Equipment quality and supplier intelligent evaluation method based on space-time coupling Bayesian model and two-ticket graph database

By constructing an intelligent evaluation method that combines a spatiotemporally coupled Bayesian model with a two-vote graph database, the problem of insufficient compatibility between the data support system and the evaluation model in existing technologies is solved. This enables dynamic and precise evaluation of equipment quality and suppliers, and improves the accuracy and timeliness of equipment anomaly identification and supplier risk prediction.

CN121660518APending Publication Date: 2026-03-13CHINA THREE GORGES CORPORATION
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Patent Information

Application Number
CN202511779305.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-28
Publication Date
2026-03-13

AI Technical Summary

Technical Problem

Existing supplier evaluation technologies have significant deficiencies in data support systems and core algorithm models, resulting in insufficient accuracy, adaptability, and guidance of evaluation results, which cannot meet the needs of new power systems for refined supply chain management.

Method used

We construct an intelligent evaluation method based on a spatiotemporally coupled Bayesian model and a two-vote graph database. The two-vote graph database provides multi-dimensional related data support, dynamic environment adaptability, systemic risk quantification, and full-process traceability. Combined with technologies such as entropy weighting, spatiotemporal encoder, and graph attention network, we achieve intelligent evaluation of equipment quality and suppliers.

Benefits of technology

It enables dynamic, precise, and intelligent evaluation of equipment quality and suppliers, improves the accuracy of equipment anomaly identification and the timeliness of supplier risk prediction, supports enterprises in optimizing supply chain management, and reduces losses from unplanned downtime.

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Abstract

The invention provides an equipment quality and supplier intelligent evaluation method based on a space-time coupling Bayesian model and a two-ticket graph database, and belongs to the technical field of intelligent databases. The two-ticket graph database is firstly constructed, and a station environment, equipment full life cycle maintenance and supplier data are integrated; obtaining a supplier initial score by using an entropy weight method and a Sigmoid function; constructing a space-time coupling Bayesian model by means of ST-LSTM and VAE, and clustering equipment health states; introducing an environment coefficient and a KL divergence gradient to correct a score, and separating environment responsibilities from supplier responsibilities; calculating an equipment target score by combining an aging model and cosine similarity; and aggregating scores through a graph attention network, considering quality fluctuation, and generating a supplier global score. According to the invention, dynamic, precise and traceable evaluation is realized, a basis is provided for power grid supply chain management and the like, and the method is suitable for supplier evaluation in electric power and other industrial fields.
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