Channel image generation and display method and device based on multi-parallel channel detection, computer device and storage medium

Abstract

This application relates to the field of computers and provides a method, apparatus, computer device, and storage medium for generating and displaying channel images based on multi-parallel channel detection. The method includes: acquiring historical resource numerical data of a target resource input product; establishing a resource numerical database based on the historical resource numerical data; searching for parallel channels at different positions in the resource numerical database using a multi-parallel channel resonance algorithm to calculate and store channel data; drawing parallel channel lines in a preset coordinate system based on the channel data to generate a channel image corresponding to the channel data; and displaying the channel image in a target display window so that resource input decision-makers can identify the decision information in the channel image. The implementation of this method improves the efficiency of channel image generation and enhances the display effect of the channel images.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, computer device, and storage medium for generating and displaying channel images based on multi-parallel channel detection. Background Technology

[0002] In data analysis, channels are a commonly used technical analysis tool that uses parallel trend lines to identify support and resistance levels.

[0003] However, traditional parallel channel techniques typically require manually drawing parallel channel lines for analysis. Manual drawing limits the number of channels that can be analyzed, leading to vague criteria for judging individual channels and making it difficult to accurately determine data relationships. Therefore, traditional techniques suffer from low efficiency in generating channel images. Summary of the Invention

[0004] This application provides a method, apparatus, computer device, and storage medium for generating and displaying channel images based on multi-parallel channel detection. More specifically, this application provides a method, apparatus, computer device, computer storage medium, and computer program product for generating and displaying channel images based on multi-parallel channel detection, which improves the efficiency of channel image generation and enhances the display effect of channel images.

[0005] In a first aspect, embodiments of this application provide a method for generating and displaying channel images based on multi-parallel channel detection, including:

[0006] Obtain historical resource value data of the target resource input product, and establish a resource value database based on the historical resource value data;

[0007] The multi-parallel-channel resonance algorithm is used to search for parallel channels at different locations in the resource numerical database in order to calculate and store channel data.

[0008] Based on the channel data, parallel channel lines are drawn in a preset coordinate system to generate a channel image corresponding to the channel data;

[0009] The channel image is displayed in the target display window so that resource allocation decision-makers can identify the decision information in the channel image.

[0010] Optionally, in some embodiments of this application, establishing a resource value database based on the historical resource value data includes:

[0011] Obtain intermediate data during the calculation process of the historical resource numerical data;

[0012] The resource value database is established based on the historical resource value data and the intermediate data.

[0013] Optionally, in some embodiments of this application, the step of searching for parallel channels at different locations in the resource value database using a multi-parallel-channel resonance algorithm to calculate and store channel data includes:

[0014] Define the channel parameters that characterize the data structure in the channel data;

[0015] Based on the resource value database, perform a cyclic search process with a preset number of searches to determine the upper and lower track data of the channel;

[0016] The channel parameters are calculated based on the upper and lower track data of the channel;

[0017] The channel validity is filtered based on the calculated channel parameters to obtain channel data that meets the filtering criteria.

[0018] Optionally, in some embodiments of this application, the channel parameters characterizing the data structure in the defined channel data include:

[0019] The basic parameters of a channel are determined by its starting price, parallel line position, step size, starting and ending positions, channel direction, and time range.

[0020] Define channel search parameters;

[0021] The channel parameters are determined based on the basic parameters and the channel search parameters.

[0022] Optionally, in some embodiments of this application, the step of performing a cyclic search process with a preset number of searches to determine the upper and lower track data of the channel includes:

[0023] Determine the starting point data and the interval data for each search corresponding to the cyclic search process;

[0024] Based on the starting point data of each search, the interval data of each search, and the preset number of searches, the cyclic search process is executed to obtain the local highest point data and local lowest point data corresponding to each search interval.

[0025] Based on the local highest point data and local lowest point data, the upper and lower track data of the channel are determined.

[0026] Optionally, in some embodiments of this application, the step of performing channel validity filtering based on the calculated channel parameters to obtain channel data that meets the filtering conditions includes:

[0027] Based on the calculated channel parameters, determine the position data of the parallel lines;

[0028] Based on the position data of the parallel lines, the parallel lines that can cover all resource values ​​within the interval are retained to obtain the channel data that meets the filtering criteria.

