CN103258388B - Automatic trading apparatus and server and the method for predicting cash demand amount - Google Patents
Automatic trading apparatus and server and the method for predicting cash demand amount Download PDFInfo
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Abstract
According to the present invention, propose a kind of automatic trading apparatus, comprising: storage part, for storing the historical transaction record of automatic trading apparatus; Optimal threshold determination portion, for determining the optimal threshold of the index removing random transaction record; Data cleansing portion, refers to the random transaction record of target value beyond the confining spectrum of described optimal threshold for removing described in the historical transaction record in fixed time section; And statistical forecast portion, for adding up the historical transaction record after the random transaction record of removal, and predict the cash demand amount in the time period corresponding with fixed time section.
Description
Technical field
The present invention relates to a kind of automatic trading apparatus of using in banking industry and connected server and the method for predicting cash demand amount, more specifically, relate to a kind of automatic trading apparatus and connected server and the method for predicting cash demand amount, by removing the impact of concluding the business on predicted value at random, the precision of cash demand quantitative statistics and prediction can be improved.
Background technology
Automatic trading apparatus is widely used in bank's financial industry relevant with other, as a kind of self-help terminal equipment, for user deposit be provided, withdraw the money, transfer accounts, paying, the financial service such as purchase payment.Automatic trading apparatus improves the efficiency of operation of bank, decreases the situation of bank counter queuing transacting business, for bank saves a large amount of human costs, also makes user's transacting business more convenient simultaneously.
General automatic cash deposit and withdrawal device (namely, automatic trading apparatus) need the staff of bank in the banknote box of this device, load the banknote of some, make device rich desirable, with the normal operation of assurance device, and improve the service efficiency of device.
In the past fill out in paper money scheme, bank clerk is rule of thumb summarised in the banknote needing to insert how much quantity in certain hour section with historical data, also have by computer program realize fill out cash amount calculate and prediction method and system.Such as, in the Japanese publication (Unexamined Patent 9-153167) being entitled as " automatic trading apparatus ", propose on the basis of historical transaction record, the environmental information of automatic trading apparatus is affected according to date, week, wage day etc., predict the trading volume of automatic trading apparatus, thus improve the fund utilization rate of bank.
In automatic trading apparatus actual motion, some transaction is random.Here, refer to that transaction has not regulation and periodicity at random, and the behavior of this user can not repeat in the future.As certain user common amount deposited on certain automatic trading apparatus is all less than 10,000 yuan, but because cause specific deposits 100,000 yuan in certain transaction, current operation is regarded as once concluding the business at random.Although known technology introduce historical data and date, week etc. parameter to revise the predicted value of automatic trading apparatus, do not consider the impact of concluding the business on predicted value at random.Random transaction has uncertainty due to the amount of money and time, can not repeat, and thus causes to add up according to historical data the cash demand amount got and can not embody regularity, and then makes the predicted value that obtains based on historical data also inaccurate.
Therefore, a kind of novel automatic trading apparatus and server is needed and for predicting that the method for cash demand amount is to improve the precision of cash demand quantitative statistics and prediction.The cash demand amount of automatic trading apparatus here comprises withdraws the money demand and deposit demand, usually for the automatic trading apparatus that banknote in paper money case can circulate, needs the cash amount that adds in automatic trading apparatus to be that total amount of withdrawing the money deducts deposit total amount.
Summary of the invention
The present invention is proposed in order to solve above-mentioned technical task.Therefore, the object of this invention is to provide a kind of automatic trading apparatus and server and the method for predicting cash demand amount, can by removing the impact concluded the business on predicted value at random, the precision of raising cash demand quantitative statistics and prediction.
To achieve these goals, according to the present invention, propose a kind of automatic trading apparatus, comprising: storage part, for storing the historical transaction record of automatic trading apparatus; Optimal threshold determination portion, for determining the optimal threshold of the index removing random transaction record; Data cleansing portion, refers to the random transaction record of target value beyond the confining spectrum of described optimal threshold for removing described in the historical transaction record in fixed time section; And statistical forecast portion, for adding up the historical transaction record after the random transaction record of removal, and predict the cash demand amount in the time period corresponding with fixed time section.
