阅读说明：本技术 一种基于机器学习的人工智能算法交易辅助设备 (Artificial intelligence algorithm transaction auxiliary assembly based on machine learning ) 是由 于宗文 于 2021-08-09 设计创作，主要内容包括：本发明涉及算法交易技术领域,尤其涉及一种基于机器学习的人工智能算法交易辅助设备。包括底框,底框底部有活动脚轮,底框内有滑槽、底座、弹簧A,底座上有支撑框、缓冲组件,支撑框内有散热箱,散热箱内有过滤板、冷却器、过滤筛、所述散热箱上设有机箱,机箱两侧与底框内两侧之间和散热箱内均有多个散热组件,散热组件包括转动轴、扇叶、齿轮、齿轮转块、电机,机箱内基于机器学习的人工智能算法交易方法实现过程包括：搜集市场数据信息、机器学习数据信息、机器学习数据模型、设计风控系统、现场实盘交易。本发明的在于提出了一种可移动、散热及减震效果良好,增加计算机使用寿命的基于机器学习的人工智能算法交易辅助设备。(The invention relates to the technical field of algorithm transaction, in particular to artificial intelligence algorithm transaction auxiliary equipment based on machine learning. Including the underframe, there is movable truckle underframe bottom, has spout, base, spring A in the underframe, has carriage, buffering subassembly on the base, has the heat dissipation case in the carriage, and the heat dissipation incasement has filter, cooler, filter sieve be equipped with quick-witted case on the heat dissipation case, all have a plurality of radiator unit between the both sides in quick-witted case both sides and the underframe and in the heat dissipation case, radiator unit includes axis of rotation, flabellum, gear commentaries on classics piece, motor, and machine incasement includes based on machine learning's artificial intelligence algorithm transaction method implementation process: collecting market data information, machine learning data models, designing a wind control system and performing field real disk transaction. The invention provides the machine learning-based artificial intelligence algorithm transaction auxiliary equipment which is movable, has good heat dissipation and shock absorption effects and prolongs the service life of a computer.)

1. An artificial intelligence algorithm transaction auxiliary equipment based on machine learning, its characterized in that: comprises a bottom frame (1), a plurality of movable trundles (2) are arranged at the bottom of the bottom frame (1), a sliding groove (3) is arranged in the bottom frame (1), a base (4) is arranged on the sliding groove (3), the sliding groove (3) is connected with the base (4) through a spring A (3.1), a supporting frame (5) is arranged on the base (4), the base (4) is connected with the supporting frame (5) through a plurality of buffer components (6), a heat dissipation box (7) is arranged in the supporting frame (5), a filter plate (7.1) is arranged in the heat dissipation box (7), a cooler (7.2) is arranged on the filter plate (7.1), a filter sieve (7.3) is arranged on the cooler (7), a machine case (9) is arranged on the heat dissipation box (7), two sides of the machine case (9) are connected with the bottom frame (1) through a plurality of springs C (10), fixed blocks (11) are arranged between two sides of the case (9) and two sides of the bottom frame (1), a plurality of heat dissipation assemblies (8) are arranged between two sides of the case (9) and the bottom frame (1) and in the heat dissipation box (7), each heat dissipation assembly (8) comprises a plurality of ventilation assemblies (8.8), each ventilation assembly (8.8) comprises a rotating shaft (8.1), fan blades (8.2) are arranged at one end of each rotating shaft (8.1), gears (8.3) are arranged on the rotating shafts (8.1), a plurality of gear rotating blocks (8.4) are arranged on the gears (8.3), two adjacent ventilation assemblies (8.8) are connected with each other through the gear rotating blocks (8.4) in an engaged mode, one rotating shaft (8.1) of each ventilation assembly (8.8) penetrates through the heat dissipation box (7) and the supporting frame (5), one rotating shaft (8.1) is far away from one end of each fan blade (8.2) and is provided with a motor (8.5), the motor (8.5) is arranged at the bottom of the supporting frame (5), and the machine learning-based artificial intelligence algorithm transaction method in the case (9) is implemented by the following steps: collecting market data information, machine learning data models, designing a wind control system and performing field real disk transaction.

2. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: and a locking structure is arranged on the movable caster (2).

3. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: and a sliding block (3.2) for the sliding of the sliding chute (3) is arranged at the bottom of the spring A (3.1).

4. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: buffering subassembly (6) include with base (4) fixed connection's sleeve A (6.1) and with carriage (5) fixed connection's sleeve B (6.2), be connected through spring B (6.3) between sleeve A (6.1) and sleeve B (6.2), sleeve A (6.1) both sides all are equipped with fixed lug (6.4), sleeve B (6.2) both sides all are equipped with guide cylinder (6.5), be equipped with bracing piece (6.6) that run through guide cylinder (6.5) on fixed lug (6.4), be equipped with the block rubber on bracing piece (6.6).

5. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: the motor (8.5) bottom is equipped with support frame (8.6) with carriage (5) fixed connection, the both ends of radiator unit (8) all are equipped with dead lever (8.7).

6. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: the bottom of the heat dissipation box (7) and the bottom of the support frame (5) are provided with small ventilation holes.

7. The machine learning based artificial intelligence algorithm transaction assistance device of claim 1, wherein: the step of collecting market data information is to make data information such as buying and selling prices, latest prices, short-term change trends and the like in the market into a data table for machine learning; the machine learning data information is obtained by analyzing and mining data in a data table and obtaining a primary decision formula through machine learning; the machine learning data model is used for establishing a data model, adjusting parameters, carrying out analysis processing and optimizing a decision formula through machine learning; the design of the wind control system is to improve the wind control processing strategy service, and perform performance analysis, order verification and compliance inspection through the wind control system; the field real disk transaction is to supply real-time data, and the machine can realize real-time transaction by performing market analysis, model compiling and transaction entrusting in a programmed way.

Technical Field

The invention relates to the technical field of algorithm transaction, in particular to artificial intelligence algorithm transaction auxiliary equipment based on machine learning.

Background

Algorithmic transactions, also known as automated transactions, black box transactions, utilize an electronic platform to input transaction instructions related to an algorithm to implement a pre-established transaction strategy. Many variables are included in the algorithm, including time, price, transaction amount, or in many cases, instructions are initiated by the "robot" without manual intervention. Algorithmic trading is widely used in investment banks, pension funds, mutual funds, and other buyer organization investors to segment large trades into many smaller trades to cope with market risk and shock, and the categories of algorithmic trading include: alpha trading strategy, trading execution strategy and marketing strategy, the most used in the market at present are: the computer IS a device in machine learning artificial intelligence algorithm transaction, but the existing computer case for machine learning artificial intelligence algorithm transaction cannot move randomly when in use, IS complex to carry, has poor heat dissipation effect and shock absorption effect, and influences service life.

Disclosure of Invention

The invention provides the artificial intelligence algorithm transaction auxiliary equipment which is movable, has good heat dissipation and shock absorption effects and is based on machine learning, and provided with a perfect algorithm system.

The technical scheme adopted by the invention is as follows: an artificial intelligence algorithm transaction auxiliary equipment based on machine learning, its characterized in that: comprises a bottom frame, a plurality of movable trundles are arranged at the bottom of the bottom frame, a chute is arranged in the bottom frame, a base is arranged on the chute, the chute is connected with the base through a spring A, a support frame is arranged on the base, the base is connected with the support frame through a plurality of buffer components, a heat dissipation box is arranged in the support frame, a filter plate is arranged in the heat dissipation box, a cooler is arranged on the filter plate, a filter screen is arranged on the cooler, the filter screen is arranged at the top of the heat dissipation box, a case is arranged on the heat dissipation box, two sides of the case are connected with the bottom frame through a plurality of springs C, fixed blocks are arranged between two sides of the case and two sides in the bottom frame, a plurality of heat dissipation components are arranged between two sides of the case and two sides in the bottom frame and in the heat dissipation box, each heat dissipation component comprises a plurality of ventilation components, and each ventilation component comprises a rotating shaft, the machine is characterized in that one end of the rotating shaft is provided with fan blades, the rotating shaft is provided with a gear, the gear is provided with a plurality of gear rotating blocks, two adjacent ventilation assemblies are connected through the gear rotating blocks in an meshed mode, one of the ventilation assemblies penetrates through the rotating shaft of the heat dissipation box and the supporting frame, one of the ventilation assemblies is arranged at one end, away from the fan blades, of the rotating shaft and is provided with a motor, the motor is arranged at the bottom of the supporting frame, and the machine case comprises an artificial intelligence algorithm transaction method implementation process based on machine learning: collecting market data information, machine learning data models, designing a wind control system and performing field real disk transaction.

And a locking structure is arranged on the movable caster.

And a sliding block for sliding the sliding groove is arranged at the bottom of the spring A.

The buffering assembly comprises a sleeve A fixedly connected with the base and a sleeve B fixedly connected with the supporting frame, the sleeve A is connected with the sleeve B through a spring B, fixed lugs are arranged on two sides of the sleeve A, guide cylinders are arranged on two sides of the sleeve B, supporting rods penetrating through the guide cylinders are arranged on the fixed lugs, and rubber blocks are arranged on the supporting rods.

