CN106709826A - Restaurant turnover prediction method and device thereof - Google Patents
Restaurant turnover prediction method and device thereof Download PDFInfo
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- CN106709826A CN106709826A CN201510784177.XA CN201510784177A CN106709826A CN 106709826 A CN106709826 A CN 106709826A CN 201510784177 A CN201510784177 A CN 201510784177A CN 106709826 A CN106709826 A CN 106709826A
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- 230000007306 turnover Effects 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000000875 corresponding effect Effects 0.000 claims description 21
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000002596 correlated effect Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 description 4
- 238000009826 distribution Methods 0.000 description 3
- 235000012054 meals Nutrition 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
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- 238000010586 diagram Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
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- 230000002860 competitive effect Effects 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
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- 230000001932 seasonal effect Effects 0.000 description 1
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- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
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- G06Q50/12—Hotels or restaurants
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Abstract
The invention discloses a restaurant turnover prediction method, which comprises steps: historical business data and related influence factors are acquired; the influence factors are marked, the historical business data are marked correspondingly according to the influence factors after being marked, and historical business data in relative to the influence factors are obtained; and when the historical business data in relative to the influence factors are related to the influence factors, a regression coefficient is calculated according to the historical business data in relative to the influence factors and the influence factors, and a restaurant turnover prediction relation is obtained. The restaurant turnover prediction method disclosed by the invention can accurately judge the influence degree of the influence factors on the restaurant turnover, and the restaurant turnover in a further preset time period is accurately predicted. The invention also discloses a restaurant turnover prediction device.
Description
Technical field
The present invention relates to technical field of catering, in particular, it is related to a kind of dining room turnover predictor method
And its device.
Background technology
At present, catering industry is increasingly competitive, is constantly carried including the operation cost such as manpower, raw material
Height, estimates to the turnover, can be very helpful for management of the dining room during daily operation.
It is a problem that food and beverage enterprise boss and manager pay special attention to, current base that the turnover in dining room is estimated
Dining room manager itself some operation can only be all leaned on to go to carry out judgement substantially in sheet, but accuracy rate is very low,
It is difficult to meet the requirement of dining room daily management.The daily procurement plan in kitchen is inaccurate, may purchase more,
Cause not selling completely for the 2nd day, cause residue excessive, inventory cost increases (need to deposit, support person, management)
Or the waste of some fresh (vegetables, seafood, chord) raw material；Buying is very few, and may influence
The business in dining room, does not have thing vegetable to sell；Kitchen do not know in advance can sell how much, before operation
Appropriate cut distribution can only be done, causes to need to carry out many cut distributions work during the business of dining room,
Cause kitchen running efficiency step-down, if the cut distribution workload reduction in meal, these people are in operation process
In can do the biography work such as dish, then my dining room may need the employee for employing just to tail off 2；Dining room
The service trade of daily business is substantially belonged to, if dining room can accurately estimate the turnover, basic just energy is really
Fixed daily passenger flow, then just can rationally be arranged an order according to class and grade according to the customer's number having meal, arranges each post daily
Headcount.
The content of the invention
In order to solve the above technical problems, the present invention provides a kind of dining room turnover predictor method, can combine
The influence factor of the turnover is accurately assessed the future time section dining room turnover.
To achieve the above object, the present invention provides following technical scheme：
A kind of dining room turnover predictor method, including：
Obtain history business data and corresponding influence factor；
The influence factor is marked, and according to the influence factor after mark to history business number
According to corresponding mark is carried out, the history business data on influence factor is obtained；
When the history business data on influence factor is related to the influence factor, according to described
History business data and the influence factor on influence factor calculate regression coefficient, obtain dining room business
Volume estimates relational expression.
Preferably, in above-mentioned dining room turnover predictor method, history business data and corresponding is obtained
Also include after influence factor：
The order of the history business data is determined according to the influence factor, ordinal variable T is obtained.
Preferably, in above-mentioned dining room turnover predictor method, also wrapped before being marked to the influence factor
Include：
Calculate the average value of history business data；
When the history business data less than the average value of the history business data 1/2, it is determined that described
History business data is abnormal data, is deleted.