Preferably, the described index for removing random transaction record comprises: the trading frequency in the trading volume in transaction record, exchange hour and trading frequency statistical form, and wherein, described trading volume comprises credit transaction amount and trading volume of withdrawing the money.
Preferably, described trading frequency statistical form is also stored in described storage part.
Preferably, the threshold value of index described in the initialization of described optimal threshold determination portion; Remove threshold value in original transaction record define beyond transaction record; Transaction record after transaction record beyond utilization removal threshold value defines is added up and predicts the demand of the past period, obtains the historical forecast precision of the past period; Threshold value is adjusted by one step; Random transaction beyond defining by the threshold value removal threshold value after adjustment, calculates new historical forecast precision; Circulation is carried out adjusting thresholds and precision of prediction and is calculated, until threshold value arrives the border of the value of described index and maximal value or minimum value, threshold value the highest for the precision of prediction obtained in so repeatedly prediction is defined as described optimal threshold.
Preferably, described statistical forecast portion utilizes time series predicting model, Regression Forecast, grey method, machine learning predicted method to predict cash demand amount.
In addition, according to the present invention, also proposed a kind of for the method for automatic trading apparatus prediction cash demand amount, comprising: the optimal threshold determining the index removing random transaction record; The random transaction record of target value beyond the confining spectrum of described optimal threshold is referred to described in the historical transaction record of the automatic trading apparatus in removal fixed time section; And the historical transaction record after removing random transaction record is added up, and predict the cash demand amount in the time period corresponding with fixed time section.
In addition, according to the present invention, also proposed a kind of server be connected with automatic trading apparatus, comprising: acquisition unit, for obtaining the historical transaction record of automatic trading apparatus from automatic trading apparatus; Optimal threshold determination portion, for determining the optimal threshold of the index removing random transaction record; Data cleansing portion, refers to the random transaction record of target value beyond the confining spectrum of described optimal threshold for removing described in the historical transaction record in fixed time section; And statistical forecast portion, for adding up the historical transaction record after the random transaction record of removal, and predict the cash demand amount in the time period corresponding with fixed time section.
As can be seen here, known technology does not consider the impact of concluding the business on predicted value at random.And cash forecast device of the present invention is by removing the impact of concluding the business on predicted value at random, improve precision of prediction.
Particularly, according to the present invention, extract transaction log or the transaction statistics of automatic trading apparatus, by being the setup measures optimal threshold for removing random transaction, the transaction record of desired value outside the confining spectrum of optimal threshold is removed as random transaction record from transaction record set, carries out adding up and predicting with the transaction record set after removing random transaction record.The so-called index for removing random transaction comprises: the attributes such as the trading frequency in trading volume (comprising credit transaction amount and trading volume of withdrawing the money), exchange hour and trading frequency statistical form in transaction record.The setting of optimal threshold or deterministic process are: the threshold value of this index of initialization; Remove threshold value in original historical transaction record define beyond transaction record; The demand of the transaction record statistical forecast the past period after the transaction record beyond defining by removal threshold value, obtains the historical forecast precision of the past period; Threshold value is adjusted by one step; Remove random transaction by the threshold value after adjustment, calculate new historical forecast precision; Circulation is carried out adjusting thresholds and is predicted, until threshold value arrives the border of the value of this index and maximal value or minimum value, threshold value the highest for the precision obtained in repeatedly prediction is defined as described optimal threshold.
By arranging optimal threshold, removing the random transaction record in transaction record, can precision of prediction be improved.Predict by this prediction mode and be automatic trading apparatus load cash, the operational efficiency of automatic trading apparatus can be improved, avoid scarce paper money or exceed required banknote and put into automatic trading apparatus, satisfaction and the bank capital utilization factor of bank-user can be improved.
Accompanying drawing explanation
Fig. 1 shows the automatic trading apparatus of first embodiment of the invention and the schematic diagram of server.
The automatic trading apparatus that Fig. 2 shows first embodiment of the invention carries out the schematic diagram of the workflow of cash demand prediction.
Fig. 3 shows the schematic diagram of the process of the random transaction of optimal threshold removal of the automatic trading apparatus service index of first embodiment of the invention.
