Integrated intelligent electronic scale

Abstract

The invention discloses an integrated intelligent electronic scale, relates to the field of commodity acceptance management, and aims to improve the accuracy of acceptance record data of the electronic scale by adjusting from the angle of parameters of the electronic scale. Then, the number of nodes of each task of an electronic scale acceptance data integration cluster for managing the multiple electronic scales is adjusted from the aspect of the integration efficiency of the acceptance record data of the multiple electronic scales, so that the integration delay of the acceptance data is lower, and the integration efficiency of the acceptance record data of the multiple electronic scales is improved; the method comprises the following steps: collecting record data during historical acceptance of an electronic scale, calculating an error between the record data and actual data, establishing a mapping model between the acceptance data record error and parameters of the electronic scale, and providing a mapping model for judging whether the parameter setting of the current electronic scale is reasonable or not subsequently; and iteratively optimizing the parameters of the current electronic scale according to the mapping model, so that the current electronic scale is more accurate when recording acceptance data.

Description

Technical Field

[0001] The present invention belongs to the field of commodity acceptance management, and in particular, relates to an integrated intelligent electronic scale. Background Art

[0002] The parameters of existing electronic scales include the size of the scale value, the smallest unit displayed by the electronic scale, the number of decimal places of the value displayed by the electronic scale, the maximum weighing range of the electronic scale, etc. These parameters are often pre-set by people based on past experience. However, the manual setting is subjective and may lead to inaccurate data recorded during commodity acceptance, which in turn brings inconvenience or even misleading to the subsequent process of tracing the commodities. In addition, more than one electronic scale is used for commodity acceptance, which results in the data recorded by each electronic scale being relatively scattered, making it difficult to uniformly manage and analyze. Summary of the invention

[0003] In view of the problems in the related art, the present invention proposes an integrated intelligent electronic scale to overcome the above technical problems existing in the existing related art.

[0004] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0005] The present invention is an integrated intelligent electronic scale, comprising a weighing plate, a display screen, a support plate, an acceptance information type setting module, an electronic scale parameter type setting module, a historical acceptance data acquisition module, a record error mapping model construction module, a current electronic scale error mapping module, a current electronic scale parameter adjustment module, an acceptance data integration cluster construction module, and a cluster task node number optimization module;

[0006] S1, the acceptance information type setting module is used to set multiple information data types recorded by the electronic scale during the canteen acceptance process to obtain a record information type set;

[0007] The electronic scale parameter type setting module is used to set multiple parameter types of the electronic scale to obtain an electronic scale parameter type set;

[0008] The historical acceptance data collection module is used to collect acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history according to the record information type set and the electronic scale parameter type set, and obtain the historical record information data matrix, the historical standard information data matrix and the historical electronic scale parameter data matrix;

[0009] S2, the record error mapping model construction module is used to construct the acceptance information record error mapping model according to the historical record information data matrix, the historical standard information data matrix and the historical electronic scale parameter data matrix;

[0010] S3, the current electronic scale error mapping module is used to map the parameter data of multiple current electronic scales using the acceptance information record error mapping model to obtain an initial acceptance record error mapping data set;

[0011] The current electronic scale parameter adjustment module is used to adjust the parameter data of multiple current electronic scales according to the initial acceptance record error mapping data set to obtain the final parameter data matrix of the current electronic scale;

[0012] S4, the acceptance data integration cluster building module is used to cooperate with the current electronic scale final parameter data matrix and multiple current electronic scales to build an electronic scale acceptance data integration cluster;

[0013] S5, the cluster task node number optimization module is used to collect the acceptance information records of each current final electronic scale and the time difference when the total number of integrated acceptance information records reaches the number of acceptance data, and optimize the number of task nodes in the electronic scale acceptance data integration cluster according to the time difference to obtain the final node number data matrix of the acceptance data integration cluster task;

[0014] By collecting the historical acceptance record data of the electronic scale and calculating the error between the recorded data and the actual data, a mapping model between the acceptance data recording error and the parameters of the electronic scale is established; the parameters of the current electronic scale are iteratively optimized according to the mapping model, so that the current electronic scale is more accurate in recording the acceptance data; when the parameters of the currently used electronic scale are adjusted, a cluster is built to manage the integration of the acceptance record data of each electronic scale, and the number of each task node in the cluster is optimized according to the difference between the integration completion time and the acceptance record completion time, so that the delay of acceptance data integration is lower and the integration efficiency is improved.

