An issue with erroneous result assessment exists, despite the critical significance that resource management evaluation plays in data center resource management systems. Uneven resource consumption in the data center resource management system is an issue that traditional management strategies cannot handle, and the assessment is unreasonable. This study suggests an incremental learning algorithm to assess and analyze the most effective way to manage innovation resources. To begin, the data nodes are evaluated using the three-ring theory. The indicators are then split according to the criteria of the resource management assessment in order to eliminate interference elements. Next, a resource management assessment scheme is developed and the findings are thoroughly analyzed using the three-ring theory, which assesses the management of resources in response to the ever-changing demand for data center resources. According to MATLAB simulations, incremental learning algorithms outperform conventional management technologies in terms of resource allocation, dynamically modified evaluation accuracy, and assessment time for resource management, under certain evaluation criteria.