[0029] Optionally, in some embodiments of this application, the method further includes:

[0030] The preset key location data and image trend data represented in the channel image are identified;

[0031] Based on the preset key location data and image trend data, the decision information corresponding to the channel image is generated.

[0032] Secondly, embodiments of this application provide a channel image generation and display apparatus based on multi-parallel channel detection, which has the function of implementing the channel image generation and display method based on multi-parallel channel detection provided in the first aspect above. The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above function, and the modules can be software and / or hardware.

[0033] In one possible design, the device includes:

[0034] The database establishment module is used to obtain historical resource value data of the target resource input products and establish a resource value database based on the historical resource value data.

[0035] The channel data calculation module is used to search for parallel channels at different locations in the resource numerical database using a multi-parallel channel resonance algorithm, so as to calculate and store channel data.

[0036] The channel image generation module is used to draw parallel channel lines in a preset coordinate system based on the channel data, so as to generate a channel image corresponding to the channel data.

[0037] The channel image display module is used to display the channel image in the target display window so that the resource allocation decision-maker can identify the decision information in the channel image.

[0038] In another aspect, this application provides a computer device including at least one connected processor and a memory, wherein the memory is used to store program code, and the processor is used to call the program code in the memory to execute the methods described in the above aspects.

[0039] In another aspect, embodiments of this application provide a computer storage medium including instructions that, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0040] In another aspect, this application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the methods described in the above aspects.

[0041] Compared to traditional technologies, the technical solution of this application embodiment can simultaneously detect and draw multiple parallel channels, avoiding the problem of ambiguous judgment criteria for a single channel, providing multi-dimensional channel information, helping users to fully understand data trends, and providing powerful visualization tools to support resource investment decision-makers in judging key positions, thereby improving the overall efficiency of channel image generation and enhancing the display effect of channel images. Attached Figure Description

[0042] Figure 1 This is an application environment diagram for one embodiment.

[0043] Figure 2 This is a flowchart of one embodiment.

[0044] Figure 3 This is a flowchart of the overall method in one embodiment.

[0045] Figure 4 This is a flowchart of a multi-parallel channel resonance algorithm in one embodiment.

[0046] Figure 5 This is a schematic diagram of a channel image in one embodiment.

[0047] Figure 6 This is a structural block diagram of the device in one embodiment.

[0048] Figure 7 This is an internal structural diagram of a computer device in one embodiment.

[0049] Figure 8 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0050] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules appearing in the embodiments of this application is only a logical division. In actual applications, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms. None of these are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0051] Figure 1 As shown in the application environment diagram of one embodiment, this application provides a method for generating and displaying channel images based on multi-parallel channel detection, which can be applied to, for example... Figure 1 In the application scenario shown, terminal 102 communicates with server 104 via a network.

[0052] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0053] It should be noted that the terminal 102 involved in the embodiments of this application can be a wired terminal or a wireless terminal, and can be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connectivity, or other processing devices connected to a wireless modem. The wireless terminal can communicate with one or more core networks via a wireless access network, and the wireless terminal can be a mobile terminal, such as a mobile phone or a computer with a mobile terminal.

[0054] Figure 2 This is a flowchart illustrating one embodiment, such as... Figure 2 As shown in the embodiments of this application, the method for generating and displaying channel images based on multi-parallel channel detection includes:

[0055] S1000: Obtain historical resource value data of the target resource input product, and establish a resource value database based on the historical resource value data.

[0056] Among them, the target resource input products include financial products that provide users with resource input-related services, such as stocks, futures, and foreign exchange; resource values ​​can be relevant numerical information of financial products, such as the price of financial products; in the financial field, historical resource value data can be historical price data, such as the highest price and the lowest price, and correspondingly, the resource value database is the price database.

[0057] More specifically, the target resource input product refers to a financial product with investment attributes; historical resource numerical data refers to the product's past price, fluctuations, and other related numerical records; the resource numerical database is used to store historical data and related data during the calculation process. For example, step S1000 can be described as: obtaining historical price data of the target financial product and establishing a price database.

[0058] S2000 uses a multi-parallel-channel resonance algorithm to search for parallel channels at different locations in the resource numerical database in order to calculate and store channel data.