[0015] Preferably, the S1 comprises the following steps:

[0016] S11, set multiple information data types recorded by the electronic scale during the canteen acceptance process, and obtain the recorded information type set a 1 ={a 11 ,...,a 1i ,...,a 1a1 ′},a 1i Indicates the i-th type of information data recorded by the electronic scale during the canteen acceptance process, a′ 1 Indicates the total number of information data types set; then set multiple parameter types of the electronic scale to obtain the electronic scale parameter type set a 2i Indicates the i-th parameter type of the electronic scale set, a′ 2 Indicates the total number of electronic scale parameter types that are set;

[0017] S12, collecting acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history according to the record information type set and the electronic scale parameter type set to obtain a historical record information data matrix , Historical Standard Information Data Matrix And the historical electronic scale parameter data matrix ; They are as follows,

[0018]

[0019] in, They respectively represent the j-th type of acceptance record information data of the i-th group of historical electronic scales, the corresponding standard information data, and the j-th type of parameter data of the electronic scales, Indicates the total number of groups of historical electronic scale acceptance record information data, corresponding standard information data and parameter data collected;

[0020] The types of recorded information include the weight of ingredients, the quantity of ingredients, and the specifications of ingredients, such as size, length, diameter, etc.; delivery time, information about the personnel who record the acceptance of ingredients, settlement-related documents, photos and videos of ingredients, etc.; the types of electronic scale parameters include the initial zero point, the time it takes for the electronic scale to stabilize after weighing, the size of the minimum scale value, the minimum unit displayed by the electronic scale, the number of decimal places of the value displayed by the electronic scale, the maximum weighing range of the electronic scale, the range of zero point tracking of the electronic scale, the backlight brightness and duration of the electronic scale display; baud rate, which refers to the data transmission rate when the electronic scale communicates with other devices, etc.

[0021] By collecting the acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history, data support is provided for the subsequent construction of the acceptance information record error mapping model.

[0022] Preferably, S2 comprises the following steps:

[0023] S21, according to the historical record information data matrix and the historical standard information data matrix, calculate the error data between each acceptance record information data of the electronic scale in history and the standard information data, and obtain the historical record information error data set It represents the error data between the acceptance record information data of each electronic scale in the history of the i-th group and the standard information data; the calculation formula is as follows:

[0024]

[0025] S22, constructing an acceptance information record error mapping model according to the historical record information error data set and the historical electronic scale parameter data matrix;

[0026] By calculating the error data between the acceptance record information data of each electronic scale in history and the standard information data, label data is provided for the subsequent construction of the acceptance information record error mapping model; by constructing the acceptance information record error mapping model, a mapping model is provided for the subsequent determination of whether the parameter settings of the current electronic scale are reasonable, and a determination result mapping method is also provided for the determination of the results of adjusting the parameters of the current electronic scale.

[0027] Preferably, S3 comprises the following steps:

[0028] S31, set a plurality of electronic scales currently in use to obtain a current initial electronic scale set; collect parameter data of each electronic scale in the current initial electronic scale set according to the electronic scale parameter type set, and obtain the current electronic scale initial parameter data matrix b 1 ;as follows,

[0029]

[0030] Among them, b 1ij represents the initial parameter data of the jth type of the i-th electronic scale currently in use, and b′ represents the total number of electronic scales currently in use;

[0031] S32, inputting each row of data in the current electronic scale initial parameter data matrix into the acceptance information record error mapping model for mapping, and obtaining an initial acceptance record error mapping data set Indicates that the i-th row data in the current electronic scale initial parameter data matrix is ​​input into the acceptance information record error mapping model for mapping to obtain the initial acceptance record error mapping data;

[0032] S33, setting an acceptance record error threshold; when there is initial acceptance record error mapping data in the initial acceptance record error mapping data set that is greater than or equal to the acceptance record error threshold, adjusting the initial parameter data of the electronic scale corresponding to the initial acceptance record error mapping data to obtain an adjusted parameter data set; and then using the adjusted parameter data set to replace the corresponding initial parameter data in the initial parameter data matrix of the current electronic scale to obtain the final parameter data matrix b of the current electronic scale 2 ;as follows,

[0033]

[0034] Among them, b 2ij Indicates the final parameter data of the jth type of the i-th electronic scale currently being used;

[0035] By inputting the current electronic scale initial parameter data into the acceptance information record error mapping model for mapping, the corresponding acceptance record error data is obtained, which provides a basis for subsequent determination of whether the electronic scale parameters need to be adjusted; by setting the acceptance record error threshold, a quantitative determination standard is provided for determining whether the electronic scale parameters meet the requirements.

[0036] Preferably, S4 comprises the following steps:

[0037] S41, using the current electronic scale final parameter data matrix to set the parameters of each current initial electronic scale in the current initial electronic scale set; after the parameter setting is completed, the current final electronic scale set is obtained;

[0038] S42, setting acceptance data integration electronic scales; constructing an electronic scale acceptance data integration cluster, setting the number of task nodes for acceptance data recording, the number of acceptance data transmission task nodes, and the number of acceptance data integration task nodes for each current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster, and obtaining the data matrix of the initial node number of the acceptance data integration cluster task ;as follows,

[0039]

[0040] in, represents the number of initial task nodes for setting acceptance data records for the i-th current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster, Respectively represent the number of initial task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster;

[0041] The acceptance data integration electronic scale is used to integrate the acceptance record data on each current final electronic scale in the current final electronic scale set, so as to facilitate unified management of the data;

[0042] This solution integrates the electronic scale acceptance data cluster based on adjusting the parameters of each current electronic scale, and is used to automatically integrate the acceptance record data of each electronic scale into a main electronic scale to facilitate unified management of the acceptance data.

