阅读说明：本技术 一种智能挑选方法、系统、设备及介质 (Intelligent selection method, system, equipment and medium ) 是由 蒋琦洪 郭韶晖 石贇 黄国珉 吴涛 吴维益 施乐 丛璇熠 于 2021-09-15 设计创作，主要内容包括：本发明涉及一种智能挑选方法、系统、设备及介质,本发明先对数字资产的面额从小到大进行排列,然后剔除大于所述需要挑选的数字资产的面额总和SUM-(总)的数字资产,最后在剩下的数字资产中选出多个符合要求的最优结果集。本发明能够极大减少运算次数,不会因为数字资产规模成倍增加而增加消耗时间,可适用于高频试算金融资产的组合方案。(The invention relates to an intelligent selecting method, system, equipment and medium, which arranges the denominations of digital assets from small to large, and then eliminates the SUM of the denominations of the digital assets which is larger than the SUM of the denominations of the digital assets to be selected General assembly And finally, selecting a plurality of optimal result sets which meet the requirements from the rest digital assets. The invention can greatly reduce the operation times, can not increase the consumption time due to the multiplied increase of the digital asset scale, and can be suitable for a combination scheme of high-frequency trial calculation of financial assets.)

1. An intelligent selection method is characterized by comprising the following steps:

acquiring a plurality of digital assets;

determining the number n to be selected and the SUM SUM of the denominations of the digital assets to be selected according to the digital assets_{General assembly}；

Arranging the digital assets according to the denomination from small to large to obtain a first data set;

adding the SUM of denominations SUM of the digital assets needing to be selected in the first data set to be larger than_{General assembly}Removing the digital assets to obtain a second data set;

SUM for judging SUM of denominations of first n digital assets_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the step that the number n required to be selected and the SUM SUM of the denominations of the digital assets required to be selected are determined according to the digital assets_{General assembly}”；

If not, making m equal to 1;

picking according to the second data setSelecting the first n-m digital assets, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m；

Removing the digital assets with single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

From the result set Ary_n-mSelecting m digital assets;

judging SUM of denominations SUM of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the step_n-mPicking out m digital assets ";

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

judging whether m is equal to n;

if not, making m equal to m +1, returning to the step, selecting the first n-m digital assets according to the second data set, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m”；

If yes, the process is ended.

2. The intelligent picking method of claim 1, wherein before the step of obtaining the first data set by ranking the digital assets according to their denominations from small to large, further comprising:

primarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

3. The intelligent pick method of claim 1, where from the result set Ary_n-mThe method for selecting the m digital assets specifically comprises the following steps:

when m is 1, Ary is selected from the result set_n-mSelecting 1 of the 1 st and the 1 st results with the absolute value of the difference value within the preset threshold rangeA digital asset;

from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

4. The intelligent selection method of claim 1, further comprising, after the step of if, then end, the steps of: and carrying out manual evaluation and selection, wherein the conditions of the manual evaluation and selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

5. An intelligent selection system, comprising:

the digital asset acquisition module is used for acquiring a plurality of digital assets;

a determining module for determining the number n to be selected and the SUM SUM of the denominations of the digital assets to be selected according to the digital assets_{General assembly}；

The first data set acquisition module is used for arranging the digital assets from small to large according to the denominations of the digital assets to obtain a first data set;

a second data set acquisition module for acquiring the SUM of denominations SUM of the digital assets needing to be selected, which is larger than the SUM of denominations SUM of the digital assets needing to be selected in the first data set_{General assembly}Removing the digital assets to obtain a second data set;

a first judging module for judging SUM of denominations SUM of the first n digital assets_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the determining module;

if not, making m equal to 1;

a first selection module for selecting the first n-m digital assets according to the second data set and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m；

A result set obtaining module, configured to remove the digital assets with a single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

A second selection module for selecting from said set of results Ary_n-mSelecting m digital assets;

a second judgment module for judging SUM of denominations SUM of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the second selecting module;

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

a third judging module, configured to judge whether m is equal to n;

if not, making m equal to m +1, and returning to the first selecting module;

if yes, the process is ended.