[0059] Among them, the multi-parallel channel resonance algorithm refers to the calculation method of searching for channels at multiple locations and filtering effective channels; parallel channels refer to the price movement range trajectory formed by parallel trend lines; channel data is used to characterize the characteristics of channel structure, position, range and other related parameters.

[0060] For example, step S2000 can also be described as: searching for parallel channels at different locations using a multi-parallel-channel resonance algorithm, and calculating and storing channel data.

[0061] S3000: Based on the channel data, parallel channel lines are drawn in a preset coordinate system to generate the channel image corresponding to the channel data.

[0062] Among them, the preset coordinate system refers to the two-dimensional drawing coordinate system composed of price and time, also known as the price-time coordinate system; the parallel channel lines refer to the straight line graphs of the track drawn according to the channel parameters; and the channel image refers to the visual graph formed by the combination of multiple parallel channels.

[0063] For example, step S3000 can also be described as: drawing parallel channel lines in the price-time coordinate system to generate a channel image.

[0064] The S4000 displays channel images in the target display window so that resource allocation decision-makers can identify decision information from the channel images.

[0065] The target display window refers to the display interface used to display channel images, i.e., the display window of the visualization tool.

[0066] Among them, the resource allocation decision-maker refers to the user who needs to understand the specific information of financial products to operate resources, such as investors.

[0067] Among them, decision information refers to the specific decisions made by the decision-makers regarding resource allocation, such as the decision to buy.

[0068] For example, step S4000 can also be described as: displaying the generated channel image to the user, so that the user can determine the valid position based on the image.

[0069] Compared to traditional technologies, this embodiment first acquires historical resource value data of the target resource input product to establish a resource value database. Then, through a multi-parallel channel resonance algorithm, it searches for parallel channels at different positions in the resource value database to calculate and store channel data. Subsequently, it draws parallel channel lines in a preset coordinate system to generate channel images corresponding to the channel data. Finally, it displays the channel images in the target display window. The technical solution of this embodiment can simultaneously detect and draw multiple parallel channels, avoiding the problem of ambiguity in the judgment criteria of a single channel. It provides multi-dimensional channel information, which helps users to fully understand data trends and provides powerful visualization tools to support resource input decision-makers in judging key positions. This improves the overall efficiency of channel image generation and enhances the display effect of channel images.

[0070] Optionally, in some embodiments of this application, establishing a resource value database based on historical resource value data includes: obtaining intermediate data of historical resource value data during the calculation process; and establishing a resource value database based on the historical resource value data and the intermediate data.

[0071] Intermediate data refers to temporary procedural data generated during channel calculation.

[0072] In this embodiment, by storing intermediate data, the comprehensiveness of data storage is improved, the continuity of calculation is ensured, and the efficiency of data processing is enhanced.

[0073] Optionally, in some embodiments of this application, a multi-parallel-channel resonance algorithm is used to search for parallel channels at different positions in the resource numerical database to calculate and store channel data. This includes: defining channel parameters that characterize the data structure in the channel data; performing a cyclic search process with a preset number of searches based on the resource numerical database to determine the upper and lower track data of the channel; calculating the channel parameters based on the upper and lower track data of the channel; and performing channel validity screening based on the calculated channel parameters to obtain channel data that meets the screening conditions.

[0074] Among them, channel parameters are used to characterize the core attributes of the channel, such as structure, position, and trend; loop search processing refers to the operation of searching for channels by traversing different intervals a set number of times.

[0075] Among them, the upper and lower rail data of the channel are used to characterize the numerical information of the channel's pressure and support levels.

[0076] Among them, channel validity screening refers to the operation of removing invalid channels and retaining qualified data.

[0077] In this embodiment, by defining channel parameters and performing cyclic search and filtering processes, the accuracy of channel calculation is improved, and the validity and reliability of the data are enhanced.

[0078] Optionally, in some embodiments of this application, channel parameters characterizing the data structure in the channel data are defined, including: constructing basic channel parameters based on the channel's starting price, parallel line position, step size, starting and ending positions, channel direction, and time range; defining channel search parameters; and determining channel parameters based on the basic parameters and channel search parameters.

[0079] Among them, channel parameters include channel basic parameters and channel search parameters. Channel basic parameters refer to the set of core basic indicators that describe the channel pattern; channel search parameters refer to the configuration values ​​that control the channel search range and interval.