[0043] Preferably, S5 comprises the following steps:

[0044] S51, set the number of acceptance data; count the time data when the total number of acceptance information records of each current final electronic scale in the current final electronic scale reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and obtain the acceptance end time data e 1 And the initial time data of the integration end2 ;

[0045] S52, setting acceptance integration delay error threshold e'; when e 2 -e 1 ≥e′, the data matrix of the initial node number of the acceptance data integration cluster task is adjusted until e 2 -e 1 <e′, the final node number data matrix of the acceptance data integration cluster task is obtained; otherwise, there is no need to adjust the initial node number data matrix of the acceptance data integration cluster task, and the initial node number data matrix of the acceptance data integration cluster task is used as the final node number data matrix of the acceptance data integration cluster task;

[0046] S53, setting the task node data of the electronic scale acceptance data integration cluster according to the final node number data matrix of the acceptance data integration cluster task;

[0047] By setting the acceptance integration delay error threshold, a quantitative judgment standard is provided for determining whether the delay data of the acceptance data integration under the management of the electronic scale acceptance data integration cluster before the number of task nodes is adjusted meets the requirements.

[0048] Preferably, the step of adjusting the initial node number data matrix of the acceptance data integration cluster task in S52 includes the following steps:

[0049] S521, build acceptance integration node to adjust the sooty tern population c 2i Indicates that the acceptance integration node adjusts the i-th sooty tern in the sooty tern population, c′ 2 Indicates that the acceptance integration node adjusts the scale of the black tern population; Sets the maximum number of iterations of the acceptance integration node to adjust the black tern population And the current number of iterations is , respectively recorded as the maximum number of iterations adjusted by the acceptance integration node and the current number of iterations adjusted by the acceptance integration node; the search space dimension of the sooty tern population adjusted by the acceptance integration node is b′+2;

[0050] S522, setting the value interval of each task's initial node number data in the acceptance data integration cluster task initial node number data matrix, and obtaining a node number value interval matrix ;as follows,

[0051]

[0052] in, respectively represent the lower limit and the upper limit of the number of task nodes for setting acceptance data records for the i-th current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster; Respectively represent the lower limit and the upper limit of the number of task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster;

[0053] According to the node number value interval matrix, the acceptance integration node is set to adjust the initial position matrix of each sooty tern in the sooty tern population, and the second initial position matrix set is obtained. d 2j It indicates that the acceptance integration node adjusts the initial position matrix of the j-th sooty tern in the sooty tern population; as follows,

[0054]

[0055] Among them, d 2j1i Indicates d 2j The position component in the dimension of the number of task nodes for setting acceptance data records for the i-th current final electronic scale in the electronic scale acceptance data integration cluster; d 2j21 d 2j22 Respectively represent d 2j The position component in the dimension of the number of task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster; d 2j1i d 2j21 d 2j22 The calculation formulas are as follows:

[0056]

[0057] In the formula, rand 2j1i 、rand 2j21 、rand 2j22 Respectively for d 2j1i d 2j21 d 2j22 A random number generated between 0 and 1; ceil represents the rounding function;

[0058] S523, according to the initial time data e of the integration end 2 Constructing the fitness function of the electronic scale acceptance data integration cluster ;as follows,

[0059]

[0060] S524, start iteration, before iteration, adjust the current iteration number of the acceptance integration node to 1; in the first round of iteration, use the acceptance integration node to adjust the fitness function of the sooty tern population Calculate the fitness value of the initial position matrix of each sooty tern in the second initial position matrix set to obtain a third fitness value set; use the maximum fitness in the third fitness value set and the corresponding initial position matrix of the sooty tern as the third global optimal fitness and the third global optimal position respectively; update the initial position matrix of each sooty tern in the second initial position matrix set according to the third global optimal fitness and the third global optimal position; after the update is completed, adjust the current iteration number of the acceptance integration node by 1 and enter the next round of iteration;

[0061] In each other iteration process, the acceptance integration node is used to adjust the fitness function of the sooty tern population. Calculate the fitness value of the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous iteration process to obtain a fourth fitness value set; use the maximum fitness in the fourth fitness value set and the corresponding sooty tern position matrix as the fourth global optimal fitness and the fourth global optimal position respectively; update the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous iteration process according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, add 1 to the current iteration number of the acceptance integration node adjustment and enter the next iteration;

[0062] S525, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until The second final global optimal position is used as the data matrix of the number of nodes after the optimization of the acceptance data integration cluster task; the electronic scale acceptance data integration cluster is set according to the data matrix of the number of nodes after the optimization of the acceptance data integration cluster task; after the setting is completed, the total number of acceptance information records of each current final electronic scale in the current final electronic scale set reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and the optimized acceptance terminal time data e is obtained. 3 And the time data after integration optimization 4 ;

[0063] When e 4 -e 3 <e′, the node number data matrix after the optimization of the acceptance data integration cluster task is used as the final node number data matrix of the acceptance data integration cluster task; otherwise, return to S524 and continue to iterate until e 4 -e3 Until <e′;

[0064] The number of each task node in the electronic scale acceptance data integration cluster is iteratively adjusted multiple times by using the Sooty Tern optimization algorithm, and the electronic scale acceptance data integration cluster is set using the number of each task node obtained by each round of iterative update. After the setting is completed, the acceptance integration delay data in the current electronic scale acceptance data integration cluster is used as the fitness function; therefore, with the progress of iterations, the acceptance integration delay data in the electronic scale acceptance data integration cluster becomes smaller and smaller, and finally meets the requirements.

