Project Overview

This project focuses on the stability of decision-support models used in wind-farm siting under uncertainty and limited data. In practical energy planning, models are often built from heterogeneous information sources and incomplete datasets, yet their recommendations are expected to remain consistent and reliable as conditions change.

The research investigates how fuzzy rule-based models behave when input data are resampled, perturbed, or partially unavailable, with particular attention to changes in decision rules and site rankings. By developing quantitative stability indicators at the rule and decision-logic level, the project provides a clearer assessment of model robustness beyond traditional accuracy metrics.

The goal is to support more reliable and transparent early-stage wind-farm siting decisions by explicitly evaluating how sensitive model recommendations are to realistic data variations.