Data-Driven Analysis of Regional Water Resources Allocation Decision-Making

Abstract Regional water allocation is of great importance to regional coordinated development. Therefore, this paper constructs a data-driven model for analysis address the existing problems imbalance between supply and demand, irrational utilization resources scarcity. Firstly, classification case constructed through cluster obtain similar regions with same salient characteristics. Then, in category are divided into be predicted other regions, similarity calculated. The Criteria Importance Through Intercriteria Correlation (CRITC) method used calculate weighted values each index forecast demands predicted. Finally, an example city Hubei province 2020 was carried out, results indicated that when 4 categories, characteristics different cities presented. relative errors demand do not exceed 5%, which highly accurate can provide decision support rational allocation.