# Dominant Design Prediction with Phylogenetic Networks

arXiv: https://arxiv.org/abs/2407.10206 · HTML: https://mlsanity.com/paper/2407.10206/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 14 Jul 2024.

## Builds on (most cited first, 3 of 3)

- [Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://mlsanity.com/paper/1606.09375/) (2016)
- [Gated Graph Sequence Neural Networks](https://mlsanity.com/paper/1511.05493/) (2015)
- [Graph Neural Networks in TensorFlow and Keras with Spektral](https://mlsanity.com/paper/2006.12138/) (2020)

## Abstract (arXiv)

This study proposes an effective method to predict technology development from an evolutionary perspective. Product evolution is the result of technological evolution and market selection. A phylogenetic network is the main method to study product evolution. The formation of the dominant design determines the trajectory of technology development. How to predict future dominant design has become a key issue in technology forecasting and new product development. We define the dominant product and use machine learning methods, combined with product evolutionary theory, to construct a Fully Connected Phylogenetic Network dataset to effectively predict the future dominant design.