[0080] Specifically, the basic parameters of a channel include the starting price, parallel line position, step size, start and end positions, channel direction, and time range; the channel search parameter can be denoted as BFF, and the value of the channel search parameter is usually 15.

[0081] More specifically, the starting price refers to the price value corresponding to the starting position of the channel; the parallel line position is used to represent the coordinate point of the channel track in the coordinate system; the step size refers to the price change range of the channel corresponding to a unit K-line; the starting and ending positions are used to represent the starting and ending nodes of the K-lines covered by the channel; the channel direction is used to represent the overall trend of the channel; and the time range is used to represent the duration of the K-line interval covered by the channel.

[0082] In this embodiment, by fully defining various parameters, the accuracy of channel description is improved and the stability of algorithm execution is enhanced.

[0083] Optionally, in some embodiments of this application, a cyclic search process with a preset number of searches is performed to determine the upper and lower track data of the channel, including: determining the starting point data and the interval data of each search corresponding to the cyclic search process; performing the cyclic search process according to the starting point data, the interval data of each search, and the preset number of searches to obtain the local highest point data and the local lowest point data corresponding to each search interval; and determining the upper and lower track data of the channel according to the local highest point data and the local lowest point data.

[0084] The starting point data for each search is used to characterize the starting K-line position information of a single channel search; for example, the starting point for each search is: "2 + number of searches * 20".

[0085] The interval data for each search is used to represent the range of K-lines covered by a single search; for example, the interval for each search is: "starting from (starting point - BFF), extending (BFF*2+1) K-lines."

[0086] The preset number of searches refers to the number of loops for the loop search process, for example, 50 loop searches.

[0087] Among them, local high point data refers to the price value information at a relatively high position within the search range, that is, the data of the upper rail point (local high point). For example, if the value of a K-line is the largest within n intervals before and after a certain K-line, then the data of that K-line is the local high point data.

[0088] Similarly, local minimum data refers to the price value information at a relatively low position within the search interval, that is, the data of the lower rail point (local minimum). For example, if the value of a certain K-line is the lowest within n intervals before and after it, then the data of that K-line is the local minimum data. n can be dynamically adjusted, for example, n = 2.

[0089] For example, the upper and lower rail data of the channel are determined based on the local highest point data and the local lowest point data. Specifically, after determining the local highest point data corresponding to the two upper rail points (local highest points), the line connecting the two upper rail points is determined as the upper rail. After determining the local lowest point data corresponding to the lower rail point (local lowest point), the line connecting the two lower rail points is determined as the lower rail, so as to generate the upper and lower rail data of the channel.

[0090] In this embodiment, by accurately determining the search starting point and interval, the efficiency of high and low point identification is improved, and the accuracy of upper and lower track data is enhanced.

[0091] Optionally, in some embodiments of this application, channel validity filtering is performed based on the calculated channel parameters to obtain channel data that meets the filtering conditions, including: determining the position data of parallel lines based on the calculated channel parameters; retaining parallel lines that can cover all resource values ​​within the interval based on the position data of parallel lines to obtain channel data that meets the filtering conditions.

[0092] Among them, the position data of parallel lines are used to represent the position information of the trajectory line in the coordinate system; the channel data that meets the filtering criteria refers to the effective channel information that can completely cover the price.

[0093] For example, the position of the parallel line corresponding to each K-line is calculated to obtain the position data of the parallel lines. The parallel lines that cover the prices of all K-lines within the channel range are retained to obtain the channel data that meets the filtering criteria.

[0094] In this embodiment, filtering channel data by coverage area improves the effectiveness of channel data and enhances the reliability of subsequent channel image generation and decision information generation.

[0095] Optionally, in some embodiments of this application, the method further includes: identifying preset key position data and image trend data represented in the channel image; and generating decision information corresponding to the channel image based on the preset key position data and image trend data.

[0096] Among them, the preset key position data, also known as key position or effective position, is used to characterize the support and pressure points formed by multi-channel resonance, such as the position corresponding to the intersection of multiple channel lines.

[0097] Among them, image trend data is used to characterize the price movement direction information reflected by the channel image, such as "price falling back to a key position" or "price rising to a key position".

