1. The utility model provides an experiment lecture selection platform based on big data analysis which characterized in that, includes student end module, educational administration platform end, equipment end, practice lecture selection platform, network operation course module, wherein:

the student end module comprises a login module suitable for the login of a student account, and the student end module also comprises a secondary function interface;

the secondary function interface comprises a student course selection module suitable for course selection at student time, an experiment demand module suitable for the experiment release demand of students, an equipment reservation module suitable for inquiring available equipment and a course release module suitable for receiving course release information;

the teaching affair platform end comprises a teaching affair course selecting system, a data analysis module, a data management module, an experiment plan module and an equipment requirement releasing module, wherein the teaching affair course selecting system is suitable for receiving the information uploaded by students of the experiment requirement module, the data analysis module is suitable for processing the information uploaded by the students and generating course recommendation, the data management module is suitable for receiving the information of the data analysis module and matching the experiment teacher with the course requirement, the experiment plan module is suitable for making the experiment plan of the teacher and the course planning according to the information of the data management module, and the equipment requirement releasing module is suitable for integrating the experiment plan of the teacher and the equipment;

the equipment end comprises an equipment data module which is suitable for managing the state information of the existing equipment, and the equipment data module is suitable for receiving the integration information of the equipment demand release module;

the equipment end also comprises an equipment personnel login module suitable for equipment management personnel to log in, an equipment management module suitable for managing the equipment after the equipment management personnel logs in the module, an equipment maintenance module suitable for issuing maintenance information according to the equipment data module and a maintenance management module suitable for processing the equipment maintenance information;

the practice course selection platform is suitable for receiving the equipment state of the equipment end and transmitting the equipment state information to the educational administration course selection system;

the practice course selection platform is suitable for receiving the course planning information processed by the experiment planning module and transmitting the course planning information to the course publishing module and the equipment reservation module;

the network operation course module is suitable for being connected with the Internet and providing course recommendation information obtained by the data analysis module and query service of the existing courses.

2. The big data analysis-based experimental course selection platform as claimed in claim 1, wherein a deep neural network model is disposed in the data analysis module, and the deep neural network model is adapted to identify experimental course requirements and process the requirements into weighted information.

3. An experiment course selection platform based on big data analysis according to claim 2, wherein a big data algorithm is further arranged in the data analysis module, and the big data algorithm is adapted to introduce the weighted information into a big data analysis model to obtain an analysis report.

4. The big data analysis-based experimental course selection platform according to claim 3, wherein the big data algorithm is a fuzzy neural network algorithm.

5. The big data analysis-based experimental course selection platform and the using method thereof as claimed in claim 2, wherein the deep neural network model is a deep convolutional neural network architecture.

6. A use method of an experiment course selection platform based on big data analysis is characterized by comprising the following steps:

s1: after the students log in the login module, the students release experiment course requirement data through the experiment requirement module;

s2: the educational administration course selection system matches the experimental course demand data with the information of the experimental teacher and the equipment, and the step is S3 if the matching is passed, and the step is S1 if the matching is failed;

s3: the data analysis module imports the experimental course demand data into a deep neural network model, converts the experimental course demand data into a data analysis model, sets a characteristic matrix, takes a character string array of a corresponding characteristic vector as a sequence parameter, sets a support degree lower limit and a confidence degree lower limit of data mining, forms an analysis report, and sends the analysis report to the network operation course module and the data management module;

s4: the data management module utilizes a decision tree mechanism to reason the results to form an optimal recommendation result and sends the optimal recommendation result to the experiment plan module;

s5: the experimental plan module integrates the recommendation results, then makes an equipment utilization time table and sends the equipment utilization time table to the experimental equipment demand module;

s6: the experimental course selection platform arranges the equipment condition and the equipment utilization schedule into a course starting plan and sends the course starting plan to the course release module.

7. The use method of the big data analysis-based experiment course selection platform as claimed in claim 6, wherein the experiment course demand data is divided by fuzzy rules.

8. The use method of the big data analysis-based course selection platform according to claim 6, wherein the data mining support and confidence level is 92%.

Background

Big data analysis is one of the main application means of artificial intelligence technology, and has been applied to mainstream fields such as machinery, education, electricity and commerce, and experimental course selection is one of the important components of the teaching management process of colleges and universities, and is the key deployment direction of the construction of practice platforms. At present, the main flow of experiment course selection adopts a mode that a teacher self-sets an experiment course and students select again, so that the problems that the experiment course is disconnected from the post requirement, experiment equipment cannot be utilized to the maximum extent, the experiment course is not flexible, the experiment interest of students is not high and the like exist, the problems that the practice teaching is rigid, the learning interest of students is not high, innovative experiments are not really developed and the like are caused, and the requirement of the students cannot be met by the practice teaching.