Preferably, in above-mentioned dining room turnover predictor method, when the influence factor is the date, institute
State and the influence factor is marked, and according to the influence factor after mark to the history business data
Corresponding mark is carried out, the history business data on influence factor is obtained, specifically included：
Date to historical date and following preset time period is marked；
Date after mark is classified according to one week date and phase festivals or holidays, date variable r is obtainedi(i is
Monday, Sunday Tuesday ... and festivals or holidays, i=8)；
According to the date variable riCorresponding mark is carried out to the history business data, history day battalion is obtained
Industry data yi。
Preferably, in above-mentioned dining room turnover predictor method, by the date after mark according to one week date
With phase festivals or holidays classify obtaining date variable, specifically include：
Calculate the arithmetic mean of instantaneous value of each class history day business dataObtain arithmetic mean of instantaneous valueMaximum
ValueAnd minimum valueAnd calculate extreme difference
Calculate the difference that the arithmetic mean of instantaneous value of each class history day business data subtracts each other successively
IfI+1 class and the i-th class are then combined into a class, date variable is obtained after merging
qn(n≤8)。
Preferably, in above-mentioned dining room turnover predictor method, when the history battalion on influence factor
When industry data are related to the influence factor, according to the history business data on influence factor and institute
State influence factor and calculate regression coefficient, obtain the dining room turnover and estimate relational expression, specifically include：
According to the ordinal variable T, the history day business data yiAnd the date variable qnCalculate
The history day business data yiWith the date variable qnSpearman coefficient of rank correlations and its aobvious
Work property level value and/or Kendall rank correlation coefficients and its significance value；
Judge the history day business data yiWith the date variable qnIt is whether significantly correlated；
If related, according to the ordinal variable T, the history day business data yiAnd the day
Phase variable qnRegression coefficient a is calculated, dining room turnover predicting equation y=∑s a*q is obtainedn。
Present invention also offers a kind of dining room turnover estimating device, including：
Dining room traveling service device, for obtaining history business data and corresponding influence factor；
Mark server, for being marked to the influence factor, and according to the influence factor after mark
Corresponding mark is carried out to the history business data, the history business data on influence factor is obtained；
Calculation server, for when the history business data on influence factor and the influence factor
When related, calculated according to the history business data on influence factor and the influence factor and return system
Number, obtains the dining room turnover and estimates relational expression.
Preferably, in above-mentioned dining room turnover estimating device, also including dining room manager, for receiving
The dining room turnover estimates the estimation results of the dining room turnover in the future time section that relational expression is obtained.
From above-mentioned technical proposal as can be seen that a kind of dining room turnover predictor method provided by the present invention,
Including：Obtain history business data and corresponding influence factor；The influence factor is marked,
And corresponding mark is carried out to the history business data according to the influence factor after mark, obtain on shadow
The history business data of the factor of sound；When the history business data on influence factor and the influence because
When plain related, calculated according to the history business data on influence factor and the influence factor and returned
Coefficient, obtains the dining room turnover and estimates relational expression.In the present embodiment, extract history business data and
May influence factor influential on history business data, this influence factor is marked, not only mark
The influence factor of historical time section, should also mark the influence factor in following preset time period, be easy to
Above-mentioned influence factor is smoothly recognized in following preset time period.History is sought according to the influence factor after mark
Industry data are marked accordingly, the history business data on influence factor are obtained, when described on shadow
When the history business data of the factor of sound is related to the influence factor, regression coefficient is calculated, so as to be eaten
The Room turnover estimates relational expression, obtains estimation results, due to influence factor and on influence factor
History business data has carried out the analysis and calculating of correlation, can accurately judge influence factor to dining room
The influence degree of the turnover, accurately estimates the dining room turnover in following preset time period.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to reality
The accompanying drawing to be used needed for example or description of the prior art is applied to be briefly described, it should be apparent that, below
Accompanying drawing in description is only embodiments of the invention, for those of ordinary skill in the art, not
On the premise of paying creative work, other accompanying drawings can also be obtained according to the accompanying drawing for providing.