6. The intelligent culling system of claim 5, further comprising:

the preliminary screening module is used for preliminarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

7. The intelligent culling system of claim 5, wherein the second culling module comprises:

a first selecting subunit for selecting from the result set Ary when m is 1_n-mSelecting 1 digital asset of which the absolute value of the difference value between the 1 st result and the first result is within a preset threshold range;

a second pick subunit for picking from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

8. The intelligent culling system of claim 5, further comprising: the manual evaluation selection module is used for performing manual evaluation selection, and the conditions of the manual evaluation selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

9. An intelligent selection device comprising:

a processor; and

a memory having computer-readable program instructions stored therein,

wherein the intelligent picking method of any one of claims 1-4 is performed when the computer readable program instructions are executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the intelligent picking method according to any one of claims 1 to 4.

Technical Field

The invention relates to the technical field of intelligent selection, in particular to an intelligent selection method, an intelligent selection system, intelligent selection equipment and an intelligent selection medium.

Background

In the prior art, a permutation and combination (Cartesian product) mode is used during selection of digital assets, so that the requirements of an owner on credit, a payment time limit and an asset denomination of an enterprise are met, and an operator obtains an optimal combination scheme of asset liquidity, asset cost and income and multi-dimensional consideration and is used for negotiating the assets of financial services of both parties.

However, at present, an operator has more than 2 million digital assets, and still has huge statistical computation amount in a permutation and combination (cartesian product) mode when selecting the digital assets, the measurement and calculation response time of only one business scheme is longer than 5 minutes, and the existing statistical method cannot be applied to the increasingly huge digital assets.

Therefore, how to design an intelligent selection method, system, device and medium that can enable a company operator to quickly count a plurality of preferred combination schemes becomes a technical problem to be solved in the field.

Disclosure of Invention

The invention aims to provide an intelligent selection method, an intelligent selection system, intelligent selection equipment and an intelligent selection medium.

In order to achieve the purpose, the invention provides the following scheme:

an intelligent selection method, comprising the steps of:

acquiring a plurality of digital assets;

determining the number n to be selected and the SUM SUM of the denominations of the digital assets to be selected according to the digital assets_{General assembly}；

Arranging the digital assets according to the denomination from small to large to obtain a first data set;

adding the SUM of denominations SUM of the digital assets needing to be selected in the first data set to be larger than_{General assembly}Removing the digital assets to obtain a second data set;

determining the total denomination of the first n digital assetsAnd SUM_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the step that the number n required to be selected and the SUM SUM of the denominations of the digital assets required to be selected are determined according to the digital assets_{General assembly}”；

If not, making m equal to 1;

according to the second data set, selecting the first n-m digital assets, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m；

Removing the digital assets with single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

From the result set Ary_n-mSelecting m digital assets;

judging SUM of denominations SUM of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the step_n-mPicking out m digital assets ";

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

judging whether m is equal to n;

if not, making m equal to m +1, returning to the step, selecting the first n-m digital assets according to the second data set, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m”；

If yes, the process is ended.

Optionally, before the step of obtaining the first data set by ranking the digital assets according to their denominations from small to large, the method further includes:

primarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

Optionally, from the result set Ary_n-mThe method for selecting the m digital assets specifically comprises the following steps:

when m is 1, Ary is selected from the result set_n-mSelecting 1 digital asset of which the absolute value of the difference value between the 1 st result and the first result is within a preset threshold range;

from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

Optionally, after the step "if yes, then end", the method further includes: and carrying out manual evaluation and selection, wherein the conditions of the manual evaluation and selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

The invention also provides an intelligent selection system, which comprises:

the digital asset acquisition module is used for acquiring a plurality of digital assets;

a determining module for determining the number n to be selected and the SUM SUM of the denominations of the digital assets to be selected according to the digital assets_{General assembly}；

The first data set acquisition module is used for arranging the digital assets from small to large according to the denominations of the digital assets to obtain a first data set;

a second data set acquisition module for acquiring the SUM of denominations SUM of the digital assets needing to be selected, which is larger than the SUM of denominations SUM of the digital assets needing to be selected in the first data set_{General assembly}Removing the digital assets to obtain a second data set;

a first judging module for judging SUM of denominations SUM of the first n digital assets_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the determining module;

if not, making m equal to 1;

a first selection module for selecting the first n-m digital assets, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m；

A result set obtaining module, configured to remove the digital assets with a single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

A second selection module for selecting from said set of results Ary_n-mSelecting m digital assets;

a second judgment module for judging SUM of denominations SUM of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the second selecting module;

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

a third judging module, configured to judge whether m is equal to n;

if not, making m equal to m +1, and returning to the first selecting module;

if yes, the process is ended.

