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Fuzzy semantic reasoning-based optimization method of influence factors of heat consumption quantity of coking process

A technology of influencing factors and fuzzy semantics, applied in design optimization/simulation, electrical digital data processing, CAD numerical modeling, etc., can solve problems such as optimization of influencing factors of heat consumption and low heat consumption

Active Publication Date: 2018-08-24
YUNNAN NORMAL UNIV
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Problems solved by technology

[0006] The present invention provides a fuzzy semantic reasoning-based optimization method for heat consumption influencing factors in the coking process, which is used to solve the problem of optimizing the heat consumption influencing factors in the coking process, and realizes that the quality of the coke is guaranteed to be qualified and the heat consumption is low at the same time in the actual production process. Target

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  • Fuzzy semantic reasoning-based optimization method of influence factors of heat consumption quantity of coking process
  • Fuzzy semantic reasoning-based optimization method of influence factors of heat consumption quantity of coking process
  • Fuzzy semantic reasoning-based optimization method of influence factors of heat consumption quantity of coking process

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Embodiment 1

[0062] Embodiment 1: as Figure 1-2 As shown, the coking process heat consumption influencing factor optimization method based on fuzzy semantic reasoning, this embodiment takes 150 pieces of real generated data (samples) in the coking production process as an example, the specific steps of the optimization method are as follows:

[0063] Step1, sample data extraction and preprocessing;

[0064] Step1.1. Calculate the average value of heat consumption of 150 samples, and divide the samples into low heat consumption category C according to the average value 1 (less than average) and high heat consumption category C 2 (greater than or equal to the mean) two types of data, the number of samples is 80 and 70 respectively;

[0065] Step1.2. For each piece of data in the two categories, only 9 main attributes (factors) are retained from the original data, which are coking time, coal addition (single hole), coke oven gas main flow, and furnace temperature coefficient ( Uniform coe...

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Abstract

The invention relates to a fuzzy semantic reasoning-based optimization method of influence factors of heat consumption quantity of a coking process, and belongs to the technical fields of metallurgical intelligent control and metallurgical automation. According to the method, intrinsic fuzzy semantics are mined for the influence factors of the heat consumption quantity in the coking process according to axiomatic-fuzzy-set (AFS) theory, key simple semantics of all the influence factors are extracted through evaluation of the semantics and calculation of importance factors, and parameter rangesof the influence factors of the heat consumption quantity are set to complete optimization of the influence factors of the heat consumption quantity of the coking process. According to the method, the influence factors of the heat consumption quantity of the coking process are optimized, and a target of enabling the heat consumption quantity to be lower while coke qualification is ensured in an actual production process is achieved.

Description

technical field [0001] The invention relates to an optimization method for influencing factors of heat consumption in a coking process based on fuzzy semantic reasoning, and belongs to the technical fields of metallurgical intelligent control and metallurgical automation. Background technique [0002] With the development of computer technology and artificial intelligence, advanced management technologies such as fuzzy logic, artificial neural network, evolutionary calculation and its integrated intelligent model have been introduced into various production links in the metallurgical field, in order to realize metallurgical automation, intelligent management and control . As one of the important links in metallurgical production, the coking process includes multiple process links, each link will produce a number of technical parameters and data. Taking heat consumption as an example, in the actual production process, we hope to keep the heat consumption as low as possible w...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F2119/08G06F2111/10G06F30/20
Inventor 甘健侯周菊香唐晓宁文斌王俊邹伟
Owner YUNNAN NORMAL UNIV
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