Disclosure of Invention

The invention aims to: the experiment course selection platform based on big data analysis can improve the utilization rate of equipment.

The technical scheme adopted by the invention is as follows:

an experiment course selection platform based on big data analysis comprises a student end module, a educational administration platform end, an equipment end, a practice course selection platform and a network operation course module, wherein the student end module comprises a login module suitable for the login of a student account, and the student end module further comprises a secondary function interface; the secondary function interface comprises a student course selection module suitable for course selection at student time, an experiment demand module suitable for the experiment release demand of students, an equipment reservation module suitable for inquiring available equipment and a course release module suitable for receiving course release information; the teaching affair platform end comprises a teaching affair course selecting system, a data analysis module, a data management module, an experiment plan module and an equipment requirement releasing module, wherein the teaching affair course selecting system is suitable for receiving the information uploaded by students of the experiment requirement module, the data analysis module is suitable for processing the information uploaded by the students and generating course recommendation, the data management module is suitable for receiving the information of the data analysis module and matching the experiment teacher with the course requirement, the experiment plan module is suitable for making the experiment plan of the teacher and the course planning according to the information of the data management module, and the equipment requirement releasing module is suitable for integrating the experiment plan of the teacher and the equipment; the equipment end comprises an equipment data module which is suitable for managing the state information of the existing equipment, and the equipment data module is suitable for receiving the integration information of the equipment demand release module; the equipment end also comprises an equipment personnel login module suitable for equipment management personnel to log in, an equipment management module suitable for managing the equipment after the equipment management personnel logs in the module, an equipment maintenance module suitable for issuing maintenance information according to the equipment data module and a maintenance management module suitable for processing the equipment maintenance information; the practice course selection platform is suitable for receiving the equipment state of the equipment end and transmitting the equipment state information to the educational administration course selection system; the practice course selection platform is suitable for receiving the course planning information processed by the experiment planning module and transmitting the course planning information to the course publishing module and the equipment reservation module; the network operation course module is suitable for being connected with the Internet and providing course recommendation information obtained by the data analysis module and query service of the existing courses.

The student end module is mainly used for students to know teacher resources and equipment information, so that experimental demand information can be issued according to preferences of the students; the educational administration platform end recommends proper experimental courses for the experimental demand information issued by a large number of students mainly by planning teacher information, student end experimental demand information, equipment information and the like, and obtains the optimal planning arrangement for opening a lesson through big data calculation; the equipment end is used for managing the use and maintenance state of the equipment; the practice course selection platform is used for receiving and releasing a final course opening plan (sent to the course release module), transmitting the state of the existing equipment to the educational administration course selection system in real time and ensuring the reliability of the data obtained by the data analysis module; the network operation course module is used for connecting the Internet and providing course recommendation information obtained by the data analysis module and query service of the existing courses.

Preferably, a deep neural network model is arranged in the data analysis module, and the deep neural network model is suitable for identifying the requirements of the experimental courses and processing the requirements into weighting information.

Preferably, a big data algorithm is further arranged in the data analysis module, and the big data algorithm is suitable for introducing the weighting information into a big data analysis model to obtain an analysis report.

Preferably, the big data algorithm is a fuzzy neural network algorithm.

In addition, the invention also comprises a use method of the course selection platform, which specifically comprises the following steps:

s1: after the students log in the login module, the students release experiment course requirement data through the experiment requirement module;

s2: the educational administration course selection system matches the experimental course demand data with the information of the experimental teacher and the equipment, and the step is S3 if the matching is passed, and the step is S1 if the matching is failed;

s3: the data analysis module imports the experimental course demand data into a deep neural network model, converts the experimental course demand data into a data analysis model, sets a characteristic matrix, takes a character string array of a corresponding characteristic vector as a sequence parameter, sets a support degree lower limit and a confidence degree lower limit of data mining, forms an analysis report, and sends the analysis report to the network operation course module and the data management module;

s4: the data management module utilizes a decision tree mechanism to reason the results to form an optimal recommendation result and sends the optimal recommendation result to the experiment plan module;

s5: the experimental plan module integrates the recommendation results, then makes an equipment utilization time table and sends the equipment utilization time table to the experimental equipment demand module;

s6: the experimental course selection platform arranges the equipment condition and the equipment utilization schedule into a course starting plan and sends the course starting plan to the course release module.