[0065] The present invention has the following beneficial effects:

[0066] 1. In the present invention, adjustments are first made from the perspective of the parameters of the electronic scale to improve the accuracy of the acceptance record data of the electronic scale; then, from the perspective of the integration efficiency of the acceptance record data of multiple electronic scales, the number of nodes of each task of the electronic scale acceptance data integration cluster that manages multiple electronic scales is adjusted, so that the delay of acceptance data integration is lower, and the integration efficiency of acceptance record data of multiple electronic scales is improved; by collecting the record data of the historical acceptance of the electronic scale and calculating the error between the record data and the actual data, a mapping model between the acceptance data record error and the parameters of the electronic scale is established; according to the mapping model, the parameters of the current electronic scale are iteratively optimized, so that the current electronic scale is more accurate in recording the acceptance data.

[0067] 2. In the present invention, by constructing an acceptance information recording error mapping model, a mapping model is provided for the subsequent determination of whether the parameter settings of the current electronic scale are reasonable.

[0068] 3. In the present invention, the number of each task node in the electronic scale acceptance data integration cluster is iteratively adjusted multiple times by using the Sooty Tern optimization algorithm, and the electronic scale acceptance data integration cluster is set using the number of each task node obtained by each round of iterative update. After the setting is completed, the acceptance integration delay data in the current electronic scale acceptance data integration cluster is used as the fitness function; therefore, as the iteration proceeds, the acceptance integration delay data in the electronic scale acceptance data integration cluster becomes smaller and smaller, and finally meets the requirements.

[0069] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0071] Figure 1 A schematic diagram of a flow chart of a method for commodity acceptance using an integrated intelligent electronic scale according to the present invention;

[0072] Figure 2 The figure is a three-dimensional structural schematic diagram of an integrated intelligent electronic scale of the present invention.

[0073] In the figure:

[0074] 1. Scale plate; 2. Display screen; 3. Support plate. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the invention to clearly and completely describe the technical solutions in the embodiments of the invention. Obviously, the described embodiments are only part of the embodiments of the invention, not all of the embodiments. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the invention.

[0076] See also Figure 1 and Figure 2 , this embodiment is an integrated intelligent electronic scale, including a weighing plate 1, a display screen 2, a support plate 3, an acceptance information type setting module, an electronic scale parameter type setting module, a historical acceptance data acquisition module, a record error mapping model construction module, a current electronic scale error mapping module, a current electronic scale parameter adjustment module, an acceptance data integration cluster construction module, and a cluster task node number optimization module;

[0077] S1, the acceptance information type setting module is used to set multiple information data types recorded by the electronic scale during the canteen acceptance process to obtain a record information type set;

[0078] The electronic scale parameter type setting module is used to set multiple parameter types of the electronic scale to obtain an electronic scale parameter type set;

[0079] The historical acceptance data collection module is used to collect acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history according to the record information type set and the electronic scale parameter type set, and obtain the historical record information data matrix, the historical standard information data matrix and the historical electronic scale parameter data matrix;

[0080] The S1 comprises the following steps:

[0081] S11, set multiple information data types recorded by the electronic scale during the canteen acceptance process, and obtain the recorded information type set a 1 ={a 11 ,...,a 1i ,...,a 1a1 ′},a1i Indicates the i-th type of information data recorded by the electronic scale during the canteen acceptance process, a 1 ′ represents the total number of information data types set; then set multiple parameter types of the electronic scale to obtain the electronic scale parameter type set , a 2i Indicates the i-th parameter type of the electronic scale set, a′ 2 Indicates the total number of electronic scale parameter types that are set;

[0082] S12, collecting acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history according to the record information type set and the electronic scale parameter type set to obtain a historical record information data matrix , Historical Standard Information Data Matrix And the historical electronic scale parameter data matrix ; They are as follows,

[0083]

[0084] in, They respectively represent the j-th type of acceptance record information data of the i-th group of historical electronic scales, the corresponding standard information data, and the j-th type of parameter data of the electronic scales, Indicates the total number of groups of historical electronic scale acceptance record information data, corresponding standard information data and parameter data collected;

[0085] S2, the record error mapping model construction module is used to construct the acceptance information record error mapping model according to the historical record information data matrix, the historical standard information data matrix and the historical electronic scale parameter data matrix;

[0086] The S2 comprises the following steps:

[0087] S21, according to the historical record information data matrix and the historical standard information data matrix, calculate the error data between each acceptance record information data of the electronic scale in history and the standard information data, and obtain the historical record information error data set It represents the error data between the acceptance record information data of each electronic scale in the history of the i-th group and the standard information data; the calculation formula is as follows:

[0088]

[0089] S22, constructing an acceptance information record error mapping model according to the historical record information error data set and the historical electronic scale parameter data matrix;

[0090] The S22 comprises the following steps:

