Prediction function determination method, tower steel index determination method, device and equipment

Abstract

The present invention provides a prediction function determination method, a tower steel index determination method, an apparatus, and equipment, relating to the field of power transmission line technology, to address the low prediction accuracy of actual tower index prediction methods. The method comprises obtaining the types of target design variables for the tower type and the tower steel index; determining at least two target combination variables based on the tower type and the types of the target design variables; and obtaining initial sample data corresponding to the at least two target combination variables; performing regression analysis based on the initial sample data to obtain at least two prediction functions, each of which is a functional relationship between the at least two target combination variables and the tower steel index. The at least two prediction functions are used to predict the tower steel index. The present invention can improve the accuracy of tower steel index prediction results.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission lines, and in particular to a prediction function determination method, a tower steel index determination method, a device and equipment. Background Art

[0002] Against the backdrop of carbon peak and carbon neutrality, the demand for renewable energy transmission is growing, and the corresponding volume of transmission line construction will also increase significantly. Currently, tower steel investment accounts for approximately 30% of the total investment in transmission line projects. The prediction of tower metrics is crucial for investment decisions in these projects. However, existing tower metric prediction methods suffer from low accuracy. Summary of the Invention

[0003] The embodiments of the present invention provide a prediction function determination method, a tower steel index determination method, a device and equipment. In current practical applications, the prediction accuracy of the tower index prediction method is relatively low.

[0004] In order to solve the above problems, the embodiments of the present invention adopt the following technical solutions:

[0005] In a first aspect, an embodiment of the present invention provides a method for determining a prediction function, comprising:

[0006] Obtaining the types of target design variables for the tower type and tower steel material index, wherein the tower type includes a linear tower and a tension tower, and the types of the target design variables include at least one of a conductor cross-section and number of splits, squared wind speed, ice thickness, altitude, tower nominal height, and terrain ratio;

[0007] Determining at least two target combination variables based on the tower type and the type of the target design variable, wherein the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, the first sub-variable being used to characterize the tower type, and the second sub-variable being used to characterize the type of the target design variable;

[0008] Obtaining initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, wherein the tower steel index is the weight of steel required for the tower within a single kilometer;

[0009] Regression analysis is performed based on the initial sample data to obtain at least two prediction functions, which are respectively functional relationships between the at least two target combination variables and the tower steel indicators. The at least two prediction functions are used to predict the tower steel indicators.

[0010] Optionally, the regression analysis is performed based on the initial sample data to obtain at least two prediction functions, and the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, including:

[0011] Based on the initial sample data, at least two variable combinations are determined, where the at least two variable combinations are variables formed by combining a search variable and a control variable, the search variable is any target combination variable among the target combination variables, and the control variable is a target combination variable among the target combination variables other than the search variable; based on the at least two variable combinations, at least two data sets corresponding to the at least two variable combinations are determined, where the at least two data sets are: sets of data in the initial sample data having different values for the search variables and the same values for the control variables;

[0012] Regression analysis is performed on the at least two data sets to obtain at least two prediction functions, which are functional relationships between the at least two target combination variables and the tower steel indicators.

[0013] Optionally, the regression analysis is performed based on the at least two data sets to obtain at least two prediction functions, and the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, including:

[0014] Based on the at least two data sets, respectively determining a first change amount of the search variable in the at least two data sets, and a second change amount of the tower steel index corresponding to the first change amount;

[0015] Regression analysis is performed based on the first variation and the second variation to obtain at least two prediction functions, respectively. The at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index.

[0016] Optionally, determining, based on the at least two data sets, a first change in the search variable in the at least two data sets and a second change in the tower steel index corresponding to the first change, respectively, includes:

[0017] Based on the at least two data sets, determining respectively that the first value of the search variable in the at least two data sets is a reference data;

[0018] determining a first change in the lookup variable based on the reference data, the first change being a difference between the reference data and a second value of the lookup variable;

[0019] Based on the benchmark data and the second value, determining a first indicator actual value corresponding to the benchmark data, and a second indicator actual value corresponding to the second value;

[0020] Based on the first indicator actual value and the second indicator actual value, a second change in the indicator actual value corresponding to the search variable is determined, where the second change is a difference between the first indicator actual value and the second indicator actual value.

