Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...
A forecasting-driven framework integrates ARIMA, LSTM, and ensemble learning to optimize cloud resource scheduling. By predicting CPU, memory, ...
The AI Prompt Optimization Platform is a professional tool designed to help users optimize prompts for AI models, enhancing AI conversation effectiveness and response accuracy. The platform integrates ...
Abstract: Finite control set model predictive current control (FCS-MPCC) often induces notable thrust fluctuations and elevated current harmonics in permanent magnet synchronous linear motor (PMSLM) ...
Abstract: This study employs an LSTM model to accurately predict future cargo volumes in logistics sorting centers, and subsequently develops a linear programming model based on these predictions to ...
Background: Plant-based diets with reduced animal protein intake are increasingly recommended for health and sustainability reasons that have potential implications for nutrient intake, including ...
Background: Large language model (LLM) fine tuning is the process of adjusting out-of-the-box model weights using a dataset of interest. Fine tuning can be a powerful technique to improve model ...
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