It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...

This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...

Abstract: BP neural network has been widely used in pattern recognition, predictive analysis, control optimization, data mining, etc. Optimizing its structure holds immense importance. For the sake of ...

Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...

ABSTRACT: Groundwater is an essential resource for rural dwellers in Burkina Faso, a country with limited surface water availability. However, localising and accessing groundwater is challenging. This ...

With the rapid optimization and evolution of various neural networks, the control problem of robotic arms in the area of automation control has gradually received more attention. The research results ...

Abstract: The challenge with self-driving cars is to create a model that converts sensors data (such as cameras or proximity sensors) into actions. This way the car can react to its changing ...