[0098] It should be noted that the decision information can be generated based on preset matching rules, which store the correspondence between different channel images and decision information. For example, in one embodiment, the preset matching rules may be: when the channel image represents "price falling back to a key level", the matched decision information is "buy"; when the channel image represents "price rising to a key level", the matched decision information is "sell"; when the channel image represents "price falling below a key level", the matched decision information is "sell"; and when the channel image represents "price breaking through a key level", the matched decision information is "buy".

[0099] In this embodiment, by identifying preset key location data and image trend data, the accuracy of decision information generation is improved, as well as the efficiency and adaptability of decision information generation.

[0100] The technical research process and other technical details of this application are described below with reference to a specific embodiment.

[0101] In market data analysis in the financial field, price channels are a commonly used technical analysis tool that uses parallel trend lines to identify price support and resistance levels.

[0102] Traditional parallel channel techniques typically focus on a single channel, which leads to a lack of clarity in the criteria for judging a single channel. This makes it difficult to accurately determine the relationship between price and channel, resulting in a lack of systematic judgment of key positions and susceptibility to subjective factors.

[0103] Therefore, a more scientific and systematic method is needed to detect multiple parallel channels, generate clear channel images, and provide reliable decision support for investors to determine effective key positions.

[0104] Based on this, this application provides a method for generating and displaying channel images based on multi-parallel channel detection, which can also be called an index calculation method for finding effective positions based on multi-parallel channel detection. It can be applied to the financial field, especially the data analysis field of financial products.

[0105] This application utilizes a multi-parallel channel resonance algorithm to simultaneously detect multiple parallel channels and plot these channels in a price-time coordinate system, generating clear channel images for users to determine valid key positions based on the images. This solves the problem of ambiguous single-channel judgment criteria in traditional parallel channel technology.

[0106] The channel image generation and display method based on multi-parallel channel detection provided in this application can detect multiple parallel channels simultaneously, avoiding the problem of ambiguity in the judgment criteria of a single channel; it provides multi-dimensional channel information to help users fully understand price trends; and it provides investors with powerful visualization tools to judge key positions, improving the accuracy and reliability of decision-making.

[0107] Figure 3 This is a flowchart of the overall method in one embodiment. Figure 4 Here is a flowchart of a multi-parallel-channel resonance algorithm in one embodiment. Figure 5 This is a schematic diagram of a channel image in one embodiment.

[0108] refer to Figures 3 to 5 The method for generating and displaying channel images based on multi-parallel channel detection provided in this application specifically includes the following steps.

[0109] Step S1000: Obtain historical price data for the target financial product and establish a price database.

[0110] Step S2000: Search for parallel channels at different locations using a multi-parallel-channel resonance algorithm, calculate and store the channel data.

[0111] Step S3000: Draw parallel channel lines in the price-time coordinate system to generate a channel image.

[0112] Step S4000: Display the generated channel image to the user so that the user can determine the valid position based on the image.

[0113] Step S1000 is the data preparation stage, and step S1000 specifically includes:

[0114] S1100 obtains historical price data for target financial products (such as stocks, futures, foreign exchange, etc.), including the highest price and the lowest price.

[0115] The S1200 establishes a price database to store historical price data and intermediate data from the calculation process.

[0116] Specifically, step S2000 includes:

[0117] Step S2100: Define the channel data structure, including parameters such as the starting price of the channel, the position of the parallel line, the step size, the starting and ending positions, the channel direction, and the time range; define the channel search parameter BFF (usually 15).

[0118] Step S2200: Loop through the search 50 times. The starting point of each search is 2 + the number of searches * 20. The range of each search is the range of (starting point - BFF) extending to (BFF * 2 + 1) K-lines.

[0119] Step S2300: In each search, find the highest and lowest points of the search interval to determine the upper and lower rails of the channel.

[0120] Step S2400: Calculate the parameters of the channel defined in step S2100;

[0121] Step S2500: Save the channel data that meets the conditions, including the various parameters and time range of the channel.

[0122] Specifically, step S2300 includes:

[0123] Step S2310: Starting from the current starting position, find the highest and lowest points that meet the conditions within the search interval;

[0124] Step S2320: If the highest point is found at the current position, record it as the upper rail point of the channel;

[0125] Step S2330: If the lowest point is found at the current position, record it as the lower rail point of the channel;

[0126] Step S2340: Move to the next position and continue searching until two upper rail points or two lower rail points are found or the search range is exceeded.

