Работы, цитирующие эту работу

Работ: 4

Работа: Advancing solar thermal utilization by optimization of phase change material thermal storage systems: A hybrid approach of artificial neural network (ANN)/Genetic algorithm (GA)

1. Optimizing novel thermal energy storage systems: Enhancing melting efficiency with tubes, stands, and advanced machine learning techniques

   Ahmad Almadhor, Ali Basem, Pradeep Kumar Singh +7

   СтатьяPhase Change Materials ResearchJournal of Energy Storage2025Цитирований: 5

   ABIABI:AkademIndex/openalex/2025.article.000117

2. Improving energy absorption capacity in a thermal energy storage system for domestic heating applications using an integrated machine learning/numerical approach

   Xianzhi Tang, Xin Sun, Sinan Q. Salih +7

   СтатьяPhase Change Materials ResearchApplied Thermal Engineering2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2025.article.001117

3. Triangular-rib structural mastery for enhanced latent heat storage system: Artificial neural network optimization of geometry, orientation, and cost-effectiveness

   Jun-bo Mao, Ali Basem, Hyder H. Abed Balla +7

   СтатьяPhase Change Materials ResearchJournal of Energy Storage2026Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.article.000057

4. Base-integrated thermal storage system: Enhancing phase change material melting performance through geometric innovation and artificial neural network-genetic algorithm optimization

   Jun-bo Mao, Ali Basem, Hyder H. Abed Balla +7

   СтатьяPhase Change Materials ResearchInternational Communications in Heat and Mass Transfer2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.008757