Suchergebnisse - reduced deep conventional stack autoencoder

Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance multikernel random vector functional network von Sahani, Mrutyunjaya, Choudhury, Sasmita, Siddique, Marif Daula, Parida, Tanmoy, Dash, Pradipta Kishore, Panda, Sanjib Kumar

“… To address this, we have developed a novel hybrid model: a reduced deep convolutional stack autoencoder with a minimum variance multikernel random vector functional link network (RDCSAE-MVMRVFLN …”
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Post-stack seismic impedance inversion based on sparse-coded Mamba seismic model von Lin, Yijian, Peng, Suping, Cui, Xiaoqin, Lu, Yongxu

“… Post-stack seismic impedance inversion plays a vital role in reservoir characterization and seismic attribute analysis, enabling the interpretation of lithological properties and the prediction …”
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