[0091] S221, constructing an initial SVM model and setting a training data ratio; dividing the historical record information error data set and the historical electronic scale parameter data matrix according to the training data ratio to obtain a historical record information error training data set, a historical electronic scale parameter training data matrix, a historical record information error test data set, and a historical electronic scale parameter test data matrix;

[0092] S222, setting a training error threshold; inputting the historical record information error training data set and the historical electronic scale parameter training data matrix as training data and training label data respectively into the initial SVM model for training operation; during the training process, when the training error is less than the training error threshold, stopping the training to obtain a trained SVM model; otherwise, continuing the training until the training error is less than the training error threshold;

[0093] S223, set a test accuracy threshold; input the historical record information error test data set and the historical electronic scale parameter test data matrix as test data and test label data respectively into the trained SVM model for testing; after the test is completed, obtain the test accuracy data; when the test accuracy data is greater than or equal to the test accuracy threshold, use the trained SVM model as the acceptance information record error mapping model; otherwise, return to S222 to continue training the trained SVM model until the test accuracy data is greater than or equal to the test accuracy threshold;

[0094] S3, the current electronic scale error mapping module is used to map the parameter data of multiple current electronic scales using the acceptance information record error mapping model to obtain an initial acceptance record error mapping data set;

[0095] The current electronic scale parameter adjustment module is used to adjust the parameter data of multiple current electronic scales according to the initial acceptance record error mapping data set to obtain the final parameter data matrix of the current electronic scale;

[0096] The S3 comprises the following steps:

[0097] S31, set a plurality of electronic scales currently in use to obtain a current initial electronic scale set; collect parameter data of each electronic scale in the current initial electronic scale set according to the electronic scale parameter type set, and obtain the current electronic scale initial parameter data matrix b 1 ;as follows,

[0098]

[0099] Among them, b 1ijrepresents the initial parameter data of the jth type of the i-th electronic scale currently in use, and b′ represents the total number of electronic scales currently in use;

[0100] S32, inputting each row of data in the current electronic scale initial parameter data matrix into the acceptance information record error mapping model for mapping, and obtaining an initial acceptance record error mapping data set Indicates that the i-th row data in the current electronic scale initial parameter data matrix is ​​input into the acceptance information record error mapping model for mapping to obtain the initial acceptance record error mapping data;

[0101] S33, setting an acceptance record error threshold; when there is initial acceptance record error mapping data in the initial acceptance record error mapping data set that is greater than or equal to the acceptance record error threshold, adjusting the initial parameter data of the electronic scale corresponding to the initial acceptance record error mapping data to obtain an adjusted parameter data set; and then using the adjusted parameter data set to replace the corresponding initial parameter data in the initial parameter data matrix of the current electronic scale to obtain the final parameter data matrix b of the current electronic scale 2 ;as follows,

[0102]

[0103] Among them, b 2ij Indicates the final parameter data of the jth type of the i-th electronic scale currently being used;

[0104] In S33, the initial parameter data of the electronic scale corresponding to the initial acceptance record error mapping data is adjusted to obtain the adjusted parameter data set, which includes the following steps:

[0105] S331, setting the parameter data set of the electronic scale to be adjusted to Indicates the parameter data of the i-th type of electronic scale that needs to be adjusted; recorded as the parameter data set to be adjusted;

[0106] S332, construct electronic scale parameters to adjust the population of sooty terns 1 ={c 11 ,...,c 1i ,...,c 1c1 ′},c 1i Indicates that the electronic scale parameter adjusts the i-th sooty tern in the sooty tern population, c 1 ' represents the electronic scale parameter to adjust the size of the black tern population; the maximum number of iterations of the electronic scale parameter to adjust the black tern population is set to And the current number of iterations is , respectively recorded as the maximum number of iterations of parameter adjustment and the current number of iterations of parameter adjustment; the search space dimension of the electronic scale parameter adjustment of the sooty tern population is a′ 2 ;

[0107] S333: Set the value interval of each parameter data to be adjusted in the parameter data set to be adjusted to obtain the parameter value interval set to be adjusted. respectively represent the lower limit and the upper limit of the value of the i-th parameter data to be adjusted in the parameter data set to be adjusted;

[0108] The electronic scale parameters are set according to the parameter value interval set to be adjusted to adjust the initial position of each sooty tern in the sooty tern population, and a first initial position matrix d is obtained. 1 ;as follows,

[0109]

[0110] Among them, d 1ji It represents the component of the initial position of the j-th sooty tern in the sooty tern population adjusted by the electronic scale parameter on the parameter data dimension of the i-th type of the electronic scale; the calculation formula is as follows:

[0111]

[0112] Among them, rand 1ji Indicates that for d 1ji Generate a random number between 0 and 1;

[0113] S334, inputting the parameter data set to be adjusted into the acceptance information record error mapping model for mapping, and obtaining the acceptance record error data d′ to be adjusted; and setting the fitness function of the electronic scale parameter adjustment sooty tern population according to the acceptance record error data d′ to be adjusted. ;as follows,

[0114]

