An economic financial economic trend curve simulation device

Abstract

This invention relates to the field of economics and finance, and provides an economic and financial trend curve simulation device. The device comprises a housing, electric slide rails, a connecting rope, moving blocks, a winding box, and a data transmission and control module. Several electric slide rails are installed inside the housing, and the moving blocks slide in conjunction with the slide rails. One end of the connecting rope is connected to the left moving block, and the other end passes through the remaining moving blocks and the housing to the winding box. The data transmission and control module is located below the winding box. The beneficial effects of this invention are: by physically plotting curves, users can intuitively experience changes in economic and financial trends, enhancing their understanding and retention of data; by employing advanced algorithms and high-precision mechanical components, the accuracy of each stage of data processing and curve plotting is strictly controlled, accurately simulating complex trend curves; and by supporting multiple data input methods and different types of economic and financial data, it can effectively simulate and analyze various types of economic and financial data.

Description

Technical Field

[0001] This invention relates to the field of economic and financial technology, specifically to an economic and financial trend curve simulation device. Background Technology

[0002] In the economic and financial fields, accurately grasping economic and financial trends is crucial for practitioners, researchers, and policymakers. Trend curves, as a tool that intuitively displays how economic and financial data changes over time, can help relevant personnel quickly understand the patterns behind the data and thus make informed decisions.

[0003] Existing physical simulation equipment mostly uses simple mechanical structures, such as just a few links and sliders to represent trends. When faced with complex economic and financial data, it cannot accurately present key characteristics such as data fluctuations and cyclical changes. Its functional limitations make it unable to meet the growing professional needs. Summary of the Invention

[0004] The purpose of this invention is to provide an economic and financial trend curve simulation device, which solves the problem that when dealing with complex economic and financial data, it is impossible to accurately present key characteristics such as data fluctuations and cyclical changes, and the limitations of its functions make it unable to meet the growing professional needs.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows:

[0006] An economic and financial trend curve simulation device includes a housing, electric slide rails, connecting ropes, and moving blocks. The electric slide rails are arranged in a plurality of units, all installed within the housing. The number of moving blocks corresponds to the number of electric slide rails, with each moving block fitted onto and slidingly engaging with one of the electric slide rails. A winding box is located on the right side of the housing. One end of the connecting rope is fixedly connected to a moving block on the left side, and the other end of the connecting rope passes through the remaining moving blocks and the housing, extending into the winding box. A data transmission and control module is located below the winding box.

[0007] As an improvement, each of the several movable blocks is provided with a rotatable roller, and each of the several movable blocks has an opening on both sides. One end of the connecting rope is connected to the left roller, and the connecting rope passes through the several openings and is wrapped around the several rollers to reduce the friction of the connecting line.

[0008] As an improvement, a slot is provided on the right side of the outer casing, and a ruler spring is provided inside the winding box. The other end of the connecting rope passes through the slot and is wound around the ruler spring, which can automatically tighten the connecting line.

[0009] As an improvement, the data transmission and control module is equipped with a USB interface and a Bluetooth module, and the data transmission and control module has a built-in data processor, making the device more convenient to use.

[0010] As an improvement, the data processor functions include: data preprocessing: after data input, it first passes through a data cleaning module. This module uses preset rules and algorithms to automatically identify and remove outliers and erroneous data in the data, smooths the data through a denoising algorithm to remove noise interference generated during data acquisition, and uses a normalization algorithm to uniformly map data of different magnitudes to the [0, 1] interval to ensure data consistency and comparability, providing a reliable data foundation for subsequent simulation analysis;

[0011] Trend simulation algorithm: The algorithm mainly uses the LSTM model under the deep learning framework, combined with the traditional ARIMA algorithm for trend simulation. The LSTM model can effectively capture long-term dependencies in the data and has good adaptability to complex economic and financial time series data. The ARIMA algorithm has advantages in processing short-term trend changes and periodic data. By organically combining the two and training and optimizing based on a large amount of historical economic and financial data, the model can accurately predict future trends and generate corresponding curve coordinate data.

[0012] Real-time updates and corrections: The device is equipped with a real-time data acquisition interface, which can obtain the latest economic and financial data in real time through network connection. Once new data is input, the device will automatically trigger a real-time update mechanism, using incremental learning algorithms to update and optimize the existing model, thereby correcting the simulated curve in real time, ensuring that the curve always reflects the latest economic and financial trend changes, and making the data more accurate.

