Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Mahesh Pal

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Sep 2026

Uncertainty Estimation in Predicting River Discharge Using Probabilistic Machine Learning and Conformal Prediction

Reliable streamflow forecasting with quantified uncertainty is essential for water resource management, flood mitigation, and climate adaptation in semi-arid regions. This research introduces a framework that combines three conformal prediction techniques, including Split Conformal Prediction (SplitCP), Cross Validatio...

Erfan Abdi, MohammadTaghi Sattari, Mahesh Pal et al. · 0 citations
Sep 2026

Machine learning for sustainable concrete incorporating marble waste and recycled aggregate

This study aims to evaluate the mechanical and durability performance of sustainable concrete incorporating Marble Fine Powder (MFP), Marble Coarse Powder (MCP) and Recycled Concrete Aggregate (RCA), and to develop machine learning (ML) models for accurate prediction of concrete properties. A total of 250 ex...

Ravikant, P. Aggarwal, Mahesh Pal · 0 citations
Review 2026

A Literature Review on the Comparative Analysis of Response Surface Methodology and the Taguchi Method in Concrete Optimization

This review paper provides a comprehensive comparison between response surface methodology (RSM) and the Taguchi method (TM) in the context of concrete mix design optimization. Existing studies often examine these methods independently, lacking a systematic comparison focused on their relevance to sustainable and cos...

Ravikant, P. Aggarwal, Mahesh Pal · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.