[0021] In a second aspect, an embodiment of the present invention provides a method for determining steel indexes of a tower, comprising:

[0022] Obtaining a design value corresponding to a target combination variable of the project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable, and the target design variable is a design variable that affects the size of the indicator;

[0023] Based on the design values, determining the average weight of the linear towers and the tension towers, and the average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is a project in which the sum of the differences between the values of the target combination variables and the design values is the smallest among existing projects, and the existing project is a completed project;

[0024] Based on the preset target combination variables and the prediction function of the tower steel index, the average weight and the average nominal height, the tower steel index of the project to be predicted is determined.

[0025] Optionally, the determining of the steel index of the tower of the project to be predicted based on the prediction function of the preset target combination variable and the steel index of the tower, the average weight and the average nominal height includes:

[0026] Determining the changes corresponding to the target combination variables based on the design value and the values of the target combination variables of the typical project;

[0027] Based on the preset target combination variables and the prediction function of the tower steel index, and the variation, determining the function values corresponding to the variation respectively;

[0028] Based on the function value, the average weight, the average nominal height and other preset design values, the tower steel index of the project to be predicted is determined, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

[0029] In a third aspect, an embodiment of the present invention provides a prediction function determination device, the device comprising:

[0030] A first acquisition module is configured to acquire the type of target design variables for the tower type and tower steel material index, wherein the tower type includes a linear tower and a tension tower, and the type of the target design variable includes at least one of a conductor cross-section and number of splits, squared wind speed, ice thickness, altitude, tower nominal height, and terrain ratio;

[0031] a determination module, configured to determine at least two target combination variables based on the tower type and the type of the target design variable, wherein the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, wherein the first sub-variable is used to characterize the tower type, and the second sub-variable is used to characterize the type of the target design variable;

[0032] A second acquisition module is configured to acquire initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, the tower steel index being the weight of steel required for the tower within a single kilometer;

[0033] An analysis module is used to perform regression analysis based on the initial sample data to obtain at least two prediction functions, wherein the at least two prediction functions are the functional relationships between the at least two target combination variables and the tower steel indicators, and the at least two prediction functions are used to predict the tower steel indicators.

[0034] In a fourth aspect, an embodiment of the present invention provides a device for determining steel indexes of a tower, the device comprising:

[0035] An acquisition module is used to obtain a design value corresponding to a target combination variable of the project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable, and the target design variable is a design variable that affects the size of the indicator;

[0036] a first determining module configured to determine, based on the design values, an average weight of the linear towers and the tension towers, and an average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is a project in which the sum of the differences between the values of the target combination variables and the design values is the smallest among existing projects, and the existing project is a completed project;

[0037] The second determination module is used to determine the steel index of the tower of the project to be predicted based on the preset target combination variable and the prediction function of the steel index of the tower, the average weight and the average nominal height.

[0038] In a fifth aspect, an embodiment of the present invention provides a prediction function determination device, the device comprising: a transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that:

[0039] The processor is configured to read the program in the memory to implement the steps of the method described in the first aspect.

[0040] In a sixth aspect, an embodiment of the present invention provides a device for determining steel indexes of a tower, the device comprising: a transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that:

[0041] The processor is used to read the program in the memory to implement the steps in the method described in the second aspect.

[0042] In an embodiment of the present invention, the prediction function determination method can determine at least two target combination variables based on the tower type and the type of target design variables, and use the initial sample data corresponding to the at least two target combination variables to perform regression analysis, and finally obtain a prediction function between the at least two target combination variables and the tower steel index. The tower steel index can be predicted by the prediction function corresponding to the target combination variable. Since the target combination variable includes the specific tower type and the target design variable type, the prediction result of this method is more accurate than the tower index prediction method in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in describing the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 is a flow chart of a method for determining a prediction function provided by an embodiment of the present invention;

[0045] Figure 2 This is a flow chart of a method for determining steel indexes for a tower provided by an embodiment of the present invention;

[0046] Figure 3 is a structural diagram of a prediction function determination device provided by an embodiment of the present invention;

[0047] Figure 4 This is a structural diagram of a device for determining steel indexes of a tower provided by an embodiment of the present invention;

[0048] Figure 5is a structural diagram of a prediction function determination device provided by an embodiment of the present invention;

[0049] Figure 6 This is a structural diagram of a tower steel index determination device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0051] Unless otherwise defined, technical or scientific terms used in this disclosure shall have the ordinary meanings understood by persons of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar expressions used in this disclosure do not denote any order, quantity, or importance; they are used solely to distinguish between components. Terms such as "upper," "lower," "left," and "right" are used solely to indicate relative positions; when the absolute position of the object being described changes, the relative position changes accordingly.

