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Related Experiment Video

Updated: Sep 22, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

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Published on: July 24, 2016

Preference prediction analysis based on graph model for environmental governance conflict.

Jinshuai Zhao¹, Baohua Yang²

¹School of Computer Science and Technology, Jiangsu Normal University, No.101 Shanghai Road, Tongshan District, Xuzhou 221116, China.

Mathematical Biosciences and Engineering : MBE

|May 23, 2022

Summary

This summary is machine-generated.

This study introduces a mathematical model to predict decision-maker preferences in environmental conflicts, aiding environmental management. The model helps understand polluting companies' motivations for better governance strategies.

Keywords:

conflict analysis decision making environmental governance environmental pollution environmental protection graph model preference prediction

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Area of Science:

Environmental Science
Mathematical Modeling
Game Theory

Background:

Rapid economic development has led to severe environmental pollution.
Profit-seeking sewage companies often evade environmental governance.
Environmental management struggles to accurately assess offending company preferences.

Purpose of the Study:

To develop a mathematical model for predicting decision-maker preferences in environmental governance conflicts.
To accurately obtain the preference set of one decision-maker when others' preferences and ideal outcomes are known.
To provide strategic decision-making support for environmental governance.

Main Methods:

Graph Model for Conflict Resolution (GMCR)
Mathematical modeling for preference prediction
Information entropy for preference value distribution analysis

Main Results:

A novel mathematical model accurately predicts decision-maker preferences in environmental conflicts.
The model successfully mines preference information using information entropy.
A case study on chromium pollution in Qujing County validates the method's effectiveness.

Conclusions:

The developed preference prediction model offers effective decision-making support for environmental governance.
The method enables understanding of conflict opponents' preferences at their ideal outcomes.
This approach facilitates the selection of appropriate coping strategies to steer conflicts favorably.