CONFLICT BETWEEN WATER SUPPLY AND ENVIRONMENTAL HEALTH RISK: A COMPUTATIONAL NEURAL NETWORK APPROACH

摘要

A two-person conflict is analyzed, where a water company and a community are the players and water supply and health risk constitute the payoff functions. An aquifer's response to different pumping policies is estimated at points of interest by a computational neural network, which was trained using simulation data from MODFLOW, a large-scale complicated finite difference model. Using the weighting method, the Pareto frontier is first determined, and four particular resolution methodologies are applied. The numerical results are analyzed and compared.