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Digital city prediction method and device, equipment and storage medium

A digital city and prediction method technology, applied in the field of neural networks, can solve the problems of high-dimensional data that cannot be effectively predicted and complex data, and achieve the effects of reducing complexity, high prediction accuracy, and reducing dimensions

Pending Publication Date: 2020-04-17
北京软通绿城科技有限公司
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The establishment of a digital twin city involves a huge amount of data. These data are very complex, not only in terms of the amount of data, but also in the multi-dimensionality of the data. The overall understanding of these data has far exceeded the ability of humans. High-dimensional data cannot be effectively predicted

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  • Digital city prediction method and device, equipment and storage medium
  • Digital city prediction method and device, equipment and storage medium
  • Digital city prediction method and device, equipment and storage medium

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Embodiment 1

[0025] figure 1 It is a flow chart of a digital city prediction method provided by Embodiment 1 of the present invention. This embodiment can be applied to the situation of predicting various aspects of a digital city. This method can be executed by a digital city prediction device. The device can be implemented by means of software and / or hardware, such as figure 1 As shown, the method specifically includes the following steps:

[0026] Step 110, acquiring the forecast items input by the user.

[0027] Wherein, the forecast items refer to the items that need to be forecasted by the digital city, such as water consumption forecast, electricity consumption forecast, total population forecast of a certain area of ​​the digital city, and type forecast of the digital city. The forecast item may be the name of the digital city forecast, including information such as forecast object and forecast range.

[0028] Specifically, the user can perform input through external devices suc...

Embodiment 2

[0049] figure 2It is a flow chart of a digital city prediction method provided by Embodiment 2 of the present invention. This embodiment is a further refinement and supplement to the previous embodiment. The digital city prediction method provided by this embodiment also includes: based on The Raida criterion, removing outliers from the model data; performing data encoding on the model data to convert non-numerical data in the model data into numerical data; encoding the data performing normalization processing; and performing dimensionality reduction on the model data based on a backpropagation neural network.

[0050] like figure 2 As shown, the method includes the following steps:

[0051] Step 210, acquiring the forecast items input by the user.

[0052] Step 220, determine the model data of the digital city by identifying the key information of the forecast item.

[0053] Step 230, determine the prediction model of the digital city according to the attributes of the...

Embodiment 3

[0084] image 3 It is a schematic diagram of a digital city prediction device provided in Embodiment 3 of the present invention, as shown in image 3 As shown, the device includes: a prediction item acquisition module 310 , a model determination module 320 and a city prediction module 330 .

[0085] Among them, the forecast item acquisition module 310 is used to acquire the forecast item input by the user; the model determination module 320 is used to acquire the model data of the digital city and determine the forecast model according to the forecast item; the city forecast module 330 is used to obtain the forecast item according to the Predictive models and model data are used to predict digital cities.

[0086] In the technical solution of the embodiment of the present invention, the forecasting items input by the user are used to determine the model data and forecasting model required for forecasting according to the forecasting items, which greatly reduces the dimension ...

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Abstract

The invention discloses a digital city prediction method and device, equipment and a storage medium. The digital city prediction method comprises the steps of obtaining a prediction item input by a user; obtaining model data of a digital city according to the prediction project and determining a prediction model; and predicting the digital city according to the prediction model and the model data.According to the technical scheme provided by the embodiment of the invention, the data and the model required by prediction are determined through the prediction project input by the user, and the digital prediction of the project is performed according to the model and the data, so that the accurate prediction of the huge data of the digital city is realized, and the prediction process is highin automation degree and high in prediction accuracy.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of neural networks, and in particular to a digital city prediction method, device, equipment and storage medium. Background technique [0002] In the process of establishing a digital twin city, it is generally necessary to collect data of real objects in real life through the Internet of Things or sensory network devices to form a simulation model. In the field of digital twins of smart cities, the data of twin targets are usually multi-dimensional data. For example, the building model: it includes the geographical information of the building, natural information, user information in the building, energy consumption information, etc. These different dimensions together constitute the multidimensional data model of the building. At the same time, when urban managers use digital twin cities for urban management, they must obtain prediction results after adding the influence of superv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06Q10/04
CPCG06Q10/04
Inventor 袁振杰雒冬梅郝瑞
Owner 北京软通绿城科技有限公司
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