Optionally, the method further includes:

the preliminary screening module is used for preliminarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

Optionally, the second selecting module includes:

a first selecting subunit for selecting from the result set Ary when m is 1_n-mSelecting 1 digital asset of which the absolute value of the difference value between the 1 st result and the first result is within a preset threshold range;

a second pick subunit for picking from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

Optionally, the method further includes: the manual evaluation selection module is used for performing manual evaluation selection, and the conditions of the manual evaluation selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

The invention also provides an intelligent selecting device, comprising:

a processor; and

a memory having computer-readable program instructions stored therein,

wherein the intelligent picking method described above is performed when the computer readable program instructions are executed by the processor.

The invention also provides a computer-readable storage medium, on which a computer program is stored, which is characterized in that the program, when being executed by a processor, implements the steps of the intelligent selection method described above.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

the invention provides an intelligent selection method, a system, equipment and a medium, which can greatly reduce the operation times, can not increase the consumption time due to the doubling of the scale of digital assets, and can be suitable for a combination scheme of high-frequency trial calculation of financial assets. Through preliminary measurement and calculation, 500 assets are selected from 2 ten thousand digital assets, the digital asset consumption which is closest to 3 hundred million is about 8s, and the method is greatly superior to the traditional permutation and combination (Cartesian product) method.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

Fig. 1 is a flowchart of an intelligent selection method according to embodiment 1 of the present invention;

fig. 2 is a block diagram of an intelligent selection system according to embodiment 2 of the present invention;

FIG. 3 is a schematic diagram of a second data set;

FIG. 4 is a result set Ary₄₉₉A schematic diagram of (a);

FIG. 5 is a result set Ary₄₉₈Schematic illustration of

FIG. 6 is a schematic illustration of picking digital assets from a result set;

FIG. 7 is a schematic illustration of determining a final digital asset from the result set;

FIG. 8 is an architecture diagram of a computing device.

Description of the symbols:

1. a digital asset acquisition module; 2. a determination module; 3. a first data set acquisition module; 4. a second data set acquisition module; 5. a first judgment module; 6. a first selecting module; 7. a result set acquisition module; 8. a second selecting module; 9. a second judgment module; 10. and a third judging module.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.

As used in this disclosure and in the claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Although the present invention makes various references to certain modules in a system according to embodiments of the present invention, any number of different modules may be used and run on a user terminal and/or server. The modules are merely illustrative and different aspects of the systems and methods may use different modules.

Flow charts are used in the present invention to illustrate the operations performed by a system according to embodiments of the present invention. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously, as desired. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

The invention aims to provide an intelligent selection method, an intelligent selection system, intelligent selection equipment and an intelligent selection medium.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

Example 1:

referring to fig. 1, the present invention provides an intelligent selection method, which includes the following steps:

s1: acquiring a plurality of digital assets;

s2: determining the number n to be selected and the SUM SUM of the denominations of the digital assets to be selected according to the digital assets_{General assembly}；

S3: arranging the digital assets according to the denomination from small to large to obtain a first data set;

s4: adding the SUM of denominations SUM of the digital assets needing to be selected in the first data set to be larger than_{General assembly}Removing the digital assets to obtain a second data set;

s5: SUM for judging SUM of denominations of first n digital assets_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the step of determining to select according to the digital assetsN and SUM of denominations SUM of digital assets to be picked_{General assembly}”；

If not, making m equal to 1;

s6: according to the second data set, selecting the first n-m digital assets, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m；

S7: removing the digital assets with single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

S8: from the result set Ary_n-mSelecting m digital assets;

s9: judging SUM of denominations SUM of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the step_n-mPicking out m digital assets ";

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

s10: judging whether m is equal to n;

if not, making m equal to m +1, returning to the step, selecting the first n-m digital assets according to the second data set, and adding and calculating the SUM SUM of the denominations of the first n-m digital assets_n-m”；

If yes, the process is ended.