[0115] S335, start iteration, before iteration, set the parameter adjustment current iteration number to 1; in the first round of iteration, use the electronic scale parameter to adjust the fitness function of the sooty tern population And cooperate with the acceptance information record error mapping model to calculate the fitness value of the initial position of each sooty tern in the first initial position matrix to obtain a first fitness value set; take the maximum fitness in the first fitness value set and the corresponding initial position of the sooty tern as the first global optimal fitness and the first global optimal position respectively; update the initial position of each sooty tern in the first initial position matrix according to the first global optimal fitness and the first global optimal position; after the update is completed, adjust the current iteration number of the parameter by 1 and enter the next round of iteration;

[0116] In each other iteration process, the electronic scale parameters are used to adjust the fitness function of the sooty tern population. And cooperate with the acceptance information record error mapping model to calculate the fitness value of the position of each sooty tern in the sooty tern population adjusted by the electronic scale parameters updated in the previous iteration process to obtain a second fitness value set; the maximum fitness in the second fitness value set and the corresponding position of the sooty tern are respectively used as the second global optimal fitness and the second global optimal position; according to the second global optimal fitness and the second global optimal position, the position of each sooty tern in the sooty tern population adjusted by the electronic scale parameters updated in the previous iteration process is updated; after the update is completed, the current iteration number of the parameter adjustment is increased by 1 and the next iteration is entered;

[0117] S336, when When , the iteration is stopped to obtain the first final global optimal position and the first final global optimal fitness; when the first final global optimal fitness is less than the acceptance record error threshold, the first final global optimal position is used as the adjusted parameter data set; otherwise, return to S335 to continue iterating until the first final global optimal fitness is less than the acceptance record error threshold;

[0118] The sooty tern optimization algorithm can perform global search in the search space by simulating the migration behavior of sooty terns, which helps to find the global optimal solution or the area close to the global optimal solution; the local search strategy in the algorithm can help the algorithm to perform fine search near the local optimal solution and improve the accuracy of the solution; the convergence speed is relatively fast, and a better solution can be found in a shorter time; it has less dependence on initial conditions and parameter settings and has strong robustness; based on the above advantages, the sooty tern optimization algorithm is used in this scheme to iteratively adjust multiple parameters of the current electronic scale at the same time, and the acceptance record error data of the current electronic scale is used as the fitness function. Therefore, as the iteration proceeds, the acceptance record error data of the current electronic scale becomes smaller and smaller, and finally meets the requirements;

[0119] S4, the acceptance data integration cluster building module is used to cooperate with the current electronic scale final parameter data matrix and multiple current electronic scales to build an electronic scale acceptance data integration cluster;

[0120] The S4 comprises the following steps:

[0121] S41, using the current electronic scale final parameter data matrix to set the parameters of each current initial electronic scale in the current initial electronic scale set; after the parameter setting is completed, the current final electronic scale set is obtained;

[0122] S42, setting acceptance data integration electronic scales; constructing an electronic scale acceptance data integration cluster, setting the number of task nodes for acceptance data recording, the number of acceptance data transmission task nodes, and the number of acceptance data integration task nodes for each current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster, and obtaining the data matrix of the initial node number of the acceptance data integration cluster task ;as follows,

[0123]

[0124] in, represents the number of initial task nodes for setting acceptance data records for the i-th current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster, Respectively represent the number of initial task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster;

[0125] S5, the cluster task node number optimization module is used to collect the acceptance information records of each current final electronic scale and the time difference when the total number of integrated acceptance information records reaches the number of acceptance data, and optimize the number of task nodes in the electronic scale acceptance data integration cluster according to the time difference to obtain the final node number data matrix of the acceptance data integration cluster task;

[0126] The S5 comprises the following steps:

[0127] S51, set the number of acceptance data; count the time data when the total number of acceptance information records of each current final electronic scale in the current final electronic scale reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and obtain the acceptance end time data e 1 And the initial time data of the integration end 2 ;

[0128] S52, setting acceptance integration delay error threshold e'; when e 2 -e 1 ≥e′, the data matrix of the initial node number of the acceptance data integration cluster task is adjusted until e 2 -e 1 <e′, the final node number data matrix of the acceptance data integration cluster task is obtained; otherwise, there is no need to adjust the initial node number data matrix of the acceptance data integration cluster task, and the initial node number data matrix of the acceptance data integration cluster task is used as the final node number data matrix of the acceptance data integration cluster task;

[0129] The step of adjusting the initial node number data matrix of the acceptance data integration cluster task in S52 includes the following steps:

[0130] S521, build acceptance integration node to adjust the sooty tern population c 2i Indicates that the acceptance integration node adjusts the i-th sooty tern in the sooty tern population, c′ 2 Indicates that the acceptance integration node adjusts the scale of the black tern population; Sets the maximum number of iterations of the acceptance integration node to adjust the black tern population And the current number of iterations is , respectively recorded as the maximum number of iterations adjusted by the acceptance integration node and the current number of iterations adjusted by the acceptance integration node; the search space dimension of the sooty tern population adjusted by the acceptance integration node is b′+2;

[0131] S522, setting the value interval of each task's initial node number data in the acceptance data integration cluster task initial node number data matrix, and obtaining a node number value interval matrix ;as follows,

[0132]