[0127] Specifically, step S2400 includes:

[0128] Step S2410: Calculate the channel step size based on the two points found;

[0129] Step S2420: Starting from the beginning of the channel and ending at the end of the channel, traverse all the K-lines in it and calculate the position of the parallel line corresponding to each K-line according to the step size of the channel.

[0130] Step S2430: Only retain the parallel lines that cover the prices of all candlesticks within the channel range;

[0131] Step S2440: After the channel data calculation is completed, save the channel data to the channel data array.

[0132] Overall, the multi-parallel channel search process in step S2000 includes: (1) searching for channels from different starting positions, searching 50 times, and the number of searches can be adjusted, with 50 being a suitable number; (2) at each starting position, simultaneously finding the highest and lowest points to determine the upper and lower rails of the channel; (3) calculating various parameters of the channel, including the starting price, parallel line position, step size, starting and ending positions, channel direction, and time range; and (4) saving the channel data that meets the conditions.

[0133] Step S3000, also known as the channel drawing and image generation step, specifically includes: drawing all eligible channel lines in the price-time coordinate system; and generating a clear channel image based on the channel data.

[0134] In step S4000, the process of the user determining the effective position based on the image specifically includes: the user observing the relationship between price and channel based on the displayed channel image; and determining the effective key position, i.e., the point where multiple channel lines intersect, based on the support and resistance characteristics of the channel. Figure 5 The point marked with a red circle.

[0135] More specifically, after users determine the effective position based on the image, they will make investment decisions based on the judgment results, including: when the judgment result is "price falls back to the key position", the matching investment decision is "buy"; when the judgment result is "price rises to the key position", the matching investment decision is "sell"; when the judgment result is "price falls below the key position", the matching investment decision is "sell"; and when the judgment result is "price breaks through the key position", the matching investment decision is "buy".

[0136] Channel images in one embodiment are as follows Figure 5 As shown, in Figure 5 In the diagram, the solid blue lines represent the data from multiple parallel channels, while the dashed blue lines represent the mid-line of the corresponding parallel channels. The red circles mark the key locations identified by resonance, as there are at least three channel lines crossing these locations.

[0137] The channel image generation and display method based on multi-parallel channel detection provided in this application searches for parallel channels at different positions in historical price data through a multi-parallel channel resonance algorithm, calculates channel parameters, and draws parallel channel lines in a price-time coordinate system for users to determine the effective position based on the image.

[0138] Because drawing parallel channels is relatively cumbersome, traditional parallel channel technical analysis usually involves manually drawing one or two parallel channel lines for analysis. However, this application, through comprehensive processing of channel data, automatically draws up to hundreds of parallel channel lines and generates clear channel images, solving the problems of cumbersome and insufficient channel number drawing in traditional parallel channel technical analysis, and providing investors with strong decision support for judging key positions.

[0139] It should be noted that any technical feature in any of the above embodiments provided in this application is also applicable to any of the following embodiments provided in this application, and similar details will not be repeated hereafter.

[0140] Figure 6 Here is a structural block diagram of the device in one embodiment, with reference to Figure 6 The channel image generation and display device based on multi-parallel channel detection includes:

[0141] The database creation module 601 is used to obtain historical resource value data of the target resource input products and to create a resource value database based on the historical resource value data.

[0142] The channel data calculation module 602 is used to search for parallel channels at different locations in the resource numerical database using a multi-parallel channel resonance algorithm, so as to calculate and store channel data.

[0143] The channel image generation module 603 is used to draw parallel channel lines in a preset coordinate system based on channel data to generate a channel image corresponding to the channel data.

[0144] The channel image display module 604 is used to display channel images in the target display window so that resource allocation decision-makers can identify the decision information in the channel images.

[0145] In this embodiment of the application, based on, as follows Figure 6 The connections between the modules or units shown in the diagram improve the efficiency of channel image generation and enhance the display effect of the channel images through the cooperation between these modules or units.