[0052] See Figure 1 , Figure 1 A flowchart of a method for determining a prediction function provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0053] Step 101, obtaining the types of target design variables for the tower type and tower steel index, wherein the tower type includes a straight tower and a tension tower, and the types of the target design variables include at least one of the conductor cross-section and split number, wind speed squared, ice thickness, altitude, tower nominal height, and terrain ratio.

[0054] Specifically, the tower type can be classified according to different angles, and can be from the perspective of use. The tower types include straight towers and tension towers. The straight tower can be a tower mainly used to withstand the longitudinal tension generated by line break accidents or other situations. The tension tower can be a tower mainly used to withstand the overhead line tension along the line direction under normal operation and line break accidents; the target design variables can be design variables that have a greater impact on the tower steel indicators in transmission line projects, such as conductor cross-section and split number, wind speed squared, ice thickness, altitude, tower nominal height and terrain ratio.

[0055] Step 102: Determine at least two target combination variables based on the tower type and the type of the target design variable. The at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable. The first sub-variable is used to characterize the tower type, and the second sub-variable is used to characterize the type of the target design variable.

[0056] Specifically, the target combination variable can be any combination of the tower type and the type of the target design variable, that is, the tower type and the type of the target design variable are arranged and combined in pairs, such as the target combination variable can be a straight tower and ice thickness, a tension tower and ice thickness, or a straight tower and altitude, etc.

[0057] Step 103: Obtain initial sample data corresponding to the at least two target combination variables, wherein the initial sample data includes: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, wherein the tower steel index is the weight of steel required for the tower within a single kilometer.

[0058] Specifically, the initial sample data can be obtained based on relevant data of the transmission line project that has been completed; the different values of the at least two target combination variables can be different values of the target design variables in the target combination variables, such as different values of ice thickness in the target combination variable of straight tower and ice thickness; the actual value of the tower steel index can be the value of the tower steel index corresponding to the specific value of ice thickness.

[0059] Step 104: perform regression analysis based on the initial sample data to obtain at least two prediction functions, wherein the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, and the at least two prediction functions are used to predict the tower steel index.

[0060] Specifically, the regression analysis can be a statistical analysis method for determining the quantitative relationship of mutual dependence between two or more variables, and linear regression analysis or polynomial regression analysis can be used, and this application does not make specific limitations; the prediction function can be the quantitative relationship between the target combination variable and the tower steel index obtained by regression analysis, and the prediction function can be used to predict the value of the tower steel index corresponding to the target combination variable under a certain value.

[0061] In an embodiment of the present invention, the prediction function determination method can determine at least two target combination variables based on the tower type and the type of target design variables, and use the initial sample data corresponding to the at least two target combination variables to perform regression analysis, and finally obtain a prediction function between the at least two target combination variables and the tower steel index. The tower steel index can be predicted by the prediction function corresponding to the target combination variable. Since the target combination variable includes the specific tower type and the target design variable type, the prediction result of this method is more accurate than the tower index prediction method in the prior art.

[0062] Optionally, the regression analysis is performed based on the initial sample data to obtain at least two prediction functions, and the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, including:

[0063] Determining at least two variable combinations based on the initial sample data, wherein the at least two variable combinations are variables formed by combining a search variable and a control variable, the search variable is any target combination variable among the target combination variables, and the control variable is a target combination variable among the target combination variables except the search variable;

[0064] Based on the at least two variable combinations, determining at least two data sets corresponding to the at least two variable combinations, wherein the at least two data sets are: sets of data in the initial sample data having different values of the search variable and the same value of the control variable;

[0065] Regression analysis is performed on the at least two data sets to obtain at least two prediction functions, which are functional relationships between the at least two target combination variables and the tower steel indicators.

[0066] Specifically, based on the initial sample data, the initial sample data are combined according to the unique variable principle, and any target combination variable among the target combination variables is selected as the search variable, and the remaining target combination variables are the control variables. After determining the variable combination, i.e., the search variable and the control variable, the corresponding data set is determined. For example, when the search variables are the straight tower and the ice thickness, the data set is the set of data corresponding to different values of the search variable, i.e., different values of the ice thickness of the straight tower, and the same value of the control variable, thereby performing regression analysis on the data set to obtain a prediction function between the search variable and the tower steel index.

[0067] In an embodiment of the present invention, the prediction function determination method can accurately obtain the prediction function between a specific target combination variable and the tower steel index by controlling a single variable, so that the value of the tower steel index corresponding to the target combination variable at a certain specific value can be predicted without being interfered by other target combination variables, thereby achieving higher prediction accuracy.