[0013] The beneficial effects of this invention are as follows: by drawing physical curves, users can more intuitively perceive changes in economic and financial trends, enhance their understanding and memory of data, and use advanced algorithms and high-precision mechanical components to strictly control the accuracy of every step from data processing to curve drawing. It can accurately simulate various complex economic and financial trend curves, and supports multiple data input methods and different types of economic and financial data. Whether it is macroeconomic indicators, financial market data or corporate financial data, it can perform effective simulation analysis. Attached Figure Description

[0014] Figure 1 This is a front view of an economic and financial trend curve simulation device according to the present invention;

[0015] Figure 2 This is an internal schematic diagram of an economic and financial trend curve simulation device according to the present invention;

[0016] Figure 3 This is an enlarged view of point A in the economic and financial trend curve simulation device of the present invention.

[0017] In the diagram: 1. Outer shell; 2. Electric slide rail; 3. Moving block; 4. Connecting rope; 5. Data transmission and control module; 6. Rewind box; 7. Slot; 8. Ruler spring; 9. Opening; 10. Roller. Detailed Implementation

[0018] To make the content of this invention easier to understand, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Identical components are represented by the same reference numerals. It should be noted that the terms "front," "rear," "left," "right," "up," and "down" used in the following description refer to directions in the accompanying drawings, while the terms "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0019] like Figure 1 and Figure 3 As shown, an economic and financial trend curve simulation device includes a housing 1, electric slide rails 2, connecting ropes 4, and moving blocks 3. There are several electric slide rails 2, all of which are installed inside the housing 1. The number of moving blocks 3 corresponds to the number of electric slide rails 2. The moving blocks 3 are respectively fitted onto the electric slide rails 2 and slide in cooperation with them. A winding box 6 is provided on the right side of the housing 1. One end of the connecting rope 4 is fixedly connected to the moving block 3 on the left side, and the other end of the connecting rope 4 passes through the remaining moving blocks 3 and the housing 1 and extends into the winding box 6. A data transmission and control module 5 is provided below the winding box 6.

[0020] Each of the movable blocks 3 has a rotatable roller 10 inside. Each of the movable blocks 3 has an opening 9 on both sides. One end of the connecting rope 4 is connected to the left roller 10. The connecting rope 4 passes through the openings 9 and is wound around the rollers 10 to reduce the friction of the connecting line 4. The outer casing 1 has a slot 7 on the right side. The winding box 6 has a ruler spring 8 inside. The other end of the connecting rope 4 passes through the slot 7 and is wound around the ruler spring 8, which can make the connecting line 4 automatically tighten.

[0021] The data transmission and control module 5 is equipped with a USB interface and a Bluetooth module. The data transmission and control module 5 has a built-in data processor, which makes the device more convenient to use. The data processor functions include: data preprocessing: after the data is input, it first passes through the data cleaning module. This module uses preset rules and algorithms to automatically identify and remove outliers and erroneous data in the data. It uses a noise reduction algorithm to smooth the data and remove noise interference generated during the data acquisition process. It uses a normalization algorithm to uniformly map data of different magnitudes to the [0, 1] interval to ensure the consistency and comparability of the data and provide a reliable data foundation for subsequent simulation analysis.

[0022] Trend simulation algorithm: The algorithm mainly uses the LSTM model under the deep learning framework, combined with the traditional ARIMA algorithm for trend simulation. The LSTM model can effectively capture long-term dependencies in the data and has good adaptability to complex economic and financial time series data. The ARIMA algorithm has advantages in processing short-term trend changes and periodic data. By organically combining the two and training and optimizing based on a large amount of historical economic and financial data, the model can accurately predict future trends and generate corresponding curve coordinate data.

[0023] Real-time updates and corrections: The device is equipped with a real-time data acquisition interface, which can obtain the latest economic and financial data in real time through network connection. Once new data is input, the device will automatically trigger a real-time update mechanism, using incremental learning algorithms to update and optimize the existing model, thereby correcting the simulated curve in real time, ensuring that the curve always reflects the latest economic and financial trend changes, and making the data more accurate.

