Philippe du Jardin

According to our database, Philippe du Jardin authored at least 13 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Designing topological data to forecast bankruptcy using convolutional neural networks.

Philippe du Jardin

Ann. Oper. Res., June, 2023

2021

Forecasting corporate failure using ensemble of self-organizing neural networks.

Philippe du Jardin

Eur. J. Oper. Res., 2021

Dynamic self-organizing feature map-based models applied to bankruptcy prediction.

Philippe du Jardin

Decis. Support Syst., 2021

Forecasting bankruptcy using biclustering and neural network-based ensembles.

Philippe du Jardin

Ann. Oper. Res., 2021

2018

Failure pattern-based ensembles applied to bankruptcy forecasting.

Philippe du Jardin

Decis. Support Syst., 2018

2017

Dynamics of firm financial evolution and bankruptcy prediction.

Philippe du Jardin

Expert Syst. Appl., 2017

2016

A two-stage classification technique for bankruptcy prediction.

Philippe du Jardin

Eur. J. Oper. Res., 2016

2015

SOM-ELM - Self-Organized Clustering using ELM.

Yoan Miché, Anton Akusok, David Veganzones, Kaj-Mikael Björk, Eric Séverin, Philippe du Jardin, Maite Termenon, Amaury Lendasse

Neurocomputing, 2015

MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model.

Anton Akusok, David Veganzones, Yoan Miché, Kaj-Mikael Björk, Philippe du Jardin, Eric Séverin, Amaury Lendasse

Neurocomputing, 2015

Bankruptcy prediction using terminal failure processes.

Philippe du Jardin

Eur. J. Oper. Res., 2015

2012

Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time.

Philippe du Jardin, Eric Séverin

Eur. J. Oper. Res., 2012

2011

Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model.

Philippe du Jardin, Eric Séverin

Decis. Support Syst., 2011

2010

Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy.

Philippe du Jardin

Neurocomputing, 2010