[0068] Optionally, the regression analysis is performed based on the at least two data sets to obtain at least two prediction functions, and the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, including:

[0069] Based on the at least two data sets, respectively determining a first change amount of the search variable in the at least two data sets, and a second change amount of the tower steel index corresponding to the first change amount;

[0070] Regression analysis is performed based on the first variation and the second variation to obtain at least two prediction functions, respectively. The at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index.

[0071] Specifically, the first change amount may be the difference between different values of the search variable. For example, when the search variable is a straight tower and ice thickness, the first change amount may be the difference between different values of the ice thickness. The second change amount may be the difference between the tower steel indicators corresponding to different values of the search variable. For example, when the search variable is a straight tower and ice thickness, the second change amount may be the difference between the tower steel indicators corresponding to different values of the ice thickness.

[0072] In an embodiment of the present invention, the prediction function determination method can obtain the functional relationship between the change amount of the at least two target combination variables and the change amount of the tower steel index by performing regression analysis on the first change amount and the second change amount, so that the accuracy of the regression analysis is higher, and the obtained prediction function is more in line with the actual situation, so that the prediction result is more accurate.

[0073] Optionally, determining, based on the at least two data sets, a first change in the search variable in the at least two data sets and a second change in the tower steel index corresponding to the first change, respectively, includes:

[0074] Based on the at least two data sets, determining respectively that the first value of the search variable in the at least two data sets is a reference data;

[0075] determining a first change in the lookup variable based on the reference data, the first change being a difference between the reference data and a second value of the lookup variable;

[0076] Based on the benchmark data and the second value, determining a first indicator actual value corresponding to the benchmark data, and a second indicator actual value corresponding to the second value;

[0077] Based on the first indicator actual value and the second indicator actual value, a second change in the indicator actual value corresponding to the search variable is determined, where the second change is a difference between the first indicator actual value and the second indicator actual value.

[0078] Specifically, the benchmark data can be a specific value of the search variable. For example, when the search variable is a straight tower and ice thickness, the benchmark data can be a specific value of ice thickness; the actual value of the first indicator can be the value of the tower steel indicator corresponding to the benchmark data, and the actual value of the second indicator can be the value of the tower steel indicator corresponding to the second value of the search variable.

[0079] In an embodiment of the present invention, the prediction function determination method can obtain the first change amount and the second change amount by determining the benchmark data, and then perform regression analysis on the first change amount and the second change amount, so that the process of performing regression analysis on the initial sample data is more efficient and the accuracy of the obtained functional relationship is higher.

[0080] The embodiment of the present invention also provides a method for determining the index of steel materials for a tower. Figure 2 As shown, the method includes:

[0081] Step 201: obtaining a design value corresponding to a target combination variable of a project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable type, and the target design variable is a design variable that affects the size of the index.

[0082] Specifically, the project to be predicted may be a transmission line project that requires prediction of tower steel indicators, and the design value may be a specific value of the target combination variable specified by the project to be predicted; the target design variable may be a design variable that has a greater impact on the tower steel indicators in the transmission line project, such as the conductor cross-section and splitting number, wind speed squared, ice thickness, altitude, tower nominal height and terrain ratio, etc.

[0083] Step 202: Based on the design values, determine the average weight of the straight towers and the tension towers, as well as the average nominal height of the straight towers and the tension towers in a typical project. The typical project is an existing project in which the sum of the differences between the values of the target combination variables and the design values is the smallest, and the existing project is a completed project.

[0084] Specifically, the typical project can be a project selected based on data from completed projects; the average weight of the straight towers and tension towers in the typical project can be the average weight obtained by dividing the total weight of the straight towers in the typical project by the total number of straight towers, and the total weight of the tension towers by the total number of tension towers; the average nominal height of the straight towers and tension towers can be the total tower height of the straight towers in the typical project divided by the total number of straight towers, and the total tower height of the tension towers divided by the total number of tension towers.

[0085] Step 203: Determine the steel index of the tower of the project to be predicted based on the preset target combination variable and the prediction function of the steel index of the tower, the average weight and the average nominal height.

[0086] Specifically, the prediction function may be a functional relationship between the target combination variable and the tower steel index, and is used to predict the tower steel index.

