Dioxin soft measurement system based on selective ensemble and least squares support vector machine

A technology of support vector machine and least squares, which is applied in computer parts, special data processing applications, instruments, etc., and can solve problems such as self-adaptive selection of unsolved modeling parameters.

Active Publication Date: 2018-04-20
BEIJING UNIV OF TECH
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Problems solved by technology

The multi-layer LSSVM based on the optimization algorithm can optimize the selection of input features, sub-models and their weights [17], but it obviously has the inherent shortcomings of the heuristic optimization algorithm
None of the above SEN-LSSVM methods solves the problem of adaptive selection of modeling parameters

Method used

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  • Dioxin soft measurement system based on selective ensemble and least squares support vector machine
  • Dioxin soft measurement system based on selective ensemble and least squares support vector machine
  • Dioxin soft measurement system based on selective ensemble and least squares support vector machine

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Embodiment Construction

[0065] Municipal waste incineration is mainly composed of four parts: waste storage and transportation, furnace combustion, flue gas treatment, and steam turbine power generation. The MSWI process flow based on the grate furnace is as follows: figure 1 shown.

[0066] Domestic garbage is collected by a special garbage transport vehicle and transported to the unloading workshop, where it is dumped into a sealed garbage pool; the garbage in the pool is automatically picked up by a manually controlled hydraulic grab bucket and put into the feed hopper of the incinerator, and the hydraulic feeder feeds the bucket The garbage inside is pushed to the reciprocating mechanical grate furnace; the garbage goes through four stages of drying, igniting, burning and burning in the incinerator in sequence, in which: the burned garbage residues fall into the water-cooled slag hopper, and then are discharged by the slag conveyor Push it into the slag pool, collect it and send it to the landfi...

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Abstract

The invention discloses a dioxin soft measurement system based on a selective ensemble and least squares support vector machine. First, a candidate kernel parameter set having the number of K and a candidate penalty parameter set having the number of R are given based on prior knowledge; second, an LSSVM (least squares support vector machine) algorithm is used to construct a candidate sub-model set having the number of K*R based on these candidate kernel parameters and candidate penalty parameters; third, an SEN(BBSEN-AWF) algorithm based on BB (brand and bound) and AWF (adaptive weighted fusion) is used to select and merge candidate sub-models having same kernel parameter and different penalty parameters so as to obtain a candidate SEN sub-model set having the number K; fourth, subjectingthe candidate SEN sub-model set having the number of K to the BBSEN-AWF algorithm again so as to obtain an SEN-LSSVM DXN (dioxin) soft measurement model.

Description

technical field [0001] The invention belongs to the technical field of solid waste treatment, and in particular relates to a dioxin soft measurement system based on a selectively integrated least squares support vector machine. Background technique [0002] Municipal solid waste incineration (MSWI) has become the main means of dealing with combustible waste in most cities at home and abroad. The incineration process produces pollutants such as polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), which are commonly known as dioxins (hereinafter referred to as DXN)[1]. DXN is currently known as a highly toxic persistent pollutant. At present, it is difficult to optimize the operation of most MSWI processes to reduce the emission concentration of dioxins. One of the most important reasons is that DXN is difficult to detect online in real time[2,3]. The complex physical and chemical properties inherent in the MSWI process make it difficult to estab...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62
CPCG06F30/20G06F18/2411
Inventor 汤健乔俊飞韩红桂李晓理
Owner BEIJING UNIV OF TECH
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