Before step S3, the method further includes:

primarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

Wherein the digital asset type screening supports: business ticket, bank ticket, account receivable and Bao Wutong Bao. The financial institution gives the core enterprise an estimated credit line, for example: eight steel surplus credit lines 9500 ten thousand and treasure steel resource surplus credit lines 1.5 million yuan. The date of redemption typically cannot be later than the last expiration date of the collaborative "financial asset management service".

In step S8, Ary is selected from the result set_n-mThe method for selecting the m digital assets specifically comprises the following steps:

s81: when m is 1, Ary is selected from the result set_n-mSelecting 1 digital asset of which the absolute value of the difference value between the 1 st result and the first result is within a preset threshold range;

s82: from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

After the step "if, then end", further include: and carrying out manual evaluation and selection, wherein the conditions of the manual evaluation and selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

In conclusion, the invention provides an intelligent selection method which gives consideration to three aspects of operation precision, full sample coverage and calculation power consumption, the method can greatly reduce operation times, the consumption time can not be increased due to the fact that the scale of the digital assets is multiplied, and the method can be suitable for a combination scheme of high-frequency trial calculation of financial assets.

The working principle of the invention is explained below in connection with practical applications:

for example, 500 digital assets are selected from 2 ten thousand digital assets, and several schemes with the nearest 3 hundred million digital assets are taken as examples. The business scene needs a scheme that the sum of 500 numbers is exactly 3 hundred million or close to 3 hundred million, and finally, the optimal combination is selected through manually evaluating the denomination, the deadline and the mobility of the assets. The method comprises the following steps:

m1: the digital assets are ranked from small to large in denomination and digital assets with individual asset denominations greater than 3 billion are culled, and a schematic diagram is shown in fig. 3.

M2: selecting the first 499(500-1) digital assets, adding the denominations to obtain SUM₄₉₉And (5) Yuan. Note that the sorted digital assets, e.g.The sum of the first 499 assets of a fruit is more than 3 hundred million, and the result can not be obtained. The target needs to be adjusted, such as: the 300 assets sum to the nearest 3 hundred million.

Rejecting single denominations greater than (300,000,000-SUM)₄₉₉) Meta digital assets, resulting in a result set Ary₄₉₉A schematic diagram of which is shown in fig. 4. From Ary₄₉₉Pick out the closest (300,000,000-SUM)₄₉₉) One asset R of the element₄₉₉. Hypothetical SUM₄₉₉And the sum is 27850.2 ten thousand yuan, then the assets of 2289.8 ten thousand and 29890.8 thousand are removed, and Ary is the rest assets₄₉₉One asset satisfying 3 billion requirements is selected. Asset R_{499 is}2149.8 trillion, exactly 3 hundred million, the round ends.

Taking a first optimal result set: front 499 digital assets + R₄₉₉Stored as one of the output schemes.

M3: selecting front 498(500-2) assets, adding the denominations to obtain SUM₄₉₈And (5) Yuan.

The first step is as follows: rejecting single denominations greater than (300,000,000-SUM)₄₉₈) Meta asset, get result set Ary₄₉₈(ii) a A schematic diagram of which is shown in fig. 5.

The second step is that: from Ary₄₉₈Pick out the closest (300,000,000-SUM) in the set₄₉₈) Two digital assets of a member; the closest meaning here is the SUM of the two digital assets chosen and (300,000,000-SUM)₄₉₈) Is determined to be the closest (300,000,000-SUM) if the absolute value of the result is within a predetermined threshold range₄₉₈) Two digital assets of a member. The method comprises the following specific steps:

alternative L1₄₉₈Find the closest (300,000,000-SUM)₄₉₈-L1₄₉₈) Monetary asset F1₄₉₈；

Alternative L2₄₉₈Find the closest (300,000,000-SUM)₄₉₈-L2₄₉₈) Monetary asset F2₄₉₈(ii) a A schematic diagram thereof is shown in fig. 6;

by analogy, a number of LN498+ FN498 combinations are obtained, the closest (300,000,000-SUM)₄₉₈) Unique result of the element: r1₄₉₈、R2₄₉₈Combination ofStored as one of the output schemes, as shown in fig. 7.

