Forecasting daily ozone concentration-a comparison between neurocomputing and statistical approaches

SURAJIT CHATTOPADHYAY; GOUTAMI CHATTOPADHYAY-BANDYOPADHYAY

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Forecasting daily ozone concentration-a comparison between neurocomputing and statistical approaches

机译：预测每日臭氧浓度-神经计算和统计方法之间的比较

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摘要

In the printed edition of Volume 29, Numbers 7-8 (April 2008), the name of Professor Goutami Chattopadhyay-Bandyopadhyay was incorrectly written. It has been updated above and is correct in the online edition.

机译：在第29卷第7-8期的印刷版中（2008年4月），Goutami Chattopadhyay-Bandyopadhyay教授的名字写得不正确。它已经在上面进行了更新，并且在在线版本中是正确的。

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来源
《International journal of remote sensing》 |2008年第12期|p.3673|共1页
作者
SURAJIT CHATTOPADHYAY; GOUTAMI CHATTOPADHYAY-BANDYOPADHYAY;
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作者单位

Department of Information Technology, Pailan College of Management and Technology, Kolkata 700104, India;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类遥感技术;
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1. Forecasting daily total ozone concentration-a comparison between neurocomputing and statistical approaches [J] . SURAJIT CHATTOPADHYAY, GOUTAM CHATTOPADHYAY-BANDYOPADHYAY International journal of remote sensing . 2008,第7a8期

机译：预测每日总臭氧浓度-神经计算和统计方法之间的比较
2. Multivariate forecast of winter monsoon rainfall in India using SST anomaly as a predictor: Neurocomputing and statistical approaches [J] . Goutami Chattopadhyay, rnSurajit Chattopadhyay, rnRajni Jain Comptes rendus . 2010,第10期

机译：使用SST异常作为预测因子的印度冬季季风降水的多变量预测：神经计算和统计方法
3. Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches [J] . Ramos Yuddy, Requia Weeberb J., St-Onge Benoit, Environmental research . 2018,第OCTa期

机译：加拿大蒙特利尔每日臭氧水平每日浓度的空间模拟：地统计学方法的比较
4. Comparison of regression and neural network approaches to forecast daily power consumption [C] . Kryukov Dmitri, Agafonova Maria, Arestova Anna International Forum on Strategic Technology . 2016

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5. A regression model to forecast the daily peak 8-h ozone concentration for the Louisville Metropolitan Statistical Area. [D] . Greenwell, Charles Glenn. 2001

机译：用来预测路易斯维尔都会统计区每日8小时臭氧峰值浓度的回归模型。
6. Forecast predictions for the COVID-19 pandemic in Brazil by statistical modeling using the Weibull distribution for daily new cases and deaths [O] . Vitor Hugo Moreau 2020

机译：通过使用Weibull分布对日常新病例和死亡的统计建模通过统计建模预测巴西Covid-19大流行的预测
7. Comparison of probabilistic post-processing approaches for improving NWP-based daily and weekly reference evapotranspiration forecasts [O] . Hanoi Medina, Di Tian 2019

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8. Ensemble Statistical Post-Processing of the National Air Quality Forecast Capability: Enhancing Ozone Forecasts in Baltimore, Maryland. [R] . Garner, G. G., Thompson, A. M. 2013

机译：国家空气质量预报能力的集合统计后处理：加强马里兰州巴尔的摩的臭氧预报。

Forecasting daily ozone concentration-a comparison between neurocomputing and statistical approaches

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