Abstract
Based on the factors that affect water resources carrying capacity, we establish water resources carrying capacity evaluation index system, introduce support vector machine (SVM) and utilize its minimization of structural risks in statistical learning theory and its advantage in solution to nonlinear and high dimensional identification, which overcomes the adverse impacts of subjective factors. We build a comprehensive evaluation model for regional water resources carrying capacity, and this model is applied to Zhoukou. The results show that water resources carrying capacity in most parts of Zhoukou is in an inferior level, which means the development of regional water resources has reached a considerable scale with obvious contradiction between the supply and demand of water resources. The model of comprehensive evaluation based on Support vector machine is reasonable and feasible in evaluation of regional water resources carrying capacity.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call