The motor bottom is equipped with the support frame with carriage fixed connection, radiator unit's both ends all are equipped with the dead lever.

And the bottom of the heat dissipation box and the bottom of the support frame are both provided with small ventilation holes.

The step of collecting market data information is to make data information such as buying and selling prices, latest prices, short-term change trends and the like in the market into a data table for machine learning; the machine learning data information is obtained by analyzing and mining data in a data table and obtaining a primary decision formula through machine learning; the machine learning data model is used for establishing a data model, adjusting parameters, carrying out analysis processing and optimizing a decision formula through machine learning; the design of the wind control system is to improve the wind control processing strategy service, and perform performance analysis, order verification and compliance inspection through the wind control system; the field real disk transaction is to supply real-time data, and the machine can realize real-time transaction by performing market analysis, model compiling and transaction entrusting in a programmed way.

The invention has the beneficial effects that:

the invention can be moved and fixed at will, is provided with a chute and a sliding block, can play a role of shock absorption when the case vibrates, is provided with a buffer component, can play a role of shock absorption in the vertical direction when the case vibrates, is provided with a spring C, can play a role of shock absorption in the horizontal direction when the case vibrates, is provided with a heat dissipation component, can start a motor when the case is heated and scalded after long-time operation, can increase the dissipation of heat inside the case by the wind blown out by fan blades passing through the case, so that parts in the case reach proper operation temperature, can prolong the service life of each part, has long-time fluidity and continuity of a data set in an established transaction algorithm, has proper machine learning strategies and transaction strategies, and can realize the function of field transaction.

Drawings

FIG. 1 is a schematic diagram of the overall structure of an artificial intelligence algorithm transaction auxiliary device based on machine learning according to the present invention;

FIG. 2 is a schematic diagram of the internal structure of a heat dissipation box of the transaction auxiliary equipment based on the machine learning artificial intelligence algorithm;

FIG. 3 is a schematic diagram of a partial structure of an artificial intelligence algorithm transaction auxiliary device A based on machine learning.

As shown in the figure: 1. a bottom frame; 2. a movable caster; 3. a chute; 3.1, a spring A; 3.2, a sliding block; 4. a base; 5. a support frame; 6. a buffer assembly; 6.1, sleeve A; 6.2, sleeve B; 6.3, spring B; 6.4, fixing the bump; 6.5, a guide cylinder; 6.6, supporting rods; 7. a heat dissipation box; 7.1, a filter plate; 7.2, a cooler; 7.3, filtering and screening; 8. a heat dissipating component; 8.1, a rotating shaft; 8.2, fan blades; 8.3, a gear; 8.4, a gear rotating block; 8.5, a motor; 8.6, a support frame; 8.7, fixing the rod; 8.8, a ventilation component; 9. a chassis; 10. a spring C; 11. and (5) fixing blocks.

Detailed Description

An artificial intelligence algorithm transaction auxiliary equipment based on machine learning, its characterized in that: comprises a bottom frame 1, a plurality of movable trundles 2 are arranged at the bottom of the bottom frame 1, a chute 3 is arranged in the bottom frame 1, a base 4 is arranged on the chute 3, the chute 3 is connected with the base 4 through a spring A3.1, a support frame 5 is arranged on the base 4, the base 4 is connected with the support frame 5 through a plurality of buffer components 6, a heat dissipation box 7 is arranged in the support frame 5, a filter plate 7.1 is arranged in the heat dissipation box 7, a cooler 7.2 is arranged on the filter plate 7.1, a filter sieve 7.3 is arranged on the cooler 7.2, the filter sieve 7.3 is arranged at the top of the heat dissipation box 7, a machine box 9 is arranged on the heat dissipation box 7, two sides of the machine box 9 are connected with the bottom frame 1 through a plurality of springs C10, fixed blocks 11 are arranged between two sides of the machine box 9 and two sides in the bottom frame 1 and a plurality of heat dissipation components 8 are arranged in the heat dissipation box 7, the heat dissipation assembly 8 comprises a plurality of ventilation assemblies 8.8, the ventilation assemblies 8.8 include rotation axis 8.1, rotation axis 8.1 one end is equipped with flabellum 8.2, be equipped with gear 8.3 on the rotation axis 8.1, be equipped with a plurality of gear commentaries on classics piece 8.4 on the gear 8.3, change piece 8.4 intermeshing through the gear between two adjacent ventilation assemblies 8.8 and connect, one of them the rotation axis 8.1 of ventilation assemblies 8.8 runs through heat dissipation case 7 and carriage 5, one of them rotation axis 8.1 is kept away from flabellum 8.2 one end and is equipped with motor 8.5, motor 8.5 sets up in carriage 5 bottom, machine case 9 is interior based on machine learning's artificial intelligence algorithm transaction method implementation process and includes: collecting market data information, machine learning data models, designing a wind control system and performing field real disk transaction.