[0133] in, respectively represent the lower limit and the upper limit of the number of task nodes for setting acceptance data records for the i-th current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster; Respectively represent the lower limit and the upper limit of the number of task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster;

[0134] According to the node number value interval matrix, the acceptance integration node is set to adjust the initial position matrix of each sooty tern in the sooty tern population, and the second initial position matrix set is obtained. d 2j It indicates that the acceptance integration node adjusts the initial position matrix of the j-th sooty tern in the sooty tern population; as follows,

[0135]

[0136] Among them, d 2j1i Indicates d 2j The position component in the dimension of the number of task nodes for setting acceptance data records for the i-th current final electronic scale in the electronic scale acceptance data integration cluster; d 2j21 d 2j22 Respectively represent d 2jThe position component in the dimension of the number of task nodes set for acceptance data transmission and acceptance data integration in the electronic scale acceptance data integration cluster; d 2j1i d 2j21 d 2j22 The calculation formulas are as follows:

[0137]

[0138] In the formula, rand 2j1i 、rand 2j21 、rand 2j22 Respectively for d 2j1i d 2j21 d 2j22 A random number generated between 0 and 1; ceil represents the rounding function;

[0139] S523, according to the initial time data of the integration end 2 Constructing the fitness function of the electronic scale acceptance data integration cluster ;as follows,

[0140]

[0141] S524, start iteration, before iteration, adjust the current iteration number of the acceptance integration node to 1; in the first round of iteration, use the acceptance integration node to adjust the fitness function of the sooty tern population Calculate the fitness value of the initial position matrix of each sooty tern in the second initial position matrix set to obtain a third fitness value set; use the maximum fitness in the third fitness value set and the corresponding initial position matrix of the sooty tern as the third global optimal fitness and the third global optimal position respectively; update the initial position matrix of each sooty tern in the second initial position matrix set according to the third global optimal fitness and the third global optimal position; after the update is completed, adjust the current iteration number of the acceptance integration node by 1 and enter the next round of iteration;

[0142] In each other iteration process, the acceptance integration node is used to adjust the fitness function of the sooty tern population. Calculate the fitness value of the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous iteration process to obtain a fourth fitness value set; use the maximum fitness in the fourth fitness value set and the corresponding sooty tern position matrix as the fourth global optimal fitness and the fourth global optimal position respectively; update the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous iteration process according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, add 1 to the current iteration number of the acceptance integration node adjustment and enter the next iteration;

[0143] S525, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until The second final global optimal position is used as the data matrix of the number of nodes after the optimization of the acceptance data integration cluster task; the electronic scale acceptance data integration cluster is set according to the data matrix of the number of nodes after the optimization of the acceptance data integration cluster task; after the setting is completed, the total number of acceptance information records of each current final electronic scale in the current final electronic scale set reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and the optimized acceptance terminal time data e is obtained. 3 And the time data after integration optimization 4 ;

[0144] When e 4 -e 3 <e′, the node number data matrix after the optimization of the acceptance data integration cluster task is used as the final node number data matrix of the acceptance data integration cluster task; otherwise, return to S524 and continue to iterate until e 4 -e 3 Until <e′;

[0145] S53, setting the task node data of the electronic scale acceptance data integration cluster according to the final node number data matrix of the acceptance data integration cluster task.

[0146] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0147] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. An integrated intelligent electronic scale, comprising a weighing plate (1), a display screen (2), and a support plate (3), characterized in that: It also includes a historical acceptance data collection module, a record error mapping model construction module, a current electronic scale parameter adjustment module, an acceptance data integration cluster construction module, and a cluster task node number optimization module; S1, the historical acceptance data collection module is used to collect acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history, and obtain a historical record information data matrix, a historical standard information data matrix and a historical electronic scale parameter data matrix; S2, the record error mapping model construction module is used to construct the acceptance information record error mapping model according to the historical record information data matrix, the historical standard information data matrix and the historical electronic scale parameter data matrix; S3, the current electronic scale parameter adjustment module is used to map the parameter data of multiple current electronic scales and adjust the parameter data of multiple current electronic scales by using the acceptance information record error mapping model to obtain the final parameter data matrix of the current electronic scale; S4, the acceptance data integration cluster building module is used to cooperate with the current electronic scale final parameter data matrix and multiple current electronic scales to build an electronic scale acceptance data integration cluster; S5. The cluster task node number optimization module is used to collect the acceptance information records of each current final electronic scale and the time difference when the total number of integrated acceptance information records reaches the number of acceptance data, and optimize the number of task nodes in the electronic scale acceptance data integration cluster.

2. The integrated intelligent electronic scale according to claim 1, characterized in that: The S1 comprises the following steps: S11, setting multiple information data types recorded by the electronic scale during the canteen acceptance process to obtain a record information type set; then setting multiple parameter types of the electronic scale to obtain an electronic scale parameter type set; S12. Collect acceptance record information data, corresponding standard information data and parameter data of multiple electronic scales in history according to the record information type set and the electronic scale parameter type set to obtain a historical record information data matrix, a historical standard information data matrix and a historical electronic scale parameter data matrix.