Fig. 4 shows the schematic diagram of the transaction statistical form stored in the server of first embodiment of the invention.
Fig. 5 shows the schematic diagram of the trading record sheet stored in the server of first embodiment of the invention.
Fig. 6 shows the schematic diagram of the trading frequency statistical form stored in the server of first embodiment of the invention.
Fig. 7 shows the schematic diagram of the process of the index optimal threshold of a calculating automatic trading apparatus of first embodiment of the invention.
Fig. 8 shows the schematic diagram of the process of the deposit amount optimal threshold of a calculating automatic trading apparatus of first embodiment of the invention.
Fig. 9 shows the schematic diagram of the process of the trading frequency optimal threshold of a calculating automatic trading apparatus of first embodiment of the invention.
Embodiment
Below with reference to the accompanying drawings the preferred embodiments of the present invention are described.
Fig. 1 shows the automatic trading apparatus of first embodiment of the invention and the schematic diagram of server.
The operations such as the automatic trading apparatus 100 shown in Fig. 1 carries out depositing for user, withdraw the money, transfer accounts, pay, payment.Automatic trading apparatus 100 comprises: banknote box 101, banknote module 102, print module 103, card reading module 104, power management module 105, communication module 106, controller 107, user operation module 108 and data memory module 111.User operation module comprises: keyboard 109 and display device 110.Here, banknote box 101 puts banknote.The banknote of banknote module 102 deposit taking is also stored in banknote box 101, and banknote module 102 spues banknote to cash dispensing port by the amount of money of withdrawing the money from banknote box.Data memory module 111 stores the Operation Log of automatic trading apparatus.The Operation Log of automatic trading apparatus is sent to server 112 by communication module 106.
The transaction log data that server 112 shown in Fig. 1 sends for receiving automatic trading apparatus 100, adds up and predicts cash demand amount.One station server 112 can connect multiple automatic trading apparatus 100.Server 112 comprises: import module 113, statistical module 114, data cleansing module 115, demand forecast module 116, communication module 117, controller 120, employee's operational module 121 and data memory module 124.Employee's operational module 121 comprises: keyboard 122 and display device 123.Communication module 117 receives the transaction log that automatic trading apparatus 100 sends, and by importing in transaction log record table that Operation Log to be saved in data memory module 124 by module 113, as shown in Figure 5.Statistical module 114 according to the historical transactional information of automatic trading apparatus, the deposit total amount of statistical unit time (hour, day) and the total amount be saved in the transaction statistical form in data memory module 124 of withdrawing the money, as shown in Figure 4.Statistical module 114 according to the historical transactional information of automatic trading apparatus, add up each subscriber card time a period of time (moon, year etc.) trading frequency and be saved in the trading frequency statistical form in data memory module 124, as shown in Figure 6.Data cleansing module 115 removes the random transaction record in historical transaction record.Demand forecast module 116 is according to historical trading statistical information and the cash demand amount removing the prediction of result fixed time after random transaction.
The flow process that cash demand according to the present invention is predicted as shown in Figure 2.In step 202., imported in transaction log record table as shown in Figure 5 by importing module 113.The information such as device numbering, exchange hour, action type, bank's card number, dealing money and operating result are contained in transaction log record table.In step 203, data cleansing module 116 removes invalid record in historical transaction record or error logging.In step 204, statistical module 114 according to the historical transactional information of automatic trading apparatus, the deposit total amount of statistical unit time (hour, day) and the total amount being saved in the transaction statistical form in data memory module 124 of withdrawing the money.Transaction statistical form as shown in Figure 4 comprise device numbering, the date, hour, total amount of withdrawing the money, deposit total amount, may the amount of withdrawing the money and may the amount of deposit (and not shown).After step 204, conclude the business in statistical form may the amount of withdrawing the money and may the amount of deposit be defaulted as 0.In step 205, operating personnel are by input equipment such as keyboard 122 grade, and input needs the data such as the numbering of the automatic trading apparatus of predicted required amount and the time of prediction.In step 206, demand forecast module 116 is according to the numbering of the automatic trading apparatus of given parameters, predicted time and revised statistics prediction cash demand amount.Demand forecast module 116 can adopt multiple Forecasting Methodology, as time series predicting model, Regression Forecast, grey method, machine learning predicted method.The input variable related in forecast model comprises: the time, whether be festivals or holidays, whether be the special days such as paying out wages, statistical demand amount, weather, economic index etc.The data comprising input variable can be generated by statistical module, also can generate in prediction module.Forecasting process is generally: the historical data comprising above-mentioned input variable joined in forecast model and carry out training or calculating, to determine the parameter of forecast model; Then prediction input variable is brought into the model after training, i.e. the data of step 205 input, and model computational prediction demand.In step 207, cash demand predicts the outcome and is saved.
