Работы, цитирующие эту работу

Работ: 4

Работа: Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques

1. Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals

   Shokirbek Shermukhamedov, Dilorom Mamurjonova, Thana Maihom +1

   СтатьяMachine Learning in Materials ScienceJournal of Chemical Information and Modeling2024Цитирований: 1

   ABIABI:AkademIndex/openalex/2024.article.001016

2. Structure to Property: Machine Learning Methods for Predicting Electronic Properties of Crystals

   Shokirbek Shermukhamedov, Dilorom Mamurjonova, Thana Maihom +1

   ПрепринтMachine Learning in Materials ScienceChemRxiv2023Цитирований: 0

   ABIABI:AkademIndex/openalex/2023.preprint.000024

3. Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks

   Shokirbek Shermukhamedov, Dilorom Mamurjonova, Michael Probst

   СтатьяMachine Learning in Materials ScienceAPL Machine Learning2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002993

4. Enhancing Renewable Energy Forecasting: A Comparative Study of Machine Learning and Deep Learning Techniques

   Pooja Pooja, Nosirjon Abdurazaqov, Р. Алиев

   ГлаваEnergy Load and Power ForecastingLecture notes in networks and systems2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.chapter.000533