Retrieval-Augmented Generation (RAG) has become a standard paradigm for grounding large language models (LLMs) in external knowledge, but typical deployments introduce substantial energy, latency, and cost overhead due to expensive retrieval and context-processing pipelines. Recent work in "Green AI" and sustainable ma...
Anupam Dhakal, Prashant Pokharel, S. Adhikari· European Journal of Applied...· 0 citations
This study utilizes robust machine learning (ML) techniques to predict compressive strength of fly-ash-based geopolymer concrete (GPC), a sustainable replacement for traditional concrete. Popular ensemble models, specifically Random Forest (RF) and Extreme Gradient Boosting (XGB), were taken as base models and were hyb...
Subodh Subedi, Ajaya Subedi, S. Adhikari et al.· Bulletin of Computational In...· 1 citation
An optimized machine learning framework for reliable bond strength prediction by integrating Extra Trees Regressor and CatBoost with Grasshopper Optimization and Northern Goshawk Optimization for hyperparameter optimization is presented.
Sanjog Chhetri Sapkota, S. Adhikari, Nisha Panta et al.· Buildings· 1 citation
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