The data cleansing module 115 of step 203 removes the detail flowchart of random transaction data as shown in Figure 3.In step 301, the optimal threshold of the index for removing random transaction is calculated.In step 302, the optimal threshold of service index, the transaction record beyond the confining spectrum of removal threshold value.In step 303, the transaction record data after removing random transaction record are used to predict, and computational prediction precision.Precision of prediction represents the degree that predicted required amount and actual demand amount are consistent.Demand Forecast accuracy computation method in a period of time is as follows: suppose there is N number of unit interval (as N days) during this period of time, the predicted required amount obtaining each unit interval deduct the difference of actual demand amount square; The above-mentioned N number of amount summation calculated; N-1 is precision of prediction divided by the above-mentioned result calculated.The last bearing reaction degree of the realistic demand of premeasuring.Result is larger, and premeasuring and actual amount more meet, and namely precision of prediction is higher; Otherwise result is less, precision of prediction is lower.Except the method for above-mentioned computational accuracy, the method that also can calculate with other precision of predictions replaces, but needs to adopt identical precision of prediction computing method to every table apparatus.In step 304, if precision of prediction is being less than acceptable scope, then index optimal threshold is being recalculated; Otherwise continue to use this optimal threshold to remove random transaction.This acceptable scope, according to the device of different banks, different location, has different settings.
The detailed process of the index optimal threshold of a calculating automatic trading apparatus of step 301 as shown in Figure 7.In step 701, initialization is carried out to the threshold value of index, here the mean value of this index in the historical transaction record of this device or statistical form is set to initial value, also can by the historical transaction record of this device or the maximal value of this index value of statistical form or minimum value be set to initial value.In a step 702, the transaction record beyond the confining spectrum removing threshold value from the original transaction record of this device.Refer to beyond confining spectrum and be greater than threshold value or be less than threshold value.In step 703, by the record data after the transaction record beyond the confining spectrum of removal threshold value, predict this device the past period demand.Calculate this device past consensus forecast precision P during this period of time.In step 704, by the size of the least unit adjustment threshold value of threshold value.In step 705, from the original transaction record of this device, remove the transaction record beyond amended threshold value confining spectrum.In step 706, by the record data after removal, same time in the past demand is predicted.Calculate past consensus forecast precision P ' during this period of time.In step 707, compare the size of P ' and P.If the precision that P ' is greater than P and the prediction of amended threshold value is greater than original initial value precision of prediction, then enter step 708; Otherwise enter step 709.In step 708, setting allows P equal P ' by representing that current optimal threshold is set to amended threshold value.In step 709, whether judgment threshold is beyond the scope of this index value.The scope of the value of index refers to the value before the historical record of this this device or statistical form middle finger target minimum value and maximal value.If gone beyond the scope, then enter step 710; Otherwise enter step 704, circulation threshold value of modifying compares precision.In step 720, the optimal threshold that P is this index for this device is preserved.