[0024] When in use, the device first connects to an external data storage device, such as a USB flash drive or external hard drive, via the USB interface on the data transmission and control module 5 or via Bluetooth, or directly obtains the required economic and financial data from a networked financial data platform. After importing the data, it enters the data processor for preprocessing. The data cleaning module quickly screens the data according to preset rules and algorithms, identifying and removing outliers and data with incorrect formats that deviate significantly from the normal range. Next, a denoising algorithm is activated to smooth the data, removing noise caused by various interference factors during data acquisition, making the data cleaner. Subsequently, a normalization algorithm normalizes data of different magnitudes to the [0, 1] interval, ensuring consistency and comparability in subsequent processing. The preprocessed data enters the trend simulation algorithm stage, where the LSTM model and ARIMA algorithm work together. The LSTM model, with its ability to capture long-term dependencies, deeply analyzes the long-term trends and potential patterns in the economic and financial data; ARIMA... The algorithm focuses on processing short-term trend changes and cyclical data. Combining these two aspects, and based on a large amount of historical economic and financial data, the model generated after training and optimization can accurately predict future trends and output corresponding curve coordinate data. The data processor transmits the generated curve coordinate data to the electric slide rail 2. According to the received instructions, the electric slide rail 2 drives the moving blocks 3 mounted on it to move precisely along the slide rail. The movement of the moving blocks 3 causes the connecting rope 4 connected to them to shift. Since the connecting rope 4 is wound around the rollers 10 inside each moving block 3, the rollers 10 rotate accordingly, reducing the friction of the connecting rope 4 during movement and ensuring smooth movement. One end of the connecting rope 4 is connected to the left moving block 3, and the other end passes through the remaining moving blocks 3 and is wound around the ruler spring 8 inside the winding box 6. The elasticity of the ruler spring 8 keeps the connecting rope 4 taut, ensuring the stability of the entire structure. As the moving blocks 3 move, the position of the connecting rope 4 continuously changes, forming a shape similar to an economic and financial trend curve inside the outer shell 1. Users can visually observe the connecting rope 4. The presented curve shape allows us to understand the trend changes in economic and financial data. The equipment acquires the latest economic and financial data through a real-time data acquisition interface, and the real-time update and correction mechanism is immediately activated. The incremental learning algorithm quickly updates and optimizes the existing model, the data processor recalculates the curve coordinate data, and transmits it again to the electric slide rail 2 and the winding box 6, so that the connecting rope 4 is readjusted. The simulated curve is corrected in real time, always reflecting the latest economic and financial trends. During use, users can also flexibly adjust the simulation time range, data interval, and other parameters through the operation interface on the data transmission and control module 5 to meet different analysis needs.

[0025] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An economic and financial trend curve simulation device, comprising a housing (1), an electric slide rail (2), a connecting rope (4), and a moving block (3), characterized in that, The number of electric slide rails (2) is several, and the electric slide rails (2) are all installed inside the outer shell (1). The number of moving blocks (3) corresponds to the number of electric slide rails (2). The moving blocks (3) are respectively sleeved on the electric slide rails (2) and slide in cooperation with the electric slide rails (2). A winding box (6) is provided on the right side of the outer shell (1). One end of the connecting rope (4) is fixedly connected to the moving block (3) on the left side. The other end of the connecting rope (4) passes through the remaining moving blocks (3) and the outer shell (1) and extends into the winding box (6). A data transmission and control module (5) is provided below the winding box (6).

2. The economic and financial trend curve simulation device according to claim 1, characterized in that, Each of the several movable blocks (3) is provided with a rotatable roller (10), and each of the several movable blocks (3) has an opening (9) on both sides. One end of the connecting rope (4) is connected to the left roller (10), and the connecting rope (4) passes through the several openings (9) and is wrapped around the several rollers (10).

3. The economic and financial trend curve simulation device according to claim 1, characterized in that, The outer casing (1) has a slot (7) on the right side, and the winding box (6) has a ruler spring (8) inside. The other end of the connecting rope (4) passes through the slot (7) and is wound around the ruler spring (8).

4. The economic and financial trend curve simulation device according to claim 1, characterized in that, The data transmission and control module (5) is equipped with a USB interface and a Bluetooth module, and the data transmission and control module (5) has a built-in data processor.

5. The economic and financial trend curve simulation device according to claim 4, characterized in that, The data processor functions include: data preprocessing: after data input, it first passes through a data cleaning module. This module uses preset rules and algorithms to automatically identify and remove outliers and erroneous data in the data, smooths the data through a denoising algorithm to remove noise interference generated during data acquisition, and uses a normalization algorithm to uniformly map data of different magnitudes to the [0, 1] interval to ensure data consistency and comparability, providing a reliable data foundation for subsequent simulation analysis; Trend simulation algorithm: The algorithm mainly uses the LSTM model under the deep learning framework, combined with the traditional ARIMA algorithm for trend simulation. The LSTM model can effectively capture long-term dependencies in the data and has good adaptability to complex economic and financial time series data. The ARIMA algorithm has advantages in processing short-term trend changes and periodic data. By organically combining the two and training and optimizing based on a large amount of historical economic and financial data, the model can accurately predict future trends and generate corresponding curve coordinate data. Real-time updates and corrections: The device is equipped with a real-time data acquisition interface, which can obtain the latest economic and financial data in real time through network connection. Once new data is input, the device will automatically trigger a real-time update mechanism, using incremental learning algorithms to update and optimize the existing model, thereby correcting the simulated curve in real time and ensuring that the curve always reflects the latest economic and financial trend changes.

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