Greenhouse gas emission analysis method and system based on multi-mode intelligent agent

By constructing a multimodal intelligent agent collaborative architecture, the problems of reliance on manual operations and low information integration efficiency in existing greenhouse gas emission analysis methods are solved. It realizes automation, multi-source information integration and professional analysis report generation, and improves the logical coherence and completeness of the reports.

CN120892536AActive Publication Date: 2025-11-04ZHEJIANG UNIV
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Patent Information

Application Number
CN202511366675.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-24
Publication Date
2025-11-04
Estimated Expiration
2045-09-24

AI Technical Summary

Technical Problem

Existing greenhouse gas emission analysis methods suffer from several problems, including reliance on manual labor for generating structured reports, low standardization, limited output length, insufficient global planning capabilities, limited multimodal information processing capabilities, inadequate task decomposition and demand analysis capabilities, low efficiency in integrating multi-source information related to greenhouse gas emissions, and a lack of visualization and analysis capabilities.

Method used

A multimodal agent-based analysis method is adopted to construct a hybrid directed acyclic graph multi-agent collaborative architecture, including agents such as semantic parsing, knowledge retrieval, data visualization, image understanding, and content fusion. Greenhouse gas emission analysis reports are generated through hierarchical intent recognition and multi-source parallel retrieval. Combined with a dedicated knowledge base and multimodal data processing technology, the report is automatically generated and multi-source information is intelligently integrated.

Benefits of technology

It enables the structured and efficient generation of greenhouse gas emission analysis reports, improves the relevance and completeness of analysis results, solves the efficiency and quality problems of traditional methods, realizes the intelligent integration of multi-source information and professional multimodal analysis, and generates logically coherent and structurally complete professional analysis reports.

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Abstract

The invention discloses a greenhouse gas emission analysis method and system based on a multi-modal intelligent agent, and belongs to the field of greenhouse gas emission data analysis, large models and multiple intelligent agents. The method comprises the following steps: firstly, processing a report document, time sequence data and geographic space data, and constructing a special knowledge base and a standardized data set; then establishing a collaborative architecture containing six agents by using a hybrid directed acyclic graph, and supporting parallel processing of chapter tasks; and finally, generating a greenhouse gas emission analysis report according to natural language input of a user, and dynamically adjusting and iteratively optimizing according to modification opinions until requirements are met. According to the method, a problem source is automatically positioned based on a manual examination result, three types of structured parameters are optimized, the quality of the generated report is improved, intelligent and specialized generation of the greenhouse gas emission analysis report is realized, and the problems of long compiling period, insufficient speciality and difficult data integration of a traditional report are solved.
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