Fig. 8 gives an object lesson of Fig. 7, calculates the optimal threshold that a certain device deposit figureofmerit is removed.In step 801, initialization is carried out to deposit figureofmerit threshold value.Here the mean value that the device being set to field 501 in the trading record sheet shown in Fig. 5 is numbered this device numbering, the action type of field 502 is field 502 amount of money of all records of deposit.In step 802, from the trading record sheet shown in the original transaction record of this device and Fig. 5, field 501 device is numbered this device numbering, field 502 action type is in all records of deposit, removes the transaction record that the amount of money is greater than threshold value.In step 803, be greater than the record data of this device after the transaction record of threshold value with the removal amount of money, by demand forecast module 206, predict this device 1 month demand in the past.Calculate the consensus forecast precision P in past 1 month of this device.In step 804, with 100 yuan for least unit increase threshold value.In step 805, from the original transaction record of this device, remove the transaction record being greater than amended threshold value.In step 806, with carrying out the record data after removal operation, prediction is 1 month demand in the past.Calculate past consensus forecast precision P ' during this period of time.In step 707, compare the size of P ' and P.If the precision that P ' is greater than P and the prediction of amended threshold value is greater than original initial value precision of prediction, then enter step 808; Otherwise enter step 809.In step 808, arrange and allow P equal P ', be about to represent that current optimal threshold is set to amended threshold value.In step 809, whether judgment threshold is beyond minimum value or the maximal value of this index value.If gone beyond the scope, then enter step 810; Otherwise, enter step 804, circulate and modify threshold value and compare precision.In step 810, preserving P is the optimal threshold removed for this device deposit figureofmerit.
Fig. 9 gives another object lesson of Fig. 7, calculates the optimal threshold that a certain device trading frequency index is removed.In step 901, initialization is carried out to trading frequency metrics-thresholds.Here the minimum value that the field 603 that the device being set to field 601 in the trading frequency statistical form shown in Fig. 6 is numbered all records of this device numbering is concluded the business.In step 902, from the trading record sheet shown in the original transaction record of this device and Fig. 5, field 501 device is numbered in all records of this device numbering, removes the transaction record that card number is all card numbers being less than threshold value in statistical form.Wherein, trading frequency statistical form is generated by statistical module 114.In step 903, by the record data of this device performed after above-mentioned removal operation, predict this device 1 month demand in the past.Calculate the consensus forecast precision P in past 1 month of this device.In step 904, with 1 time for least unit increase threshold value.In step 905, from the raw readings of this device, remove the transaction record that card number is all card numbers being less than amendment threshold value in statistical form.In step 906, by the record data performed after above-mentioned removal operation, prediction is 1 month demand in the past.Calculate past consensus forecast precision P ' during this period of time.In step 907, compare the size of P ' and P.If the precision that P ' is greater than P and the prediction of amended threshold value is greater than original initial value precision of prediction, then enter step 908; Otherwise enter step 909.In step 908, arrange and allow P equal P ', be about to represent that current optimal threshold is set to amended threshold value.In step 909, whether judgment threshold is beyond minimum value or the maximal value of this index value.If gone beyond the scope, then enter step 910; Otherwise, enter step 904, circulate and modify threshold value and compare precision.In step 910, preserving P is the optimal threshold removed for this device trading frequency.
According to the present invention, by arranging optimal threshold, removing the random transaction record in transaction record, can precision of prediction be improved.Predict by this prediction mode and be automatic trading apparatus load cash, the operational efficiency of automatic trading apparatus can be improved, avoid scarce paper money or exceed required banknote and put into automatic trading apparatus, satisfaction and the bank capital utilization factor of bank-user can be improved.
Those skilled in the art are to be understood that, module in server disclosed in this invention can when not departing from essence of the present invention, can be installed in automatic trading apparatus, by correction and the prediction of automatic trading apparatus complete independently cash demand amount of the present invention.
Although below show the present invention in conjunction with the preferred embodiments of the present invention, one skilled in the art will appreciate that without departing from the spirit and scope of the present invention, various amendment, replacement and change can be carried out to the present invention.Therefore, the present invention should not limited by above-described embodiment, and should be limited by claims and equivalent thereof.
Claims (6)
1. an automatic trading apparatus, comprising:
Storage part, for storing the historical transaction record of automatic trading apparatus;
Optimal threshold determination portion, for determining the optimal threshold of the index removing random transaction record;
Data cleansing portion, refers to the random transaction record of target value beyond the confining spectrum of described optimal threshold for removing described in the historical transaction record in fixed time section; And
Statistical forecast portion, for adding up the historical transaction record after the random transaction record of removal, and predicts the cash demand amount in the time period corresponding with fixed time section,
The threshold value of index described in the initialization of described optimal threshold determination portion; Remove threshold value in original transaction record define beyond transaction record; Transaction record after transaction record beyond utilization removal threshold value defines is added up and predicts the demand of the past period, obtains the historical forecast precision of the past period; Threshold value is adjusted by one step; Random transaction beyond defining by the threshold value removal threshold value after adjustment, calculates new historical forecast precision; Circulation is carried out adjusting thresholds and precision of prediction and is calculated, until threshold value arrives the border of the value of described index and maximal value or minimum value, threshold value the highest for the precision of prediction obtained in so repeatedly prediction is defined as described optimal threshold.
