Yang‐Seon Kim

2 ta ish

Mechanical Engineering Department, College of Engineering, Wichita State University, Wichita, KS 67260, USA

1. Advanced techniques for electricity consumption prediction in buildings using comparative correlation analysis, data normalization, and Long Short-Term Memory (LSTM) networks: A case study of a U.S. commercial building

   Moon Keun Kim, Yang‐Seon Kim, Nuodi Fu +4

   MaqolaBuilding Energy and Comfort OptimizationEnergy Reports20250 iqtibos

   ABIABI:AkademIndex/openalex/2025.article.000191

2. Advanced Techniques for Electricity Consumption Prediction in Buildings Using Comparative Correlation Analysis, Data Normalization, and Long Short-Term Memory (Lstm) Networks: A Case Study of a U.S. Commercial Building

   Moon Keun Kim, Yang‐Seon Kim, Nuodi Fu +4

   PreprintEnergy Load and Power ForecastingSSRN Electronic Journal20250 iqtibos

   ABIABI:AkademIndex/openalex/2025.preprint.000068