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A Demand Forecasting Method Combining Enterprise Productivity and Demand State

A forecasting method and productivity technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as data impact, achieve intuitive forecasting results, and maximize the satisfaction of target groups

Active Publication Date: 2021-08-06
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, the existing forecasts are all focused on finding the law of demand data, expecting to predict demand results with higher accuracy and smaller errors, but paying too much attention to the data itself but ignoring the impact of the status and type of each demand on the forecast results

Method used

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  • A Demand Forecasting Method Combining Enterprise Productivity and Demand State
  • A Demand Forecasting Method Combining Enterprise Productivity and Demand State
  • A Demand Forecasting Method Combining Enterprise Productivity and Demand State

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Embodiment Construction

[0093] The present invention will be further described below in conjunction with drawings and embodiments.

[0094] Embodiments of the present invention are as follows:

[0095] Injection molding machine is an indispensable manufacturing machine in social production. The following takes the injection molding machine company that produces injection molding machines as an example to predict the demand for injection molding machines.

[0096] 1. Establishment of questionnaire database for injection molding machines

[0097] Classify the functional requirements of the injection molding machine. The functional requirements of the injection molding machine can be divided into the following 8 functions, 1. The stability and reliability of machine work, 2. The degree of automation and production efficiency, 3. Energy saving and environmental protection, 4. Human-computer interaction and operability, 5. The difficulty of machine maintenance, 6. The weight and space of the injection m...

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Abstract

The invention discloses a demand forecasting method combining enterprise productivity and demand state. According to the demand characteristics of the target group, construct the demand information model of the target group, establish the demand questionnaire database; calculate the comprehensive adjustment coefficient of enterprise productivity; use the evaluation set under the demand questionnaire database to calculate the interaction matrix, and obtain the demand status matrix according to the comparison of the demand standard threshold, Use the historical data of the enterprise to calculate the state transition matrix, and then forecast to obtain the forecast demand state matrix, calculate the demand state adjustment coefficient matrix; calculate the preliminary demand importance, use the gray forecast method to calculate the demand importance of the next stage of direct prediction, and then combine the enterprise productivity The adjustment coefficient and the demand state adjustment coefficient are calculated to obtain the final demand importance of the target group. The present invention further processes the result of directly predicting the importance of demand to obtain the importance of demand combined with the status of the enterprise itself, which more intuitively reflects the importance of demand.

Description

technical field [0001] The invention relates to a demand forecasting method, in particular to a demand data forecasting method combining enterprise profitability and demand status. Background technique [0002] As a part of the development of future industrial intelligent manufacturing, demand forecasting has received extensive attention. The existing demand methods are mainly: investigate the needs of the target group, and distinguish the importance of different demand attributes, use the triangular fuzzy function to defuzzify the demand, and then use the product quality house to construct the demand-technology matrix to calculate the technical importance. Finally, use forecasting models such as autoregressive moving average model, gray forecasting, Markov chain, neural network, etc. to predict the importance of demand or technology, so as to provide directional guidance for the next stage of design. [0003] At present, the existing forecasts all focus on finding the law ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/04
CPCG06Q10/04G06Q50/04Y02P90/30
Inventor 张树有孙诗浩
Owner ZHEJIANG UNIV
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