# QxEAI: Quantum-like evolutionary algorithm for automated probabilistic forecasting

arXiv: https://arxiv.org/abs/2405.03701 · HTML: https://mlsanity.com/paper/2405.03701/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 28 references that are in the map.
- First posted on arXiv 2 May 2024.

## Builds on (most cited first, 2 of 2)

- [DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks](https://mlsanity.com/paper/1704.04110/) (2017)
- [Review of automated time series forecasting pipelines](https://mlsanity.com/paper/2202.01712/) (2022)

## Abstract (arXiv)

Forecasting, to estimate future events, is crucial for business and decision-making. This paper proposes QxEAI, a methodology that produces a probabilistic forecast that utilizes a quantum-like evolutionary algorithm based on training a quantum-like logic decision tree and a classical value tree on a small number of related time series. We demonstrate how the application of our quantum-like evolutionary algorithm to forecasting can overcome the challenges faced by classical and other machine learning approaches. By using three real-world datasets (Dow Jones Index, retail sales, gas consumption), we show how our methodology produces accurate forecasts while requiring little to none manual work.