Fig. 1 is a kind of dining room turnover predictor method flow chart provided in an embodiment of the present invention；
Fig. 2 is a kind of dining room turnover estimating device schematic diagram provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out
Clearly and completely describe, it is clear that described embodiment is only a part of embodiment of the invention, and
It is not all, of embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art are not doing
Go out the every other embodiment obtained under the premise of creative work, belong to the scope of protection of the invention.
Fig. 1,2, Fig. 1 are referred to for a kind of dining room turnover predictor method flow provided in an embodiment of the present invention
Figure；Fig. 2 is a kind of dining room turnover Prediction System schematic diagram provided in an embodiment of the present invention.
The embodiment of the invention discloses a kind of dining room turnover predictor method, it is applied to the dining room turnover and estimates
System, referring to Fig. 1, above-mentioned dining room turnover predictor method includes：
Step S11：Obtain history business data and corresponding influence factor.Wherein, influence factor can be with
It is some objective factors influential on business data such as date, weather and volume of the flow of passengers, or one
Some subjective factors influential on business data such as a little service staffs.
Step S12：The influence factor is marked, and is gone through to described according to the influence factor after mark
History business data carries out corresponding mark, obtains the history business data on influence factor.
Step S13：When the history business data on influence factor is related to the influence factor,
Regression coefficient is calculated according to the history business data on influence factor and the influence factor, is obtained
The dining room turnover estimates relational expression.
Further, arranged according to certain order in order that obtaining history business data, in order to recognize, obtained
Take and also include after history business data and corresponding influence factor：Determine institute according to the influence factor
The order of history business data is stated, ordinal variable T is obtained.
Further, in order that the history business data that must be chosen is more accurate, remove dining room probably due to
Cut off the water, have a power failure and other abnormal conditions cause one day certain time period interrupt business, in data analysis
Exception Filter business data is needed, and the turnover is considered as abnormal data less than the half of the average turnover,
Needs are filtered.Specifically, also including before being marked to the influence factor：Calculate history business number
According to average value；When the history business data less than the average value of the history business data 1/2,
Determine that the history business data, for abnormal data, is deleted.
In the present embodiment, history business data and may shadow influential on history business data is extracted
The factor of sound, is marked to this influence factor, not only marks the influence factor of historical time section, should also
Influence factor in the following preset time period of mark, is easy to smoothly to be recognized in following preset time period above-mentioned
Influence factor.History business data is marked accordingly according to the influence factor after mark, is closed
In the history business data of influence factor, when the history business data on influence factor and the shadow
When the factor of sound is related, regression coefficient is calculated, relational expression is estimated so as to obtain the dining room turnover, estimated
As a result, due to influence factor and the history business data on influence factor carried out correlation point
Analysis and calculating, can accurately judge influence degree of the influence factor to the dining room turnover, accurately estimate not
The dining room turnover come in preset time period.