2. automatic trading apparatus according to claim 1, wherein,
The described index for removing random transaction record comprises: the trading frequency in the trading volume in transaction record, exchange hour and trading frequency statistical form, and wherein, described trading volume comprises credit transaction amount and trading volume of withdrawing the money.
3. automatic trading apparatus according to claim 1, wherein, described trading frequency statistical form is also stored in described storage part.
4. automatic trading apparatus according to claim 1, wherein,
Described statistical forecast portion utilizes time series predicting model, Regression Forecast, grey method, machine learning predicted method to predict cash demand amount.
5., for the method for automatic trading apparatus prediction cash demand amount, comprise the following steps:
Determine the optimal threshold of the index removing random transaction record;
The random transaction record of target value beyond the confining spectrum of described optimal threshold is referred to described in the historical transaction record of the automatic trading apparatus in removal fixed time section; And
Historical transaction record after removing random transaction record is added up, and predicts the cash demand amount in the time period corresponding with fixed time section,
In the step determining optimal threshold, the threshold value of index described in initialization; Remove threshold value in original transaction record define beyond transaction record; Transaction record after transaction record beyond utilization removal threshold value defines is added up and predicts the demand of the past period, obtains the historical forecast precision of the past period; Threshold value is adjusted by one step; Random transaction beyond defining by the threshold value removal threshold value after adjustment, calculates new historical forecast precision; Circulation is carried out adjusting thresholds and precision of prediction and is calculated, until threshold value arrives the border of the value of described index and maximal value or minimum value, threshold value the highest for the precision of prediction obtained in so repeatedly prediction is defined as described optimal threshold.
6. the server be connected with automatic trading apparatus, comprising:
Acquisition unit, for obtaining the historical transaction record of automatic trading apparatus from automatic trading apparatus;
Optimal threshold determination portion, for determining the optimal threshold of the index removing random transaction record;
Data cleansing portion, refers to the random transaction record of target value beyond the confining spectrum of described optimal threshold for removing described in the historical transaction record in fixed time section; And
Statistical forecast portion, for adding up the historical transaction record after the random transaction record of removal, and predicts the cash demand amount in the time period corresponding with fixed time section,
The threshold value of index described in the initialization of described optimal threshold determination portion; Remove threshold value in original transaction record define beyond transaction record; Transaction record after transaction record beyond utilization removal threshold value defines is added up and predicts the demand of the past period, obtains the historical forecast precision of the past period; Threshold value is adjusted by one step; Random transaction beyond defining by the threshold value removal threshold value after adjustment, calculates new historical forecast precision; Circulation is carried out adjusting thresholds and precision of prediction and is calculated, until threshold value arrives the border of the value of described index and maximal value or minimum value, threshold value the highest for the precision of prediction obtained in so repeatedly prediction is defined as described optimal threshold.
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| CN106156122B (en) * | 2015-04-07 | 2020-02-07 | 阿里巴巴集团控股有限公司 | Transaction information acquisition method and device |
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| CN107798057B (en) * | 2017-09-05 | 2019-02-01 | 平安科技（深圳）有限公司 | Transaction data processing method, device, storage medium and computer equipment |
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| CN110400021B (en) * | 2019-07-31 | 2022-03-25 | 中国工商银行股份有限公司 | Bank branch cash usage prediction method and device |
| CN111341040A (en) * | 2020-03-28 | 2020-06-26 | 江西财经职业学院 | Financial self-service equipment and management system thereof |
| CN111708768A (en) * | 2020-05-20 | 2020-09-25 | 广州中智融通金融科技有限公司 | Cash dispatching method, system and storage medium for automatic teller machine |
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