序的计算效率。以温度和降水预报的检验评估为例,简要说明了MetEva的功能和使用方法,展示了MetEva在精细化检验评估方面的应用价值。该程序库已开源发布,可有效支撑全国各级气象部门开展天气预报全流程检验评估工作。
文摘Assessment of the current status of Lake Baikal proved to be based on changes in natural (“preindustrial”) chemical content in basic abiotic and biological compartments of the Lake geosystem. This approach was used to evaluate background “base-line levels” of 6 major and about 50 minor and trace ele-ments in the Lake Baikal water body using a number of most reliable data re-ported within 1992-2012. In terms of environment geochemistry Baikal is one of the purest water reservoirs on the Earth. A simple mass balance model was proposed for assessing possible anthropogenic impact on Baikal water geo-chemistry. Estimations of change trends showed that only for Na+, SO42-, Cl- and Mo growth rate of their average concentrations in the Lake occurred to be 1%, 3%, 7% and 2% in every 10 years. Space-time monitoring schedules for all water body compartments of the Lake are proposed as well as similar moni-toring programs for tributaries, precipitations, bottom sediments, aquatic biota.