Preferably, the experimental course requirement data is divided by adopting a fuzzy rule.

Preferably, the data mining support and confidence level is 92%.

In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:

compared with the prior art, the invention brings the requirements of students into the course selection process of the experiment by creating the experiment course selection platform and the method based on big data analysis, so that the students independently dominate the course selection process and recommend the corresponding latest experiment training network course, thereby realizing the independence and intellectualization of course selection of the students, avoiding the waste of teaching resources and improving the practice teaching quality.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a hardware schematic diagram of an experimental course selection platform for big data analysis provided by the present invention.

Fig. 2 is a flow chart of an experimental course selection method for big data analysis according to the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.

It is noted that 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. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

As shown in fig. 1, an experimental course selection platform based on big data analysis includes a student end module, a educational administration platform end, an equipment end, a practice course selection platform, and a network operation course module, where the student end module includes a login module suitable for student account login, and the student end module further includes a secondary function interface; the secondary function interface comprises a student course selection module suitable for course selection at student time, an experiment demand module suitable for the experiment release demand of students, an equipment reservation module suitable for inquiring available equipment and a course release module suitable for receiving course release information; the teaching affair platform end comprises a teaching affair course selecting system, a data analysis module, a data management module, an experiment plan module and an equipment requirement releasing module, wherein the teaching affair course selecting system is suitable for receiving the information uploaded by students of the experiment requirement module, the data analysis module is suitable for processing the information uploaded by the students and generating course recommendation, the data management module is suitable for receiving the information of the data analysis module and matching the experiment teacher with the course requirement, the experiment plan module is suitable for making the experiment plan of the teacher and the course planning according to the information of the data management module, and the equipment requirement releasing module is suitable for integrating the experiment plan of the teacher and the equipment; the equipment end comprises an equipment data module which is suitable for managing the state information of the existing equipment, and the equipment data module is suitable for receiving the integration information of the equipment demand release module; the equipment end also comprises an equipment personnel login module suitable for equipment management personnel to log in, an equipment management module suitable for managing the equipment after the equipment management personnel logs in the module, an equipment maintenance module suitable for issuing maintenance information according to the equipment data module and a maintenance management module suitable for processing the equipment maintenance information; the practice course selection platform is suitable for receiving the equipment state of the equipment end and transmitting the equipment state information to the educational administration course selection system; the practice course selection platform is suitable for receiving the course planning information processed by the experiment planning module and transmitting the course planning information to the course publishing module and the equipment reservation module; the network operation course module is suitable for being connected with the Internet and providing course recommendation information obtained by the data analysis module and query service of the existing courses; a deep neural network model is arranged in the data analysis module and is suitable for identifying the requirements of the experimental courses and processing the requirements into weighting information; a big data algorithm is also arranged in the data analysis module and is suitable for introducing the weighted information into a big data analysis model to obtain an analysis report; the big data algorithm is a fuzzy neural network algorithm.

As shown in fig. 2, the present invention further includes a method for using the above course selection platform, which specifically includes the following steps:

s1: after a student logs in the login module, releasing experiment course demand data through the experiment demand module, wherein the experiment course demand data are divided by adopting a fuzzy rule;

s2: the educational administration course selection system matches the experimental course demand data with the information of the experimental teacher and the equipment, and the step is S3 if the matching is passed, and the step is S1 if the matching is failed;

s3: the data analysis module imports the experimental course demand data into a deep neural network model, converts the data into a data analysis model, sets a characteristic matrix, takes a character string array of a corresponding characteristic vector as a sequence parameter, sets the support degree and the confidence degree of data mining to be 92%, forms an analysis report, and sends the analysis report to a network operation course module and a data management module;

s4: the data management module utilizes a decision tree mechanism to reason the results to form an optimal recommendation result and sends the optimal recommendation result to the experiment plan module;

s5: the experimental plan module integrates the recommendation results, then makes an equipment utilization time table and sends the equipment utilization time table to the experimental equipment demand module;

s6: the experimental course selection platform arranges the equipment condition and the equipment utilization schedule into a course starting plan and sends the course starting plan to the course release module.

According to the steps, the scheme can bring the requirements of the students into the course selection process of the experiment, so that the students independently lead the course selection process and recommend the corresponding latest experiment training network course, the independence and the intellectualization of course selection of the students are realized, the waste of teaching resources is avoided, and the practice teaching quality is improved.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.