02300nam0 22004693i 450 VAN0027469920240806101540.442N978303094482720240410d2021 |0itac50 baengCH|||| |||||Deep Learning in Multi-step Prediction of Chaotic DynamicsFrom Deterministic Models to Real-World SystemsMatteo Sangiorgio, Fabio Dercole, Giorgio GuarisoChamSpringerPoliMI2021xii, 104 p.ill.24 cm001VAN001034342001 SpringerBriefs in applied sciences and technology210 Berlin [etc.]Springer2011-001VAN001270522001 SpringerBriefs in Applied Sciences and Technology. PoliMI SpringerBriefs210 Berlin [etc.]SpringerPolitecnico di Milano68-XXComputer science [MSC 2020]VANC019670MF68T07Artificial neural networks and deep learning [MSC 2020]VANC036862MF68TxxArtificial intelligence [MSC 2020]VANC021266MF93-XXSystems theory; control [MSC 2020]VANC027040MFChaotic attractorsKW:KEnvironmental variablesKW:KExposure biasKW:KHenon systemsKW:KNeural architecturesKW:KNeural network trainingKW:KRecurrent Neural NetworksKW:KCHChamVANL001889SangiorgioMatteoVANV2271461198545DercoleFabioVANV2271471697821GuarisoGiorgioVANV227148116936Politecnico di MilanoVANV111571650Springer <editore>VANV108073650ITSOL20241115RICAhttps://doi.org/10.1007/978-3-030-94482-7E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN00274699BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08DLOAD e-book 8197 08eMF8197 20240412 Deep Learning in Multi-step Prediction of Chaotic Dynamics4149028UNICAMPANIA