Who Will Pay for the “Mine Toxic Land”?—A Dynamic Game and Simulation Study of Negative Externality Governance in Rare Earth Mines Based on Prospect Theory

Managerial and Decision Economics, Journal Year: 2025, Volume and Issue: unknown

Published: April 16, 2025

ABSTRACT The contradiction between economic development and the negative externalities generated by extraction of ionic rare earth elements, such as resource depletion environmental pollution, is becoming increasingly prominent. Based on prospect theory, this paper utilizes perceived value game players to construct a benefit matrix that differs from traditional tripartite model. On basis analysis evolution static reward punishment mechanisms, three dynamic namely, reward, punishment, are successively introduced for analysis. study demonstrated under mechanism, three‐party evolutionary not asymptotically stable. After introduction becomes stable, all in show positive willingness govern. Furthermore, varying sensitivity coefficients result relatively stable governance behaviors mine enterprises. With different coefficients, product enterprises remains while government application more variable.

Language: Английский

Application of Image Recognition Methods to Determine Land Use Classes

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4765 - 4765

Published: April 25, 2025

The increasing availability of satellite data and advances in machine learning (ML) have significantly enhanced land use image classification for environmental monitoring. However, the primary challenge using imagery lies presence cloud cover, variations resolution, seasonal changes, which impact accuracy reliability. This paper aims to improve assessment cover changes by proposing a hybrid ML, interpolation, vegetation indices-based approach. proposed approach was implemented random forest (RF) classifier, combined with interpolation indices, classify Sentinel-2 Baltic States. experimental results demonstrate that achieves an rate above 90%, effectively demonstrating its capacity distinguish between various types. We believe this study will inspire researchers practitioners further work towards applying ML algorithms offer valuable insights future tasks involving noise digitalization research.

Language: Английский

Fusion of MobileNet and GRU: Enhancing Remote Sensing Applications for Sustainable Agriculture and Food Security

Remote Sensing in Earth Systems Sciences, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 19, 2024

Language: Английский