JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v9i6.13168ArticleIntelligent Agent Analysis and Measurement Application Based on DeepSeekhttps://artdesignp.com/journal/JERA/9/6/10.26689/jera.v9i6.13168GaoFengxi,SunMingze2025962025-12-16In the context of the integrated development of artificial intelligence and the power industry, the State Grid has carried out in-depth research on the research and development and application of the Guangming Power model. The model is based on the knowledge of the power industry, cognitive computing as the core, and knowledge service as the goal, and has the characteristics of large sample, large calculation, large parameters, large knowledge, and large tasks, providing important support for the intelligent transformation of the power industry. This study focuses on the efficient operation of Guangming Power large model, builds a trinity operation system of “model iterative optimization, sample full-process governance, and computing power resource collaboration”, and drives the continuous improvement of model capabilities and compliance development through a two-level collaboration mechanism. With the goal of “building a strong and excellent Bright Power Large Model”, the study clearly states that it is necessary to accelerate the construction of a two-level collaborative operation system, and promote model iterative optimization, capability evaluation, service monitoring and compliance review on a regular basis. At the same time, focusing on the whole process of R&D and application of large and small models, starting from four aspects: computing power planning and layout, allocation and scheduling, adaptation and optimization, monitoring and analysis, strengthening the application monitoring and analysis of two-level intelligent computing centers, and building an efficient computing power resource application and supply system to continuously improve its operation and service capabilities.

Liu W, Gan Z, Xi T, et al., 2022, A Semantic and Intelligent Focused Crawler based on Semantic Vector Space Model and Membrane Computing Optimization Algorithm. Applied Intelligence, 53(7): 7390–7407.

Yeh P, Puri C, Kass A, 2010, A Knowledge based Approach for Capturing Rich Semantic Representations from Text for Intelligent Systems. Int. J. of Advanced Intelligence Paradigms, 2(1): 33–48.

Andon P, Rogushina J, Grishanova I, et al., 2020, Experience of the Semantic Technologies Use for Intelligent Web Encyclopedia Creation (On Example of the Great Ukrainian Encyclopedia Portal). CEUR Workshop Proceedings, 2866(2020): 246–259.

Bai X, Wei G, Ye T, 2024, Analysis and Optimization Scheme of the Effectiveness of Word2vec in Intelligent Recommendation of Traditional Chinese Medicine Folk Prescriptions. Frontiers in Computing and Intelligent Systems, 10(3): 95–100.

Hadi E, Kishoro B, Rachita M, et al., 2023, Semantics Aware Intelligent Framework for Content-Based E-Learning Recommendation. Natural Language Processing Journal, 2023(3).

Kamaleddin Y, Ali F, 2022, An Approach for Semantic Interoperability in Autonomic Distributed Intelligent Systems. Journal of Software: Evolution and Process, 34(10).

Zhou H, Shen Y, Liu X, et al., 2020, Survey of Knowledge Graph Approaches and Applications. Journal on Artificial Intelligence, 2(2): 89–101.

Gong Y, Ma F, Wang H, et al., 2025, The Evolution of Research at the Intersection of Industrial Ecology and Artificial Intelligence. Journal of Industrial Ecology, 29(2): 440–457.

Haghighi M, Joseph A, Kapetanios G, et al., 2025, Machine Learning for Economic Policy. Journal of Econometrics, 2025(249): 105970.

Flores-Becerra G, Tlelo-Cuautle E, Polanco-Martagon S, 2009, Applying Fuzzy Sets Intersection in the Sizing of Voltage Followers. CEUR Workshop Proceedings, 2009(533): 209–216.

Schulze L, Douglas B, Raffo G, 2022, Fast Computation of Binary Search Tree for PWA Functions Representation using Intersection Classification. Automatica, 141(5): 110217.

Kishore D, George A, 2023, Empowering Novel Scholarship at the Intersection of Machine Learning/Deep Learning and Ecology. Ecological Informatics, 2023(77).

Mohammad H, Reza A, Hoda M, Hyperideal-Based Intersection Graphs. Indian Journal of Pure and Applied Mathematics, 54(1): 120–132.

Schwartmann R, Keber T, Zenner K, et al., 2024, Data Protection Aspects of the Use of Artificial Intelligence: Initial Overview of the Intersection between GDPR and AI Act. Computer Law Review International, 25(5): 145–150.