[0087] In an embodiment of the present invention, the tower steel index determination method can determine a typical project, that is, an existing project that is relatively close to the design value of the project to be predicted, by obtaining the design value corresponding to the target combination variable of the project to be predicted, and then use the relevant data and prediction function of the typical project to predict the tower steel index of the project to be predicted, so that the accuracy of the prediction result is higher.

[0088] Optionally, the determining of the steel index of the tower of the project to be predicted based on the prediction function of the preset target combination variable and the steel index of the tower, the average weight and the average nominal height includes:

[0089] Determining the changes corresponding to the target combination variables based on the design value and the values of the target combination variables of the typical project;

[0090] Based on the preset target combination variables and the prediction function of the tower steel index, and the variation, determining the function values corresponding to the variation respectively;

[0091] Based on the function value, the average weight, the average nominal height and other preset design values, the tower steel index of the project to be predicted is determined, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

[0092] Specifically, the prediction formula for the tower steel index of the project to be predicted, that is, the tower steel index per kilometer, can be:

[0093] G={(k z *g z0*N*(1-p)+k n *g n0 *N*p} / L

[0094] Among them, k z k is the product of the weight change ratio of the linear tower caused by the difference of each target combination variable calculated according to the prediction function when the first sub-variable in the target combination variable is a linear tower between the project to be predicted and the typical project; n g is the product of the weight change ratio of the tension tower caused by the difference of each target combination variable calculated according to the prediction function between the project to be predicted and the typical project, when the first sub-variable in the target combination variable is a tension tower; z0 is the average weight of a typical linear tower; g n0 is the average weight of the tension towers of a typical project; N is the total number of towers; p is the ratio of tension towers; and L is the length of the transmission line.

[0095] In an embodiment of the present invention, the tower steel index determination method can calculate the change ratio of each target combination variable between the project to be predicted and the typical project, and calculate based on the change ratio and the prediction function to obtain the weight change ratio of the straight tower and the weight change ratio of the tension tower respectively, so that the average weight of the straight tower and the average weight of the tension tower in the project to be predicted can be accurately calculated, so that the prediction result has a higher accuracy.

[0096] The embodiment of the present invention provides a prediction function determination device 300, such as Figure 3 As shown, the device includes:

[0097] The first acquisition module 301 is configured to acquire the type of target design variables for the tower type and tower steel material index, wherein the tower type includes a straight tower and a tension tower, and the type of the target design variable includes at least one of a conductor cross-section and number of splits, squared wind speed, ice thickness, altitude, tower nominal height, and terrain ratio;

[0098] A determination module 302 is configured to determine at least two target combination variables based on the tower type and the type of the target design variable, where the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, where the first sub-variable is used to characterize the tower type, and the second sub-variable is used to characterize the type of the target design variable;

[0099] A second acquisition module 303 is configured to acquire initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, the tower steel index being the weight of steel required for the tower within a single kilometer;

[0100] The analysis module 304 is used to perform regression analysis based on the initial sample data to obtain at least two prediction functions, where the at least two prediction functions are the functional relationships between the at least two target combination variables and the tower steel indicators, and the at least two prediction functions are used to predict the tower steel indicators.

[0101] Optionally, the analysis module 304 includes:

[0102] a determining unit configured to determine, based on the initial sample data, at least two variable combinations, the at least two variable combinations being variables formed by a combination of a search variable and a control variable, the search variable being any target combination variable among the target combination variables, and the control variable being a target combination variable among the target combination variables other than the search variable; and determining, based on the at least two variable combinations, at least two data sets corresponding to the at least two variable combinations, the at least two data sets being sets of data in the initial sample data having different values for the search variables and the same values for the control variables;

[0103] The analysis unit is used to perform regression analysis based on the at least two data sets to obtain at least two prediction functions, where the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel indicators.

[0104] Optionally, the analysis unit is used to:

[0105] Based on the at least two data sets, respectively determining a first change amount of the search variable in the at least two data sets, and a second change amount of the tower steel index corresponding to the first change amount;

[0106] And based on the first change amount and the second change amount, regression analysis is performed to obtain at least two prediction functions respectively, and the at least two prediction functions are the functional relationships between the at least two target combination variables and the tower steel index.

[0107] Optionally, the analysis unit is used to:

[0108] Based on the at least two data sets, determining respectively that the first value of the search variable in the at least two data sets is a reference data;

[0109] determining a first change in the lookup variable based on the reference data, the first change being a difference between the reference data and a second value of the lookup variable;

[0110] Based on the benchmark data and the second value, determining a first indicator actual value corresponding to the benchmark data, and a second indicator actual value corresponding to the second value;

[0111] And based on the first indicator actual value and the second indicator actual value, a second change in the indicator actual value corresponding to the search variable is determined, where the second change is the difference between the first indicator actual value and the second indicator actual value.