The embodiment of the invention discloses a kind of specific dining room turnover predictor method, implement relative to upper one
Example, the present embodiment is further illustrated and optimizes to technical scheme.Specifically：
In order to count the influence with seasonal variations or festivals or holidays to the dining room turnover, a selection date is
Influence factor.When influence factor is the date, specifically, in upper embodiment step S12, for the ease of
Statistics and identification history business data and date, the influence factor is marked, and according to mark
Influence factor afterwards carries out corresponding mark to the history business data, obtains going through on influence factor
History business data, specifically includes：
Step S121：Date to historical date and following preset time period is marked；
Step S122：Date after mark is classified according to one week date and phase festivals or holidays, day is obtained
Phase variable ri(i is Monday, Sunday Tuesday ... and festivals or holidays, i=8)；
Step S123：According to the date variable riCorresponding mark is carried out to the history business data,
Obtain history day business data yi。
Further, in above-mentioned steps S122, it is contemplated that inhomogeneity date corresponding history day business data
May be identical, more accurately classification is carried out to the date, it is therefore an objective to when more accurately estimating following default
Between the dining room turnover in section.The date by after mark is divided according to one week date and phase festivals or holidays
Class obtains date variable, specifically includes：
Calculate the arithmetic mean of instantaneous value of each class history day business dataObtain arithmetic mean of instantaneous valueMaximum
ValueAnd minimum valueAnd calculate extreme difference
Calculate the difference that the arithmetic mean of instantaneous value of each class history day business data subtracts each other successively
IfI+1 class and the i-th class are then combined into a class, date variable is obtained after merging
qn(n≤8)。
In upper embodiment step S13, the history business data on influence factor and the influence
The correlation analysis of factor and calculating process：
When the history business data on influence factor is related to the influence factor, according to described
History business data and the influence factor on influence factor calculate regression coefficient, obtain dining room business
Volume estimates relational expression, specifically includes：
Step S131：According to the ordinal variable T, the history day business data yiAnd the date
Variable qnCalculate the history day business data yiWith the date variable qnSpearman rank correlations
Coefficient and its significance value and/or Kendall rank correlation coefficients and its significance value；
Step S132：Judge the history day business data yiWith the date variable qnIt is whether significantly correlated；
Step S133：If related, according to the ordinal variable T, the history day business data yiWith
And the date variable qnRegression coefficient a is calculated, dining room turnover predicting equation y=∑s a*q is obtainedn。
It is pointed out that the business data in dining room with the difference on date in addition to having certain change,
Also by weather etc., other influence factors are influenceed, and these influence factors can be counted by the above method
Calculate, accurately judge influence degree of the influence factor to the dining room turnover, accurately estimate following Preset Time
The dining room turnover in section.
The embodiment of the invention also discloses a kind of dining room turnover estimating device, referring to Fig. 2, above-mentioned dining room battalion
Industry volume estimating device includes：
Dining room traveling service device 21, for obtaining history business data and corresponding influence factor；
Calculation server 22, for being marked to the influence factor, and according to mark after influence because
Element carries out corresponding mark to the history business data, obtains the history business data on influence factor；
When the history business data on influence factor is related to the influence factor, according to it is described on
The history business data of influence factor and the influence factor calculate regression coefficient, obtain the dining room turnover pre-
Estimate relational expression.
In the present embodiment, above-mentioned dining room turnover estimating device also includes dining room manager 23, for receiving
The dining room turnover estimates the estimation results of the dining room turnover in the future time section that relational expression is obtained.
A kind of dining room turnover predictor method and its device that the present invention is provided, realize to the dining room turnover
It is accurate estimate, fundamentally change dining room in daily operation management process from labor management to digitization intelligence
The transformation that can be managed, from empirical low level management to the transformation of scientific precision management, greatly improves meal
Room efficiency, it is effective to promote the intelligentized process of catering industry IT application in management.
Each embodiment is described by the way of progressive in this specification, and each embodiment is stressed
The difference with other embodiment, between each embodiment identical similar portion mutually referring to.
The foregoing description of the disclosed embodiments, enables professional and technical personnel in the field to realize or use
The present invention.Various modifications to these embodiments will be for those skilled in the art aobvious and easy
See, generic principles defined herein can without departing from the spirit or scope of the present invention,
Realize in other embodiments.Therefore, the present invention is not intended to be limited to the embodiments shown herein,
And it is to fit to the most wide scope consistent with principles disclosed herein and features of novelty.
Claims (8)
1. a kind of dining room turnover predictor method, it is characterised in that including：
Obtain history business data and corresponding influence factor；
The influence factor is marked, and according to the influence factor after mark to history business number
According to corresponding mark is carried out, the history business data on influence factor is obtained；
When the history business data on influence factor is related to the influence factor, according to described
History business data and the influence factor on influence factor calculate regression coefficient, obtain dining room business
Volume estimates relational expression.
2. turnover predictor method in dining room as claimed in claim 1, it is characterised in that obtain history battalion
Also include after industry data and corresponding influence factor：
The order of the history business data is determined according to the influence factor, ordinal variable T is obtained.
