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Hybrid nanofluid density prediction dataset for the IEEE Access research paper: "A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and Deep Learning Paradigms"

  • Updated Mar 9, 2025

Reproducible Python pipeline for the IEEE Access paper "A Seven-Year Higher-Order Ambisonics Recording Corpus" - corpus-wide figures (geography, timeline, room acoustics, loudness, session inventory), LaTeX-macro generation for every numeric claim, and the peer-review bootstrap uncertainty analysis for the microphone-comparison results.

  • Updated Aug 4, 2026
  • Python

This repository contains code for a comprehensive hybrid machine learning and deep learning frameworks for accurately predicting hybrid nanofluid density using stacking ensembles, advanced data augmentation, and metaheuristic optimization techniques.

  • Updated Mar 9, 2025

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