[0146] In another embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, it includes a processor, memory, input / output interfaces, and a communication interface. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface is connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores relevant data. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0147] In yet another embodiment, a computer device is provided, such as a terminal, whose internal structure diagram may be as follows: Figure 8 As shown, it includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0148] Those skilled in the art will understand that Figure 7 and Figure 8 The structure shown is only a block diagram of a part of the structure related to the present application and does not constitute a limitation on the computer device on which the present application is applied. It may also include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, in order to realize the function of the computer device.

[0149] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0150] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the systems, devices, equipment, modules or units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, devices, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0152] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0153] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0154] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0155] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium, or a semiconductor medium (e.g., a solid-state drive), etc.

[0156] The technical solutions provided by the embodiments of this application have been described in detail above. Specific examples have been used in the embodiments of this application to illustrate the principles and implementation methods of the embodiments of this application. The description of the above embodiments is only for the purpose of helping to understand the methods and core ideas of the embodiments of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments of this application. Therefore, the content of this specification should not be construed as a limitation on the embodiments of this application.

Claims

1. A method for generating and displaying channel images based on multi-parallel channel detection, characterized in that, The method includes: Obtain historical resource value data of the target resource input product, and establish a resource value database based on the historical resource value data; The multi-parallel-channel resonance algorithm is used to search for parallel channels at different locations in the resource numerical database in order to calculate and store channel data. Based on the channel data, parallel channel lines are drawn in a preset coordinate system to generate a channel image corresponding to the channel data; The channel image is displayed in the target display window so that resource allocation decision-makers can identify the decision information in the channel image.

2. The method according to claim 1, characterized in that, The step of establishing a resource value database based on the historical resource value data includes: Obtain intermediate data during the calculation process of the historical resource numerical data; The resource value database is established based on the historical resource value data and the intermediate data.

3. The method according to claim 1, characterized in that, The step of searching for parallel channels at different locations in the resource numerical database using a multi-parallel channel resonance algorithm to calculate and store channel data includes: Define the channel parameters that characterize the data structure in the channel data; Based on the resource value database, perform a cyclic search process with a preset number of searches to determine the upper and lower track data of the channel; The channel parameters are calculated based on the upper and lower track data of the channel; The channel validity is filtered based on the calculated channel parameters to obtain channel data that meets the filtering criteria.

4. The method according to claim 3, characterized in that, The channel parameters that characterize the data structure in the defined channel data include: The basic parameters of a channel are determined by its starting price, parallel line position, step size, starting and ending positions, channel direction, and time range. Define channel search parameters; The channel parameters are determined based on the basic parameters and the channel search parameters.

5. The method according to claim 3, characterized in that, The process of performing a cyclic search a preset number of times to determine the upper and lower track data of the channel includes: Determine the starting point data and the interval data for each search corresponding to the cyclic search process; Based on the starting point data of each search, the interval data of each search, and the preset number of searches, the cyclic search process is executed to obtain the local highest point data and local lowest point data corresponding to each search interval; Based on the local highest point data and local lowest point data, the upper and lower track data of the channel are determined.

6. The method according to claim 3, characterized in that, The process of filtering channel validity based on the calculated channel parameters to obtain channel data that meets the filtering criteria includes: Based on the calculated channel parameters, determine the position data of the parallel lines; Based on the position data of the parallel lines, the parallel lines that can cover all resource values ​​within the interval are retained to obtain the channel data that meets the filtering criteria.

7. The method according to claim 1, characterized in that, The method further includes: The preset key location data and image trend data represented in the channel image are identified; Based on the preset key location data and image trend data, the decision information corresponding to the channel image is generated.

8. A channel image generation and display device based on multi-parallel channel detection, characterized in that, The device includes: The database establishment module is used to obtain historical resource value data of the target resource input products and establish a resource value database based on the historical resource value data. The channel data calculation module is used to search for parallel channels at different locations in the resource numerical database using a multi-parallel channel resonance algorithm, so as to calculate and store channel data. The channel image generation module is used to draw parallel channel lines in a preset coordinate system based on the channel data, so as to generate a channel image corresponding to the channel data. The channel image display module is used to display the channel image in the target display window so that the resource allocation decision-maker can identify the decision information in the channel image.

9. A computer device, characterized in that, The computer device includes: At least one processor and memory; The memory is used to store program code, and the processor is used to call the program code stored in the memory to execute the method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, It includes instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 7.

Images