RCM SC-ANN Data

Published: 27 June 2025| Version 2 | DOI: 10.17632/5mktc323j4.2
Contributor:
Tomasz Bartuś

Description

The collection contains source data of morphodiversity evaluation of the Pieniny Mountains region (southern Poland) and evaluation results obtained using models using Supervised Classification (SC) methodology using artificial neural networks (ANN): RCMSC-ANN; RCMSC-ANN-M; models optimized using the Global Sensitivity Analysis (GSA) procedure in two variants: Backward Analysis (BA): RCMSC-ANN-BA; RCMSC-ANN-M-BA and GSA Backward Stepwise Analysis (BSA): RCMSC-ANN-BSA; RCMSC-ANN-M-BSA; as well as comparative models: SC-ANNVSR-9-BSA and RCMSDcm. Data and results are authored by Tomasz Bartuś and come from the work Development and Optimization of a Universal Morphodiversity Model for Mountainous Areas Using Supervised Classification and Artificial Neural Networks (in press).

Files

Steps to reproduce

The evaluations were created in Statistica (Neural Networks) software. The dataset includes the source data and ANN models.

Institutions

  • Akademia Gorniczo-Hutnicza imienia Stanislawa Staszica w Krakowie Wydzial Geologii Geofizyki i Ochrony Srodowiska

Categories

Artificial Neural Network, Geographic Information System, Particle Morphology, Mountain, Morphometry, Binary Classification

Funders

Licence