Application of artificial neural network in the modeling and optimization of volatile acid from anaerobic digestion of biomass

Ali Noohi

doi:10.5937/ror2401029N

Autori

Ali Noohi Ca' Foscari University, Department of Environmental Sciences, Informatics and Statistics, Venice, Italy Author

DOI:

https://doi.org/10.5937/ror2401029N

Ključne reči:

isparljive masne kiseline, mašinsko učenje, veštačka neuronska mreža, višeslojni model, anaerobna digestija, fermentacija

Apstrakt

Veštačke neuronske mreže (ANN) zajedno sa Brute Force algoritmima (BF) predstavljaju dve od najčešćih i najjednostavnijih tehnika za modelovanje nelinearnih problema i linearnu pretragu za pronalaženje elementa. Veoma veliki skupovi podataka se zapravo sakupljaju i unose u ANN. Algoritam se pokreće i iterativno vrši milijarde malih prilagođavanja težina i pristrasnosti miliona čvorova. U ovom radu, koristili su se pilot testovi fermentacije u manjem obimu sa mešavinama kanalizacionog mulja i ostataka hrane, kako bi se istražili različiti parametri procesa koji utiču na prinose fermentacije. Pristup mašinskog učenja je korišćen za upravljanje podacima i razvoj modela sposobnog da koreliše performanse procesa na osnovu različitih ulaznih parametara. Kako bi se simulisao rad digestora i procenili izlazi isparljivih masnih kiselina (VFA), razvijen je višeslojni ANN model sa dva skrivena sloja. ANN i BF su korišćeni za simulaciju i optimizaciju VFA iz anaerobne digestije.

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