Extension design dynamic classification method oriented to low-carbon product instance analysis

Abstract

The invention discloses an extension design dynamic classification method oriented to low-carbon product instance analysis. The method comprises the following steps: performing further dynamic classification on a low-carbon product on the basis of static product classification in order to mine a dynamic transformation rule of the product demand; establishing a product instance dynamic classification model based on low-carbon instance model transformation, wherein the product instance dynamic classification model is relevant to both instance type transformation and an attribute characteristic and a magnitude or only relevant to an attribute characteristic value; and constructing an instance field dynamic classification model based on low-carbon instance characteristic transformation, and meanwhile constructing an instance field dynamic classification model based on product instance characteristic parameter transformation, mainly including reduction in the full-life-circle cost caused by reduction transformation of the cost of the low-carbon product at a certain stage, reduction in the cost at another or certain other stages caused by transformation of the cost of the low-carbon product at a certain stage, reduction in the carbon footprint caused by transformation of the cost of the low-carbon product at a certain stage, and conduction transformation of the product performance and reduction in the carbon footprint at a certain stage caused by transformation of the cost of the low-carbon product at a certain stage.

Description

technical field [0001] The invention relates to the technical field of low-carbon design, in particular to an extension design dynamic classification method oriented to case analysis of low-carbon products. Background technique [0002] When the static classification results fail to meet the expected goals, for example, there are too many product instances in the positive domain, resulting in too many choices, making it difficult to make a decision, unable to match the required product instances or similar product instances, etc. In this process, through comparative analysis and retrieval of similar products, the understanding and understanding of similar product attributes, re-evaluation of the purpose and function of the product to be purchased, and professional explanations for the corresponding items of product demand, etc., will make a comprehensive analysis of product demand. Constant dynamic updates, i.e. {PR i}→{PR i '}→{PR i ”}=…, which makes it necessary to esta...

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Problems solved by technology

[0002] When the static classification results fail to meet the expected goals, for example, there are too many product instances in the positive domain, resulting in too many choices, making it difficult to make a decision, unable to match the required product instances or similar product instances, etc.

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