Green construction decision-making method for railway tunnel in mountainous area based on CBR

By integrating a green construction decision-making system for mountain railway tunnels using a CBR-based approach, the problems of incomplete and untargeted data were solved, enabling efficient and accurate recommendations for green construction measures and improving the sustainability and economic benefits of construction.

CN120910119AActive Publication Date: 2025-11-07LANZHOU JIAOTONG UNIV
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Patent Information

Application Number
CN202511431542.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-09
Publication Date
2025-11-07
Estimated Expiration
2045-10-09

AI Technical Summary

Technical Problem

The decision-making on green construction measures for railway tunnel projects in mountainous areas lacks specificity, data is scattered and poorly managed, construction personnel rely on subjective experience, resulting in blind and inapplicable decisions, incomplete or vague data records in complex environments, and traditional methods cannot effectively utilize existing cases.

Method used

By adopting a case-based and CBR-based approach, an intelligent decision-making system is constructed by integrating scene attributes, evaluating ambiguity coefficients, generating virtual supplementary data, hybrid coding, and Siamese neural networks, thereby achieving effective utilization and accurate matching of incomplete data.

Benefits of technology

It improved the accuracy and applicability of green construction measures, reduced construction energy consumption and costs, avoided rework and environmental accidents, and enhanced the sustainability and economic benefits of construction.

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Abstract

The invention discloses a mountain railway tunnel green construction decision-making method based on CBR, and relates to the field of construction decision-making, and the method comprises the following steps: 1, integrating scene attribute systems of tunnel portal and tunnel shaft construction parts, obtaining case representations including construction scene attributes, attribute values and green construction measures, and generating a three-dimensional scene through Rhino software parameterization; 2, aiming at a case which is judged to be data fuzzy or missing due to special terrains or weather, based on a standard integrity case index, evaluating ambiguity coefficients of geological conditions, environment sensitive areas, construction machinery types, energy consumption indexes and material transportation path parameters in a case scene attribute system; a fuzzy data virtual filling mechanism is set, and the most similar data is searched from complete cases based on characteristic label matching for virtual replacement, so that data missing and fuzziness in a real scene are effectively dealt with, and the similarity between incomplete characteristic cases is accurately calculated instead of simply discarding the characteristic missing cases.
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