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Intelligent city environmental sanitation resource scheduling system based on sparse self-encoding and SVM

A sparse self-encoding and resource scheduling technology, applied in the field of smart city sanitation resource scheduling system, can solve problems such as difficult to meet, and achieve the effect of simple and efficient data dimension reduction and simple algorithm

Pending Publication Date: 2020-08-28
JIYUAN VOCATIONAL & TECHN COLLEGE
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Problems solved by technology

The traditional garbage removal mode is difficult to meet and suitable for urban development

Method used

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  • Intelligent city environmental sanitation resource scheduling system based on sparse self-encoding and SVM
  • Intelligent city environmental sanitation resource scheduling system based on sparse self-encoding and SVM
  • Intelligent city environmental sanitation resource scheduling system based on sparse self-encoding and SVM

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Embodiment Construction

[0038] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0039] The present invention proposes a smart city sanitation resource scheduling system based on sparse self-encoding and SVM, which can rationally schedule urban public resources according to urban cleaning information. Such as figure 1 is the system flow chart.

[0040] First, the server uses the urban monitoring system to collect street garbage information in various areas of the city; manually preprocesses and labels the training image information.

[0041] The method of preprocessing the image information is to convert the RGB color space model to YCrCb, and discard the Cr and Cb components and only keep the Y component. The conversion formula is:

[0042] Y=0.299R+0.587G+0.114B (1)

[0043] Cr=0.511R-0.428G-0.083B+128 (2)

[0044] Cb=-0.172R-0.339G+0.511B+128 (3)

[0045] Among them, R represents the RED component of the RGB model, G...

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Abstract

The invention relates to an intelligent city environmental sanitation resource scheduling system based on sparse self-coding and SVM. In order to meet the requirements of urban construction management, sparse self-coding is used for carrying out data dimension reduction on image information of main urban streets, and key features of images are extracted; and then the image features are sent to anSVM training recognition model, the cleaning conditions of all streets of the city are evaluated, and urban environmental sanitation resources are reasonably scheduled according to the evaluation result. The urban environmental sanitation information can be fully understood, urban environmental sanitation work can be carried out very favorably, Meanwhile, the urban environmental sanitation information can be used as a powerful basis for upper-layer decision making and is also an important basis for urban planning.

Description

technical field [0001] The invention relates to the field of artificial intelligence, and especially designs a smart city sanitation resource scheduling system based on sparse self-encoding and SVM. Background technique [0002] Urban environmental sanitation management is a task involving a wide range of areas, a large workload, and complicated matters. If we can fully understand the information of urban environmental sanitation, it will be very beneficial to the urban environmental sanitation work, and it will also serve as a powerful basis for upper-level decision-making. It is an important basis for urban planning. The traditional garbage removal mode is difficult to meet and suitable for urban development. At the same time, in order to meet the needs of urban construction management, it is of great practical significance to rationally optimize the collection and transportation system. [0003] In view of the above problems, the present invention uses a camera to colle...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04G06Q50/26G06K9/62G06N3/04
CPCG06Q10/06312G06Q10/04G06Q50/26G06N3/045G06F18/2411G06F18/214
Inventor 王亚利
Owner JIYUAN VOCATIONAL & TECHN COLLEGE
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