CN109033275B - Medicine area demand prediction method based on association map and neural network - Google Patents
Medicine area demand prediction method based on association map and neural network Download PDFInfo
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Abstract
The invention discloses a medicine area demand prediction method based on an association map and a neural network, which specifically comprises the following steps: s1, firstly, a sales information mining module and a sales information clustering module are respectively established between the sales data association atlas database and the system management module, then, people can interact with the system management module through the user interaction unit, and people can control the sales information mining module through the system management module to mine sales data information in the sales data association atlas database; relates to the technical field of medicine sales. The medicine regional demand prediction method based on the association graph and the neural network well realizes the purpose of predicting the future medicine sales condition of a local medicine sales region by utilizing the spatial information and the time information in the medicine sales data, achieves the purpose of grasping regional characteristics of medicine sales and obtaining a more accurate prediction result, and is favorable for the internet regional sales of medicines.
Description
Technical Field
The invention relates to the technical field of medicine sales, in particular to a medicine area demand prediction method based on an association map and a neural network.
Background
The medicine is characterized in that: it is used by people to prevent, treat and diagnose diseases of people, purposefully regulate the physiological function of people, and has specified application symptoms, usage and dosage requirements; in terms of using method: besides appearance, patients cannot recognize the inherent quality, many medicines need to be used under the guidance of doctors and are not selected and determined by the patients, meanwhile, the using method, the quantity, the time and other factors of the medicines greatly determine the using effect, and misuse cannot treat diseases and can cause diseases, and even endanger life safety. Therefore, the medicine is a special commodity, the specific variety of the medicine is about 20000 more than that of the world, more than 5000 Chinese medicinal preparations and more than 4000 western medicinal preparations in China, so that the medicine is complex in variety and various in variety, is not an independent commodity, is closely combined with the medicine and supplements each other, and the aims of preventing diseases and protecting health can be achieved only by checking and diagnosing by a doctor and reasonably using the medicine under the guidance of the doctor by a patient.
When the existing medicines are sold on the internet, the future sales condition of the medicines in a local medicine sales area can not be predicted by utilizing space information and time information in medicine sales data, the regional characteristics of medicine sales can not be grasped, and the purpose of obtaining a more accurate prediction result can not be achieved, so that great disadvantages are brought to the internet regional sales of the medicines.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a medicine regional demand prediction method based on an associated graph and a neural network, which solves the problems that the future sales condition of medicines in a local medicine sales region cannot be predicted by utilizing spatial information and time information in medicine sales data when the existing medicines are sold on the internet, the regional characteristic of medicine sales cannot be grasped, and a more accurate prediction result cannot be obtained, so that the great disadvantage is brought to the internet regional sales of the medicines.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: a medicine area demand prediction method based on an association map and a neural network specifically comprises the following steps:
s1, firstly, a sales information mining module and a sales information clustering module are respectively established between the sales data association atlas database and the system management module, then, people can interact with the system management module through the user interaction unit, and people can control the sales information mining module through the system management module to mine sales data information in the sales data association atlas database;
s2, the system management module can control the sales information clustering module to classify and store the sales data information mined in the S1 according to different geographic positions, then the area dividing unit integrates the sales information stored in the classification and concentration to create medicine sales area blocks in different geographic areas, and the different sales area blocks are integrated into sales area units in a distributed mode;
s3, a data information regression algorithm processing module is established between the system management module and the sales data association map library, a data transmission channel is established between the data information regression algorithm processing module and the sales region unit in S2, the data information regression algorithm processing module can retrieve and extract corresponding data information from the sales data association map library according to the data missing condition of each sales region block in the sales region unit, and the extracted data information is transmitted to the corresponding sales region block in the sales region unit for information completion;
s4, establishing a CNN-RNN neural network algorithm processing module between the system management module and the sales area unit, predicting future drug demands of corresponding sales area blocks in the sales area unit by using the CNN-RNN neural network algorithm, sending the predicted results to the system management module, and transmitting the predicted results to the user interaction unit by the system management module for display so as to be convenient for people to watch;
and S5, the system management module can control the printing module to print the predicted future medicine demand of the corresponding sales area block out of the prediction report through the peripheral printing equipment.
Preferably, the number of sales area blocks in the sales area unit corresponds to the number of geographical areas in the sales data association map library.
Preferably, the sales data association atlas database is a historical spatiotemporal data repository for drug sales.
