Intelligent Decision Support Algorithm Based on Multimodal Data

Some grid companies have initially built a digital grid framework and promoted the integration of technology platforms and various technology components. However, there are still problems such as insufficient integration degree of technical services and general technical components and weak access ability of technical services. This research proposes a technology intelligent decision support algorithm based on multi-modal data. By integrating various data sources and technologies such as Nannetcloud microservice platform, AI components and blockchain components, hybrid machine learning and optimization algorithms are adopted to achieve efficient data processing and decision support. The core method of this research is to establish a unified data processing framework and an adaptive decision generation model, and verify its effectiveness through simulation and practical application. The test results of the response time of the technical service show that the average response time of the system gradually increases with the increase of the request volume. When the number of requests is less than 100 per second, the average response time remains at 750 milliseconds or less, and the request success rate is 100%. The algorithm not only improves the integration degree and access ability of technical services, but also enhances the efficiency and security of business implementation, and provides strong technical support for the company's digital transformation and rapid business construction.