3. turnover predictor method in dining room as claimed in claim 2, it is characterised in that on the influence
Also include before factor mark：
Calculate the average value of history business data；
When the history business data less than the average value of the history business data 1/2, it is determined that described
History business data is abnormal data, is deleted.
4. the dining room turnover predictor method as described in any one of claims 1 to 3, it is characterised in that
It is described that the influence factor is marked when the influence factor is the date, and after foundation mark
Influence factor carries out corresponding mark to the history business data, obtains the history battalion on influence factor
Industry data, specifically include：
Date to historical date and following preset time period is marked；
Date after mark is classified according to one week date and phase festivals or holidays, date variable r is obtainedi(i is
Monday, Sunday Tuesday ... and festivals or holidays, i=8)；
According to the date variable riCorresponding mark is carried out to the history business data, history day battalion is obtained
Industry data yi。
5. turnover predictor method in dining room as claimed in claim 4, it is characterised in that after mark
Date classify obtaining date variable according to one week date and phase festivals or holidays, specifically includes：
Calculate the arithmetic mean of instantaneous value of each class history day business dataObtain arithmetic mean of instantaneous valueMaximum
ValueAnd minimum valueAnd calculate extreme difference
Calculate the difference that the arithmetic mean of instantaneous value of each class history day business data subtracts each other successively
IfI+1 class and the i-th class are then combined into a class, date variable is obtained after merging
qn(n≤8)。
6. turnover predictor method in dining room as claimed in claim 5, it is characterised in that when it is described on
When the history business data of influence factor is related to the influence factor, according to described on influence factor
History business data and the influence factor calculate regression coefficient, obtain the dining room turnover and estimate relational expression,
Specifically include：
According to the ordinal variable T, the history day business data yiAnd the date variable qnCalculate
The history day business data yiWith the date variable qnSpearman coefficient of rank correlations and its aobvious
Work property level value and/or Kendall rank correlation coefficients and its significance value；
Judge the history day business data yiWith the date variable qnIt is whether significantly correlated；
If related, according to the ordinal variable T, the history day business data yiAnd the day
Phase variable qnRegression coefficient a is calculated, dining room turnover predicting equation y=∑s a*q is obtainedn。
7. a kind of dining room turnover estimating device, it is characterised in that including：
Dining room traveling service device, for obtaining history business data and corresponding influence factor；
Calculation server, for being marked to the influence factor, and according to the influence factor after mark
Corresponding mark is carried out to the history business data, the history business data on influence factor is obtained；
When the history business data on influence factor is related to the influence factor, according to it is described on
The history business data of influence factor and the influence factor calculate regression coefficient, obtain the dining room turnover pre-
Estimate relational expression.
8. turnover estimating device in dining room as claimed in claim 7, it is characterised in that also including dining room
Manager, dining room business in the future time section that relational expression is obtained is estimated for receiving the dining room turnover
The estimation results of volume.
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| CN201510784177.XA CN106709826A (en) | 2015-11-13 | 2015-11-13 | Restaurant turnover prediction method and device thereof |
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| CN201510784177.XA CN106709826A (en) | 2015-11-13 | 2015-11-13 | Restaurant turnover prediction method and device thereof |
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| CN201510784177.XA Pending CN106709826A (en) | 2015-11-13 | 2015-11-13 | Restaurant turnover prediction method and device thereof |
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| CN107507040A (en) * | 2017-09-05 | 2017-12-22 | 盐城工学院 | A kind of turnover processing method and data processing equipment |
| CN107563649A (en) * | 2017-09-05 | 2018-01-09 | 盐城工学院 | A kind of data processing method and equipment |
| CN107590595A (en) * | 2017-09-05 | 2018-01-16 | 盐城工学院 | A kind of scheduling method and data processing equipment |
| CN111353828A (en) * | 2020-03-30 | 2020-06-30 | 中国工商银行股份有限公司 | Method and device for predicting number of people arriving at store from network |
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| CN107507040A (en) * | 2017-09-05 | 2017-12-22 | 盐城工学院 | A kind of turnover processing method and data processing equipment |
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Application publication date: 20170524 |