(III) advantageous effects
The invention provides a medicine area demand prediction method based on an association map and a neural network. The method has the following beneficial effects: the medicine area demand prediction method based on the association map and the neural network specifically comprises the following steps: s1, firstly, respectively establishing a sales information mining module and a sales information clustering module between a sales data correlation atlas database and a system management module, S2, then the system management module can control the sales information clustering module to classify and store the sales data information mined in S1 according to different geographic positions, S3, then establishing a data information regression algorithm processing module between the system management module and the sales data correlation atlas database, S4, then establishing a CNN-RNN neural network algorithm processing module between the system management module and a sales region unit, S5, finally the system management module can control a printing module to print a predicted report of the predicted future medicine demand of the corresponding sales region block through an external printing device, thereby well realizing that the future medicine sales condition of the local medicine sales region is predicted by utilizing the space information and the time information in the medicine sales data, the method achieves the purpose of obtaining a more accurate prediction result by grasping regional characteristics of medicine sales, thereby being favorable for internet regional sales of medicines.
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FIG. 1 is a schematic block diagram of the architecture of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a technical solution: a medicine area demand prediction method based on an association map and a neural network specifically comprises the following steps:
s1, firstly, a sales information mining module and a sales information clustering module are respectively established between the sales data association atlas database and the system management module, then, people can interact with the system management module through the user interaction unit, and people can control the sales information mining module through the system management module to mine sales data information in the sales data association atlas database;
s2, the system management module can control the sales information clustering module to classify and store the sales data information mined in the S1 according to different geographic positions, then the area dividing unit integrates the sales information stored in the classification and concentration to create medicine sales area blocks in different geographic areas, and the different sales area blocks are integrated into sales area units in a distributed mode;
s3, a data information regression algorithm processing module is established between the system management module and the sales data association map library, a data transmission channel is established between the data information regression algorithm processing module and the sales region unit in S2, the data information regression algorithm processing module can retrieve and extract corresponding data information from the sales data association map library according to the data missing condition of each sales region block in the sales region unit, and the extracted data information is transmitted to the corresponding sales region block in the sales region unit for information completion;
s4, establishing a CNN-RNN neural network algorithm processing module between the system management module and the sales area unit, predicting future drug demands of corresponding sales area blocks in the sales area unit by using the CNN-RNN neural network algorithm, sending the predicted results to the system management module, and transmitting the predicted results to the user interaction unit by the system management module for display so as to be convenient for people to watch;
and S5, the system management module can control the printing module to print the predicted future medicine demand of the corresponding sales area block out of the prediction report through the peripheral printing equipment.
In the present invention, the number of sales area blocks in the sales area unit corresponds to the number of geographical areas in the sales data association map library.
In the invention, the sales data association atlas database is a historical time-space data storage library for medicine sales.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A medicine area demand prediction method based on an association map and a neural network is characterized by comprising the following steps: the method specifically comprises the following steps:
s1, firstly, a sales information mining module and a sales information clustering module are respectively established between the sales data association atlas database and the system management module, then, people can interact with the system management module through the user interaction unit, and people can control the sales information mining module through the system management module to mine sales data information in the sales data association atlas database;
s2, the system management module can control the sales information clustering module to classify and store the sales data information mined in the S1 according to different geographic positions, then the area dividing unit integrates the sales information stored in the classification and concentration to create medicine sales area blocks in different geographic areas, and the different sales area blocks are integrated into sales area units in a distributed mode;
s3, a data information regression algorithm processing module is established between the system management module and the sales data association map library, a data transmission channel is established between the data information regression algorithm processing module and the sales region unit in S2, the data information regression algorithm processing module can retrieve and extract corresponding data information from the sales data association map library according to the data missing condition of each sales region block in the sales region unit, and the extracted data information is transmitted to the corresponding sales region block in the sales region unit for information completion;
s4, establishing a CNN-RNN neural network algorithm processing module between the system management module and the sales area unit, predicting future drug demands of corresponding sales area blocks in the sales area unit by using the CNN-RNN neural network algorithm, sending the predicted results to the system management module, and transmitting the predicted results to the user interaction unit by the system management module for display so as to be convenient for people to watch;
and S5, the system management module can control the printing module to print the predicted future medicine demand of the corresponding sales area block out of the prediction report through the peripheral printing equipment.
2. The method for predicting the regional demand of drugs based on a correlation map and a neural network as claimed in claim 1, wherein: the number of sales area blocks in the sales area unit corresponds to the number of geographic areas in the sales data association map library.
3. The method for predicting the regional demand of drugs based on a correlation map and a neural network as claimed in claim 1, wherein: the sales data association atlas database is a historical spatiotemporal data storage library for medicine sales.
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| CN111428930A (en) * | 2020-03-24 | 2020-07-17 | 中电药明数据科技(成都)有限公司 | GBDT-based medicine patient using number prediction method and system |
| CN113344465B (en) * | 2021-07-13 | 2023-09-15 | 壹药网科技(上海)股份有限公司 | Prediction system for pharmacy operation |
| CN116051170A (en) * | 2023-01-28 | 2023-05-02 | 航天正通汇智(北京)科技股份有限公司 | Method and device for predicting regional usual medicine demand based on AI technology |
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