[0112] The embodiment of the present invention provides a device 400 for determining steel index of a tower, such as Figure 4 As shown, the device includes:

[0113] An acquisition module 401 is configured to acquire a design value corresponding to a target combination variable of the project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable type, and the target design variable is a design variable that affects the size of the indicator;

[0114] A first determining module 402 is configured to determine, based on the design values, an average weight of the linear towers and the tension towers, and an average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is an existing project having a minimum sum of differences between the values of the target combination variables and the design values, and the existing project is a completed project;

[0115] The second determination module 403 is used to determine the steel index of the tower of the project to be predicted based on the preset target combination variable and the prediction function of the steel index of the tower, the average weight and the average nominal height.

[0116] Optionally, the second determining module 403 includes:

[0117] A first determining unit is configured to determine, based on the design value and the values of the target combination variables of the typical project, the changes corresponding to the target combination variables respectively;

[0118] A second determining unit is configured to determine function values corresponding to the respective changes based on a preset target combination variable and a prediction function of the tower steel index, and the changes;

[0119] The third determination unit is used to determine the tower steel index of the project to be predicted based on the function value, the average weight, the average nominal height and other preset design values, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

[0120] The embodiment of the present invention provides a prediction function determination device, such as Figure 5As shown, the resource scheduling device includes: a transceiver 501, a memory 502, a processor 500, and a program stored in the memory and executable on the processor:

[0121] The transceiver 501 is used to obtain the type of target design variables of the tower type and tower steel index, wherein the tower type includes a straight tower and a tension tower, and the type of the target design variable includes at least one of the conductor cross-section and number of splits, square of wind speed, ice thickness, altitude, tower nominal height, and terrain ratio;

[0122] The processor 500 is configured to read the program in the memory 502 and execute the following steps:

[0123] Determining at least two target combination variables based on the tower type and the type of the target design variable, wherein the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, the first sub-variable being used to characterize the tower type, and the second sub-variable being used to characterize the type of the target design variable;

[0124] Obtaining initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, wherein the tower steel index is the weight of steel required for the tower within a single kilometer;

[0125] Regression analysis is performed based on the initial sample data to obtain at least two prediction functions, which are respectively functional relationships between the at least two target combination variables and the tower steel indicators. The at least two prediction functions are used to predict the tower steel indicators.

[0126] Among them, Figure 5 In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 500 and memory represented by memory 502. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 501 may be a plurality of components, i.e., including a transmitter and a transceiver, providing a unit for communicating with various other devices over a transmission medium. The processor 500 is responsible for managing the bus architecture and general processing, and the memory 502 may store data used by the processor 500 when performing operations.

[0127] Optionally, the processor 500 is further configured to:

[0128] Based on the initial sample data, at least two variable combinations are determined, where the at least two variable combinations are variables formed by combining a search variable and a control variable, the search variable is any target combination variable among the target combination variables, and the control variable is a target combination variable among the target combination variables other than the search variable; based on the at least two variable combinations, at least two data sets corresponding to the at least two variable combinations are determined, where the at least two data sets are: sets of data in the initial sample data having different values for the search variables and the same values for the control variables;

[0129] Regression analysis is performed on the at least two data sets to obtain at least two prediction functions, which are functional relationships between the at least two target combination variables and the tower steel indicators.

[0130] Optionally, the processor 500 is further configured to:

[0131] Based on the at least two data sets, respectively determining a first change amount of the search variable in the at least two data sets, and a second change amount of the tower steel index corresponding to the first change amount;

[0132] Regression analysis is performed based on the first variation and the second variation to obtain at least two prediction functions, respectively. The at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index.

[0133] Optionally, the processor 500 is further configured to:

[0134] Based on the at least two data sets, determining respectively that the first value of the search variable in the at least two data sets is a reference data;

[0135] determining a first change in the lookup variable based on the reference data, the first change being a difference between the reference data and a second value of the lookup variable;

[0136] Based on the benchmark data and the second value, determining a first indicator actual value corresponding to the benchmark data, and a second indicator actual value corresponding to the second value;

[0137] Based on the first indicator actual value and the second indicator actual value, a second change in the indicator actual value corresponding to the search variable is determined, where the second change is a difference between the first indicator actual value and the second indicator actual value.