It should be noted that, since the digital assets are arranged from small to large in sequence, it is likely that the digital assets are arranged in Ary₄₉₈There are multiple groups of close to or equal to (300,000,000-SUM) in the collection₄₉₈) Meta results, therefore, only the SUM of the first set of digital assets and (300,000,000-SUM)₄₉₈) And outputting the absolute value of the difference result within the range of the preset threshold value, and jumping out of the cycle.

Taking a second optimal result set: front 498 digital assets + R1₄₉₈+R2₄₉₈Stored as one of the output schemes.

M4: selecting the top 497(500-3) assets, adding the denominations to obtain SUM₄₉₇And (5) Yuan.

Taking the statistical method of step M3 as an example, a third optimal result set can be obtained in the same way: 497 front digital asset + R1₄₉₇+R2₄₉₇+R3₄₉₇Stored as one of the output schemes.

In this way, the first 499 result sets are subjected to the number-making, the second 498 result sets are subjected to the number-making, the second 497 result sets are subjected to the number-making, the second 496 result sets are subjected to the number-making, and the same as the algorithm of the step M3 is performed until the first 1 result set is subjected to the number-making.

M5: and obtaining a plurality of preferred result sets meeting the requirements of the exchange payment duration and the asset denomination from the steps.

Through preliminary measurement and calculation, 500 assets are selected from 2 ten thousand digital assets, the digital asset consumption which is closest to 3 hundred million is about 8s, and the method is greatly superior to the traditional permutation and combination (Cartesian product) method.

The operator then selects through manual evaluation by the flowability of the digital product (poor flowability with a relatively low credit rating). And the operator obtains the asset income through an industry standard formula, and further manually evaluates and selects:

asset remaining days is asset redemption period-service roll-out date.

Asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

And finally, selecting an optimal combination scheme for carrying out negotiation financial resource management business based on the high and low liquidity of the assets and the high and low income of the business.

The technical scheme of the invention is used for the initial measurement and calculation of the financial industry asset operation party and the fund provider and the cooperative income. The workload of the early-stage manual asset screening scheme is greatly reduced through an algorithm, and limited manual work is concentrated on the final screening decision.

Example 2:

referring to fig. 2, the present invention further provides an intelligent selecting system, which includes:

the digital asset acquisition module 1 is used for acquiring a plurality of digital assets;

a determining module 2, configured to determine the number n to be selected and the SUM of denominations SUM of the digital assets to be selected according to the plurality of digital assets_{General assembly}；

The first data set acquisition module 3 is used for arranging the digital assets from small to large according to the denominations of the digital assets to obtain a first data set;

a second data set obtaining module 4, configured to obtain the SUM of denominations SUM of the digital assets needing to be selected, which is greater than the SUM of denominations SUM of the digital assets needing to be selected in the first data set_{General assembly}Removing the digital assets to obtain a second data set;

a first judging module 5, configured to judge the SUM of the denominations of the first n digital assets_nWhether the SUM of the denominations of the digital assets needing to be selected is larger than SUM_{General assembly}；

If yes, returning to the determining module 2;

if not, making m equal to 1;

a first selecting module 6, configured to select the first n-m digital assets according to the second data set, and add and calculate a SUM of denominations SUM of the first n-m digital assets_n-m；

A result set obtaining module 7, configured to remove the digital assets with a single denomination larger than the first result and the first n-m digital assets in the second data set to obtain a result set Ary_n-m(ii) a The first result is a SUM_{General assembly}-SUM_n-m；

A second selection module 8 for selecting from said set of results Ary_n-mSelecting m digital assets;

a second judging module 9 for judging the SUM SUM of the denominations of the m digital assets_mWhether the absolute value of the difference value with the first result is within a preset threshold range;

if not, returning to the second selecting module 8;

if yes, taking the first n-m digital assets and the m digital assets as an m-th optimal result set;

a third judging module 10, configured to judge whether m is equal to n;

if not, making m equal to m +1, and returning to the first selecting module 6;

if yes, the process is ended.

