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Tobacco putting amount studying and judging method and system based on neural network

A neural network and neural network model technology, applied in the field of machine learning and data mining, can solve the problems that the accuracy and flexibility of cigarette brand placement need to be improved, and it is impossible to understand the feedback and effectiveness of the delivery amount, etc.

Pending Publication Date: 2020-11-27
INSPUR SOFTWARE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

According to the original cigarette launch mode, the accuracy and flexibility of some cigarette brands need to be improved. When the release of specific cigarettes is confirmed, it is impossible to understand the feedback and effectiveness of this launch in the market

Method used

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  • Tobacco putting amount studying and judging method and system based on neural network
  • Tobacco putting amount studying and judging method and system based on neural network
  • Tobacco putting amount studying and judging method and system based on neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] as attached figure 1 As shown, the neural network-based tobacco dosage research and judgment method of the present invention is to use the neural network model to build a cigarette dosage model, and according to the characteristics of the tobacco market, the characteristics of the cigarette are used as the reading index of the cigarette dosage model. The quantity model calculates the quantity of cigarettes that meet the requirements according to the training conditions, and provides customers with the simulated weekly delivery of cigarettes under different dosages, that is, provides the reference quantity of cigarettes for users under the condition that the cigarettes that users expect reach the full rate ;details as follows:

[0069] S1. Acquire the characteristic data of the cigarette; the details are as follows:

[0070] S101. The user needs to select the tobacco brand information that is expected to be simulated according to the actual needs, and obtain the number ...

Embodiment 2

[0089] as attached Figure 4 As shown, the neural network-based tobacco quantity research and judgment system of the present invention includes,

[0090] The data acquisition unit is used to acquire the characteristic data of the cigarette; the data acquisition unit includes,

[0091] The characteristic data acquisition module is used for the user to select the tobacco brand information that is expected to be simulated according to the actual needs, and obtain the number of users to be placed, the number of ordering households, the sufficient order quantity, the total amount of orders, the number of fully subscribed households, and the sufficient quantity to be ordered according to the tobacco brand information. data on the characteristics of the cigarettes ordered by the customer;

[0092] The screening module is used for the cigarette volume model to add the filter conditions of account manager, prefecture and city area and customer label to the characteristic data of cigar...

Embodiment 3

[0118] An embodiment of the present invention also provides an electronic device, including: a memory and at least one processor;

[0119] Wherein, the memory stores computer-executable instructions;

[0120] The at least one processor executes the computer-executed instructions stored in the memory, so that the at least one processor executes the neural network-based tobacco dosage research and judgment method in Embodiment 1.

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Abstract

The invention discloses a tobacco putting amount studying and judging method and system based on a neural network. The method belongs to the field of machine learning and data mining. The technical problem to be solved by the invention is how to obtain the feedback and effective situation of the cigarette putting amount in the current market. The cigarette putting amount is further adjusted; average effect, according to the technical scheme, the method comprises the steps that 1, the method comprises the following steps: constructing a cigarette putting amount model by using a neural network model; characteristics according to the tobacco market, the characteristics of the cigarettes serve as reading indexes of a cigarette putting amount model, the cigarette putting amount model calculatesthe cigarette putting amount meeting the requirements according to training conditions, and the simulated week putting conditions of the cigarettes under different putting amounts are provided for customers, that is, the reference putting amount of the cigarettes of the users is provided under the condition that the cigarettes expected by the users reach the sufficient rate; the method specifically comprises the following steps: S1, collecting characteristic data of cigarettes; s2, preprocessing the data of the related characteristics of the cigarette; s3, training a cigarette putting amountmodel; and S4, displaying and using a cigarette putting amount model result.

Description

technical field [0001] The invention relates to the fields of machine learning and data mining, in particular to a neural network-based method and system for researching and judging tobacco dosage. Background technique [0002] The original tobacco market mainly determines the amount of tobacco in the market by retailer stalls or tobacco price ranges. The original tobacco distribution mechanism lacks flexibility and has certain limitations, especially in cities with a relatively large gap between urban and rural areas, the disadvantages of the original distribution mechanism are more obvious. For example, retail customers in the township market in Heze area have relatively high levels of retail customers and high sales volume, but the actual demand for high-end cigarettes is relatively small. In contrast, retailers in the urban market have relatively low demand for mid-to-high-end cigarettes. larger. According to the original cigarette distribution model, the accuracy and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06Q50/04G06N3/08
CPCG06Q30/0607G06Q50/04G06N3/08Y02P90/30
Inventor 孔繁博耿云涛
Owner INSPUR SOFTWARE CO LTD
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