[0138] The embodiment of the present invention also provides a prediction function determination device, such as Figure 6As shown, the resource scheduling device includes: a transceiver 601, a memory 602, a processor 600, and a program stored in the memory and executable on the processor:

[0139] The transceiver 601 is used to obtain the design value corresponding to the target combination variable of the project to be predicted, where the target combination variable is a combination of the tower type and the target design variable, and the target design variable is a design variable that affects the size of the indicator;

[0140] The processor 600 is configured to read the program in the memory 602 and execute the following steps:

[0141] Based on the design values, determining the average weight of the linear towers and the tension towers, and the average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is a project in which the sum of the differences between the values of the target combination variables and the design values is the smallest among existing projects, and the existing project is a completed project;

[0142] Based on the preset target combination variables and the prediction function of the tower steel index, the average weight and the average nominal height, the tower steel index of the project to be predicted is determined.

[0143] Among them, Figure 6 In the embodiment, the bus architecture can include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 600 and memory represented by memory 602. The bus architecture can also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be further described herein. The bus interface provides an interface. The transceiver 601 can be multiple components, that is, including a transmitter and a transceiver, providing a unit for communicating with various other devices on a transmission medium. The processor 600 is responsible for managing the bus architecture and general processing, and the memory 602 can store data used by the processor 600 when performing operations.

[0144] Optionally, the processor 600 is further configured to:

[0145] Determining the changes corresponding to the target combination variables based on the design value and the values of the target combination variables of the typical project;

[0146] Based on the preset target combination variables and the prediction function of the tower steel index, and the variation, determining the function values corresponding to the variation respectively;

[0147] Based on the function value, the average weight, the average nominal height and other preset design values, the tower steel index of the project to be predicted is determined, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

[0148] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0149] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may be physically included separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional units.

[0150] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform some steps of the sending and receiving methods described in various embodiments of the present invention. The aforementioned storage medium includes: a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., various media that can store program code.

[0151] The above is a preferred embodiment of the present invention. It should be pointed out that the scope of protection of the present invention is not limited thereto. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles described in the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining a prediction function, characterized in that: include: Obtaining the types of target design variables for the tower type and tower steel material index, wherein the tower type includes a linear tower and a tension tower, and the types of the target design variables include at least one of a conductor cross-section and number of splits, squared wind speed, ice thickness, altitude, tower nominal height, and terrain ratio; Determining at least two target combination variables based on the tower type and the type of the target design variable, wherein the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, the first sub-variable being used to characterize the tower type, and the second sub-variable being used to characterize the type of the target design variable; Obtaining initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, wherein the tower steel index is the weight of steel required for the tower within a single kilometer; Performing regression analysis based on the initial sample data to obtain at least two prediction functions, wherein the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, and the at least two prediction functions are used to predict the tower steel index; The regression analysis is performed based on the initial sample data to obtain at least two prediction functions, wherein the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, including: Based on the initial sample data, at least two variable combinations are determined, where the at least two variable combinations are variables formed by combining a search variable and a control variable, the search variable is any target combination variable among the target combination variables, and the control variable is a target combination variable among the target combination variables other than the search variable; based on the at least two variable combinations, at least two data sets corresponding to the at least two variable combinations are determined, where the at least two data sets are: sets of data in the initial sample data having different values for the search variables and the same values for the control variables; Regression analysis is performed on the at least two data sets to obtain at least two prediction functions, which are functional relationships between the at least two target combination variables and the tower steel indicators.

2. The determination method according to claim 1, characterized in that The regression analysis is performed based on the at least two data sets to obtain at least two prediction functions, wherein the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, and the prediction functions include: Based on the at least two data sets, respectively determining a first change amount of the search variable in the at least two data sets, and a second change amount of the tower steel index corresponding to the first change amount; Regression analysis is performed based on the first variation and the second variation to obtain at least two prediction functions, respectively. The at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index.

3. The determination method according to claim 2, characterized in that: The determining, based on the at least two data sets, respectively a first change amount of the search variable in the at least two data sets and a second change amount of the tower steel index corresponding to the first change amount includes: Based on the at least two data sets, determining respectively that the first value of the search variable in the at least two data sets is a reference data; determining a first change in the lookup variable based on the reference data, the first change being a difference between the reference data and a second value of the lookup variable; Based on the benchmark data and the second value, determining a first indicator actual value corresponding to the benchmark data, and a second indicator actual value corresponding to the second value; Based on the first indicator actual value and the second indicator actual value, a second change in the indicator actual value corresponding to the search variable is determined, where the second change is a difference between the first indicator actual value and the second indicator actual value.