And a locking structure is arranged on the movable caster 2.

And a sliding block 3.2 for the sliding of the sliding chute 3 is arranged at the bottom of the spring A3.1.

Buffer unit 6 includes sleeve A6.1 with 4 fixed connection of base and sleeve B6.2 with 5 fixed connection of carriage, be connected through spring B6.3 between sleeve A6.1 and the sleeve B6.2, sleeve A6.1 both sides all are equipped with fixed lug 6.4, sleeve B6.2 both sides all are equipped with guide cylinder 6.5, be equipped with the bracing piece 6.6 that runs through guide cylinder 6.5 on the fixed lug 6.4, be equipped with the block rubber on the bracing piece 6.6.

The bottom of the motor 8.5 is provided with a support frame 8.6 fixedly connected with the support frame 5, and both ends of the heat dissipation assembly 8 are provided with fixing rods 8.7.

And small ventilation holes are formed in the bottom of the heat dissipation box 7 and the bottom of the support frame 5.

The step of collecting market data information is to make data information such as buying and selling prices, latest prices, short-term change trends and the like in the market into a data table for machine learning; the machine learning data information is obtained by analyzing and mining data in a data table and obtaining a primary decision formula through machine learning; the machine learning data model is used for establishing a data model, adjusting parameters, carrying out analysis processing and optimizing a decision formula through machine learning; the design of the wind control system is to improve the wind control processing strategy service, and perform performance analysis, order verification and compliance inspection through the wind control system; the field real disk transaction is to supply real-time data, and the machine can realize real-time transaction by performing market analysis, model compiling and transaction entrusting in a programmed way.

In the artificial intelligence algorithm transaction auxiliary equipment based on machine learning, the auxiliary equipment is pushed to a proper position, the locking structure on the movable caster 2 is stepped by feet to fix the equipment, the case 9 of the computer is placed into the bottom frame 1 and fixed by the fixing block 11, the case 9 is started, and the following steps are sequentially completed: making data information such as buying and selling prices, latest prices, short-term change trends and the like in the market into a data table for machine learning; analyzing and mining the data in the data table, and obtaining a primary decision formula through machine learning; establishing a data model, adjusting parameters, carrying out analysis processing, and optimizing a decision formula through machine learning; improving the wind control processing strategy service, and performing performance analysis, order verification and compliance inspection through a wind control system; real-time data is supplied, and the machine carries out market analysis, model compiling and transaction entrusting in a programmed mode, so that real-time transaction can be realized. When the computer is used, the case 9 can vibrate, when the base 4 moves downwards, the spring A3.1 can move downwards, and the sliding block 3.2 is arranged below the spring A3.1 and can move in an arc on the sliding groove 3, so that the damping effect is achieved; when the case 9 moves downwards, the spring B6.3 in the buffer assembly 6 also moves downwards, so that the sleeve a6.1 and the sleeve B6.2 are close to each other, and when the height of the sleeve B6.2 is equal to that of the support rod 6.6, the rubber block contacts the bottom of the support frame 5, so that the horizontal shock absorption effect is achieved, and the support frame 5 is protected; the fixing block 11 can fix the case left and right, and when the case 1 slightly shakes left and right, the spring C10 moves left and right to prevent the case 9 from impacting the bottom frame 1 and being damaged; can generate heat and scald after quick-witted case 9 long-time operation, 8.5 backs of starter motor, axis of rotation 8.1 follows the rotation, make flabellum 8.2 also along with rotating, gear commentaries on classics piece 8.4 also along with rotating simultaneously, take other ventilation assembly 8.8 to rotate, blow to quick-witted case 9 inside, be equipped with cooler 7.2 simultaneously, can blow off microthermal wind, increase the thermal scattering and disappearing of quick-witted case 9 internals, make each spare part can reach suitable operating temperature, be equipped with filter 7.1 and filter sieve 7.3, can filter the wind that blows off, reduce the damage to quick-witted case 9 internals, reduce the entering of dust in the air simultaneously, increase the life of the inside parts of quick-witted case 9.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.