Работы, цитирующие эту работу

Работ: 4

Работа: Connectionist approaches for solubility prediction of n-alkanes in supercritical carbon dioxide

1. A robust machine learning framework for predicting CO2 solubility in polyethylene glycol using advanced optimization strategies

   Fadhel F. Sead, Dharmesh Sur, Anupam Yadav +7

   СтатьяPhase Equilibria and ThermodynamicsChinese Journal of Analytical Chemistry2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.010719

2. Developing rigorous machine learning models to accurately estimate pesticide photodegradation by ZnO-based photocatalysts in water

   Farag M. A. Altalbawy, Shoira Formanova, Ahmad Almalkawi +7

   СтатьяWater Quality Monitoring and AnalysisJournal of the Indian Chemical Society2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.016579

3. Prediction of H ₂ S adsorption capacity of biochar using rigorous machine learning frameworks

   Kassem Al Attabi, Farag M. A. Altalbawy, Anupam Yadav +5

   СтатьяIndustrial Gas Emission ControlJournal of Environmental Science and Health Part A2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.017816

4. Effects of physical properties on the heavy metal adsorption of biochar via a robust approach

   Mahran Al-Zyoud, Salama A. Mostafa, Ibrahim Khersan +6

   СтатьяAdsorption and biosorption for pollutant removalCurrent Research in Biotechnology2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.000174