4. A method for determining steel indexes for iron towers, characterized in that: include: Obtaining a design value corresponding to a target combination variable of the project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable type, and the target design variable is a design variable that affects the size of the indicator; Based on the design values, determining the average weight of the linear towers and the tension towers, and the average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is a project in which the sum of the differences between the values of the target combination variables and the design values is the smallest among existing projects, and the existing project is a completed project; Determine the steel index of the tower for the project to be predicted based on the preset target combination variable and the prediction function of the steel index of the tower, the average weight and the average nominal height; The prediction function based on the preset target combination variable and the tower steel index, the average weight and the average nominal height is used to determine the tower steel index of the project to be predicted, including: Determining the changes corresponding to the target combination variables based on the design value and the values of the target combination variables of the typical project; Based on the preset target combination variables and the prediction function of the tower steel index, and the variation, determining the function values corresponding to the variation respectively; Based on the function value, the average weight, the average nominal height and other preset design values, the tower steel index of the project to be predicted is determined, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

5. A prediction function determination device, characterized in that: The device comprises: A first acquisition module is configured to acquire the type of target design variables for the tower type and tower steel material index, wherein the tower type includes a linear tower and a tension tower, and the type of the target design variable includes at least one of a conductor cross-section and number of splits, squared wind speed, ice thickness, altitude, tower nominal height, and terrain ratio; a determination module, configured to determine at least two target combination variables based on the tower type and the type of the target design variable, wherein the at least two target combination variables are variables formed by combining a first sub-variable and a second sub-variable, wherein the first sub-variable is used to characterize the tower type, and the second sub-variable is used to characterize the type of the target design variable; A second acquisition module is configured to acquire initial sample data corresponding to the at least two target combination variables, the initial sample data including: different values of the at least two target combination variables, and actual values of the tower steel index corresponding to the at least two target combination variables under the different values, the tower steel index being the weight of steel required for the tower within a single kilometer; An analysis module is configured to perform regression analysis based on the initial sample data to obtain at least two prediction functions, wherein the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel index, and the at least two prediction functions are used to predict the tower steel index; The analysis module includes: a determining unit configured to determine, based on the initial sample data, at least two variable combinations, the at least two variable combinations being variables formed by a combination of a search variable and a control variable, the search variable being any target combination variable among the target combination variables, and the control variable being a target combination variable among the target combination variables other than the search variable; and determining, based on the at least two variable combinations, at least two data sets corresponding to the at least two variable combinations, the at least two data sets being sets of data in the initial sample data having different values for the search variables and the same values for the control variables; The analysis unit is used to perform regression analysis based on the at least two data sets to obtain at least two prediction functions, where the at least two prediction functions are functional relationships between the at least two target combination variables and the tower steel indicators.

6. A device for determining steel index of a tower, characterized in that: The device comprises: An acquisition module is used to obtain a design value corresponding to a target combination variable of the project to be predicted, wherein the target combination variable is a combination of a tower type and a target design variable type, and the target design variable is a design variable that affects the size of the indicator; a first determining module configured to determine, based on the design values, an average weight of the linear towers and the tension towers, and an average nominal height of the linear towers and the tension towers in a typical project, wherein the typical project is a project in which the sum of the differences between the values of the target combination variables and the design values is the smallest among existing projects, and the existing project is a completed project; A second determination module is configured to determine the steel index of the tower of the project to be predicted based on a preset target combination variable and a prediction function of the steel index of the tower, the average weight, and the average nominal height; The second determining module includes: A first determining unit is configured to determine, based on the design value and the values of the target combination variables of the typical project, the changes corresponding to the target combination variables respectively; A second determining unit is configured to determine function values corresponding to the respective changes based on a preset target combination variable and a prediction function of the tower steel index, and the changes; The third determination unit is used to determine the tower steel index of the project to be predicted based on the function value, the average weight, the average nominal height and other preset design values, wherein the other design values include the preset total number of towers, the ratio of tension towers and the length of the transmission line.

7. A prediction function determination device, comprising: A transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that: The processor is configured to read a program in a memory to implement the steps in the method according to any one of claims 1 to 3.

8. A device for determining steel indexes of a tower, comprising: A transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that: The processor is configured to read the program in the memory to implement the steps in the method according to claim 4.

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