3. The integrated intelligent electronic scale according to claim 2, characterized in that: The S2 comprises the following steps: S21, calculating the error data between each acceptance record information data of the electronic scale in history and the standard information data according to the historical record information data matrix and the historical standard information data matrix, and obtaining a historical record information error data set; S22, constructing an acceptance information record error mapping model according to the historical record information error data set and the historical electronic scale parameter data matrix.

4. The integrated intelligent electronic scale according to claim 3, characterized in that: The acceptance information record error mapping model adopts the SVM model.

5. The integrated intelligent electronic scale according to claim 4, characterized in that: The S3 comprises the following steps: S31, setting a plurality of electronic scales currently in use to obtain a current initial electronic scale set; collecting parameter data of each electronic scale in the current initial electronic scale set according to the electronic scale parameter type set to obtain a current electronic scale initial parameter data matrix; S32, inputting each row of data in the current electronic scale initial parameter data matrix into the acceptance information record error mapping model for mapping, to obtain an initial acceptance record error mapping data set; S33. Set an acceptance record error threshold; when there is initial acceptance record error mapping data in the initial acceptance record error mapping data set that is greater than or equal to the acceptance record error threshold, adjust the initial parameter data of the electronic scale corresponding to the initial acceptance record error mapping data to obtain an adjusted parameter data set; and then use the adjusted parameter data set to replace the corresponding initial parameter data in the initial parameter data matrix of the current electronic scale to obtain the final parameter data matrix of the current electronic scale.

6. The integrated intelligent electronic scale according to claim 5, characterized in that: In S33, the initial parameter data of the electronic scale corresponding to the initial acceptance record error mapping data is adjusted using the Sooty Tern optimization algorithm.

7. The integrated intelligent electronic scale according to claim 6, characterized in that: The S4 comprises the following steps: S41, using the current electronic scale final parameter data matrix to set the parameters of each current initial electronic scale in the current initial electronic scale set; after the parameter setting is completed, the current final electronic scale set is obtained; S42, setting acceptance data integration electronic scales; constructing an electronic scale acceptance data integration cluster, setting the number of task nodes for acceptance data recording, the number of acceptance data transmission task nodes and the number of acceptance data integration task nodes for each current final electronic scale in the current final electronic scale set in the electronic scale acceptance data integration cluster, and obtaining the data matrix of the initial node number of the acceptance data integration cluster task.

8. The integrated intelligent electronic scale according to claim 7, characterized in that: The S5 comprises the following steps: S51, setting the number of acceptance data; counting the time data when the total number of acceptance information records of each current final electronic scale in the current final electronic scale set reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and obtaining the acceptance end time data e1 and the integration end initial time data e2; S52, setting the acceptance integration delay error threshold value e′; when e2-e1≥e′, adjusting the data matrix of the initial node number of the acceptance data integration cluster task until e2-e1<e′, and obtaining the data matrix of the final node number of the acceptance data integration cluster task; otherwise, there is no need to adjust the data matrix of the initial node number of the acceptance data integration cluster task, and the data matrix of the initial node number of the acceptance data integration cluster task is used as the data matrix of the final node number of the acceptance data integration cluster task; S53, setting the task node data of the electronic scale acceptance data integration cluster according to the final node number data matrix of the acceptance data integration cluster task.

9. The integrated intelligent electronic scale according to claim 8, characterized in that: The step of adjusting the initial node number data matrix of the acceptance data integration cluster task in S52 includes the following steps: S521, constructing an acceptance integration node to adjust the sooty tern population; setting the maximum number of iterations of the acceptance integration node to adjust the sooty tern population to And the current number of iterations is Recorded as the maximum number of iterations adjusted by the acceptance integration node and the current number of iterations adjusted by the acceptance integration node respectively; S522, setting the value interval of the initial node number data of each task in the acceptance data integration cluster task initial node number data matrix, and obtaining the node number value interval matrix; setting the acceptance integration node to adjust the initial position matrix of each sooty tern in the sooty tern population according to the node number value interval matrix, and obtaining the second initial position matrix; S523, constructing a fitness function of the electronic scale acceptance data integration cluster according to the initial time data of the integration terminal; S524, start iteration, and before iteration, set the current iteration number of the acceptance integration node adjustment to 1; in each round of iteration, use the fitness function of the acceptance integration node to adjust the sooty tern population to calculate the fitness value of the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous round of iteration, and update the position matrix of each sooty tern in the sooty tern population adjusted by the acceptance integration node obtained in the previous round of iteration; S525, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until until time; use the second final global optimal position as the data matrix of the number of nodes after optimization of the acceptance data integration cluster task; set the electronic scale acceptance data integration cluster according to the data matrix of the number of nodes after optimization of the acceptance data integration cluster task; after the setting is completed, count the time data when the total number of acceptance information records of each current final electronic scale in the current final electronic scale set reaches the number of acceptance data and the total number of acceptance information records integrated in the acceptance data integration electronic scale reaches the number of acceptance data, and obtain the optimized acceptance end time data e3 and the integrated end optimized time data e4; when e4-e3<e′, use the data matrix of the number of nodes after optimization of the acceptance data integration cluster task as the final node number data matrix of the acceptance data integration cluster task; otherwise, return to S524 to continue iterating until e4-e3<e′.

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