Titlebook: Artificial Neural Networks in Hydrology; R. S. Govindaraju,A. Ramachandra Rao Book 2000 Springer Science+Business Media B.V. 2000 artifici

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書目名稱Artificial Neural Networks in Hydrology影響因子(影響力)




書目名稱Artificial Neural Networks in Hydrology影響因子(影響力)學(xué)科排名




書目名稱Artificial Neural Networks in Hydrology網(wǎng)絡(luò)公開度




書目名稱Artificial Neural Networks in Hydrology網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Neural Networks in Hydrology被引頻次




書目名稱Artificial Neural Networks in Hydrology被引頻次學(xué)科排名




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書目名稱Artificial Neural Networks in Hydrology讀者反饋




書目名稱Artificial Neural Networks in Hydrology讀者反饋學(xué)科排名

PLUMP

The metal-insulator transition in Si:P,cal to answering questions posed by management. These questions range from “what are the pathways by which receptors may be exposed to (human or ecological) health risks” to “can I determine from existing measurement data whether a buried facility is failing”.

無節(jié)奏

笨拙處理

CHOP

Hans Peter Wagner,Hermann Leidererrunoff and storage. The space-time distribution of soil moisture can influence atmospheric system on time scales from several hours to many years. Currently, the most feasible procedure to obtain soil moisture over large areas is through remote sensing.

NATTY

Optical characterization of ZnTe epilayers,ly to lakes, rivers and sub-surface moisture storage, which are the primary sources of water supply for plants and animals. Therefore, a better understanding of the temporal and spatial distribution of precipitation is critical to long-term water resources and agricultural system planning.

CERE

彎曲的人

溝通

Adaptive Neural Networks in Regulation of River Flows,mand for water. One of the ways to conserve water is to estimate the water demand accurately, and provide just the right quantity of water to the users, i.e. match supply with demand as closely as possible.

Favorable