Titlebook: Machine Learning and Data Mining Approaches to Climate Science; Proceedings of the 4 Valliappa Lakshmanan,Eric Gilleland,Martin Tingley Con

BULK

書目名稱Machine Learning and Data Mining Approaches to Climate Science影響因子(影響力)




書目名稱Machine Learning and Data Mining Approaches to Climate Science影響因子(影響力)學科排名




書目名稱Machine Learning and Data Mining Approaches to Climate Science網絡公開度




書目名稱Machine Learning and Data Mining Approaches to Climate Science網絡公開度學科排名




書目名稱Machine Learning and Data Mining Approaches to Climate Science被引頻次




書目名稱Machine Learning and Data Mining Approaches to Climate Science被引頻次學科排名




書目名稱Machine Learning and Data Mining Approaches to Climate Science年度引用




書目名稱Machine Learning and Data Mining Approaches to Climate Science年度引用學科排名




書目名稱Machine Learning and Data Mining Approaches to Climate Science讀者反饋




書目名稱Machine Learning and Data Mining Approaches to Climate Science讀者反饋學科排名

DEMN

addition

Stable-Angina

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murmur

Multilevel Random Slope Approach and Nonparametric Inference for River Temperature, Under Haphazard mates. We address these concerns using multilevel random slope models and nonparametric bootstrap inference for assessing the statistical significance of the annual trend in river temperature when measurement times and dates are haphazard.

友好

Teleconnections in Climate Networks: A Network-of-Networks Approach to Investigate the Influence of d as two separate climate networks, and teleconnections within the individual climate networks are studied with special focus on dipolar patterns. Our analysis reveals a pronounced rainfall dipole between Southeast Asia and the Afghanistan-Pakistan region, and we discuss the influences of Pacific SST anomalies on this dipole.

Gustatory

少量

Predicting Crop Yield via Partial Linear Model with Bootstrapence of orthonormal basis functions of the appropriate function space. We use different bootstrap schemes to produce prediction bounds and error estimates for the model, since the noise terms appear to be heteroscedastic and non-normal in the data. Results are presented and caveats and extensions to the model are also discussed.

Facilities

不安

Evaluation of Global Climate Models Based on Global Impacts of ENSOsed this criteria to evaluate the Coupled Model Intercomparison Project (CMIP5) GCMs. We found that the global impact of ENSO in CNRM-CM5, GFDL-CM3, and CESM-FASTCHEM is highly similar to that of observations.