Results 241 to 250 of about 164,385 (278)

AI-Enhanced Virtual LIG-IoT Sensor Framework for Microclimatic Stress Prediction in <i>Vasconcellea stipulata</i> (Toronche) from Southern Ecuador. [PDF]

Sensors (Basel)
Cuenca-Sánchez A, Pantoja-Suárez F.
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Dynamic pricing scheme for energy balancing in microgrid using an intelligent system. [PDF]

Sci Rep
Balakumar I, Vaithilingam C.
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Attention-Enhanced CNN-LSTM with Spatial Downscaling for Day-Ahead Photovoltaic Power Forecasting. [PDF]

Sensors (Basel)
Peng F, Tang X, Xiao M.
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A Solar Array Temperature Multivariate Trend Forecasting Method Based on the CA-PatchTST Model. [PDF]

Sensors (Basel)
Wang Y, Shi X, Zhang Z, Zhou F.
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Forecasting photovoltaic power in high-latitude regions via support vector machine optimized by meta-heuristics. [PDF]

Sci Rep
Oruç S, Hınıs MA, Tuğrul T.
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Development of a solar-integrated energy management system for grid-to-vehicle and vehicle-to-grid power exchange. [PDF]

Sci Rep
Rao NVK, Krishna KB.
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Atmospheric science: Solar cycle and climate predictions

, 2011
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The solar cycle: predicting the peak of solar cycle 25

Astrophysics and Space Science, 2020
Motivated by a successful prediction on the peak of solar cycle 24 (81.7, comparable to the observed 81.9, Du in Astrophys. Space Sci. 338:9, 2012), based on the logarithmic relationship between the maximum amplitude ( $R_{ \mathrm{m}}$ ) of a solar cycle and the preceding minimum $aa$ geomagnetic index ( $aa_{\mathrm{min}}$ ), we perform a ...
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Standard prediction of solar cycles

Geomagnetism and Aeronomy, 2008
To make a long-term prediction of the solar cycle in a standard way (GOST 25645.302-83), it is necessary to know the instant of the activity minimum onset, the determination of which is difficult during the decline stage of the previous cycle. The dependence of the long-term prediction error on the time of shift (t) relative to the solar activity ...
A. V. Kryachko, A. A. Nusinov
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