Further comprising:

the preliminary screening module is used for preliminarily screening the digital assets according to screening conditions, wherein the screening conditions comprise: asset type, core enterprise credit line and cashing deadline condition.

The second selection module 8 comprises:

a first selecting subunit for selecting from the result set Ary when m is 1_n-mSelecting 1 digital asset of which the absolute value of the difference value between the 1 st result and the first result is within a preset threshold range;

a second pick subunit for picking from the result set Ary when m ≠ 1_n-mThe m digital assets of the 1 st group of digital assets with the absolute value of the difference value of the first result within the preset threshold value range are selected.

Further comprising: the manual evaluation selection module is used for performing manual evaluation selection, and the conditions of the manual evaluation selection are as follows:

the asset remaining days are the asset exchange period-service roll-out date;

asset revenue-asset denomination (capital cost interest rate-discount interest rate) asset remaining days/360.

Example 3:

the method or apparatus according to embodiments of the invention may also be implemented by means of the architecture of a computing device as shown in fig. 8. Fig. 8 illustrates an architecture of the computing device. As shown in figure 8 of the drawings,

the computing device 11 may include a bus 111, one or at least two CPUs 112, a Read Only Memory (ROM)113, a Random Access Memory (RAM)114, a communication port 115 to connect to a network, an input/output component 116, a hard disk 117, and the like. A storage device in the computing device 11, such as the read only memory 113 or the hard disk 117, may store various data or files used for processing and/or communication of the login authorization management method provided by the present invention and program instructions executed by the CPU. Computing device 11 may also include user interface 118. Of course, the architecture shown in FIG. 8 is merely exemplary, and one or at least two of the components in the computing device shown in FIG. 8 may be omitted when implementing different devices, as desired.

According to another aspect of the present invention, there is also provided a non-transitory computer readable storage medium having stored thereon computer readable instructions which, when executed by a computer, can perform the method as described above.

Portions of the technology may be considered "articles" or "articles of manufacture" in the form of executable code and/or associated data, which may be embodied or carried out by a computer readable medium. Tangible, non-transitory storage media may include memory or storage for use by any computer, processor, or similar device or associated module. For example, various semiconductor memories, tape drives, disk drives, or any similar device capable of providing a storage function for software.

All or a portion of the software may sometimes communicate over a network, such as the internet or other communication network. Such communication may load software from one computer device or processor to another. For example: from a server or host computer of the video object detection device to a hardware platform of a computer environment, or other computer environment implementing a system, or similar functionality related to providing information needed for object detection. Thus, another medium capable of transferring software elements may also be used as a physical connection between local devices, such as optical, electrical, electromagnetic waves, etc., propagating through cables, optical cables, air, etc. The physical medium used for the carrier wave, such as an electric, wireless or optical cable or the like, may also be considered as the medium carrying the software. As used herein, unless limited to a tangible "storage" medium, other terms referring to a computer or machine "readable medium" refer to media that participate in the execution of any instructions by a processor.

The present invention has been described using specific terms to describe embodiments of the invention. Such as "first/second embodiment," "an embodiment," and/or "some embodiments" means a feature, structure, or characteristic described in connection with at least one embodiment of the invention. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some of the features, structures, or characteristics of one or more embodiments of the present invention may be combined as suitable.

Moreover, those skilled in the art will appreciate that aspects of the invention may be illustrated and described as embodied in several forms or conditions of patentability, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereof. Accordingly, aspects of the present invention may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present invention may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The foregoing is illustrative of the present invention and is not to be construed as limiting thereof. Although a few exemplary embodiments of this invention have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of this invention. Accordingly, all such modifications are intended to be included within the scope of this invention as defined in the claims. It is to be understood that the foregoing is illustrative of the present invention and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims. The invention is defined by the claims and their equivalents.