Prefabricated thin-wall cable trench optimization method and related device

Abstract

The embodiment of the invention discloses a prefabricated thin-wall cable trench optimization method and a related device, and the method comprises the steps: determining a target evaluation index set for evaluating a prefabricated thin-wall cable trench, and determining a standard value corresponding to each evaluation index according to a plurality of collected sample data; determining an objective weight corresponding to each evaluation index based on an objective weighting method; the method comprises the following steps: after obtaining actual evaluation index values of a plurality of prefabricated thin-wall cable trenches, scoring each evaluation index of each prefabricated thin-wall cable trench based on a standard value corresponding to each evaluation index to obtain a plurality of scoring groups, the evaluation result of each prefabricated thin-wall cable trench can be determined according to the multiple score groups and the objective weight corresponding to each evaluation index, and finally the prefabricated thin-wall cable trench with the optimal comprehensive performance is selected based on the multiple evaluation results.

Description

Technical Field

[0001] The present application relates to the field of selection of prefabricated cable trench parts, and in particular to a method for optimizing a prefabricated thin-wall cable trench and related devices. Background Art

[0002] In order to improve the efficiency of power grid construction, it has become a top priority to expand and update the existing power grid. However, the current research on mechanized construction of cable lines has been slow, especially in the construction of various cable channels such as cable trenches, cable ducts, cable tunnels, and cable working wells. The level of mechanized application is still low. At present, these projects usually rely on traditional cast-in-place concrete methods. Although this method performs well in terms of the overall structure, it still has some problems such as long construction period and difficulty in ensuring quality.

[0003] Although prefabrication technology has been introduced to improve the shortcomings of cast-in-place methods, its flexibility and adaptability are still insufficient when dealing with special situations such as complex geological conditions, interlaced underground pipelines, and sudden engineering changes. In complex scenarios, the design, production, and installation of prefabricated components may require substantial adjustments or even customized processing, which not only increases project costs but also reduces construction efficiency, thereby weakening the economic benefits and time advantages of prefabrication technology in conventional environments.

[0004] Therefore, it is crucial to establish a systematic evaluation and selection method to evaluate the adaptability and flexibility of prefabricated thin-wall cable trenches in different construction scenarios and select suitable prefabricated thin-wall cable trenches to improve construction efficiency, reduce costs and ensure project quality. Summary of the invention

[0005] The embodiment of the present application provides a method for optimizing a prefabricated thin-wall cable trench and related devices, which comprehensively analyzes the prefabricated thin-wall cable trench from six key indicators, namely, stress dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection, and evaluates the prefabricated thin-wall cable trench based on the analysis results, thereby achieving the selection of a prefabricated thin-wall cable trench with the best comprehensive performance among multiple prefabricated thin-wall cable trenches for power grid construction, thereby improving construction efficiency, reducing costs and ensuring project quality.

[0006] In a first aspect, an embodiment of the present application provides a method for optimizing a prefabricated thin-wall cable trench, comprising:

[0007] Determine a target evaluation index set for evaluating prefabricated thin-wall cable trenches; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection;

[0008] Acquire a target sample data set, determine a standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of a plurality of prefabricated thin-wall cable trench samples;

[0009] Determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set;

[0010] Obtain multiple prefabricated thin-wall cable trenches;

[0011] Determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set, and obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values;

[0012] Scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups;

[0013] Determine an evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups to obtain a plurality of evaluation results;

[0014] A maximum value is selected from the multiple evaluation results, and the prefabricated thin-wall cable trench corresponding to the maximum value is determined as the target optimal prefabricated thin-wall cable trench.

[0015] In a second aspect, an embodiment of the present application provides a prefabricated thin-wall cable trench optimization device, including: a data acquisition unit, a data processing unit, a weight analysis unit, an evaluation analysis unit, and a data output unit, wherein:

[0016] The data acquisition unit is used to determine a target evaluation index set for evaluating the prefabricated thin-wall cable trench; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, low carbon and environmental protection;

[0017] The data processing unit is used to obtain a target sample data set, determine the standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of multiple prefabricated thin-wall cable trench samples;

[0018] The weight analysis unit is used to determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set;

[0019] The data acquisition unit is also used to acquire a plurality of prefabricated thin-wall cable trenches;

[0020] The data processing unit is further used to determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set to obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values;

[0021] The evaluation and analysis unit is used to score each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups;

[0022] The evaluation and analysis unit is further used to determine the evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups, to obtain a plurality of evaluation results;

[0023] The data output unit is used to select a maximum value from the multiple evaluation results, and determine the prefabricated thin-wall cable trench corresponding to the maximum value as the target optimal prefabricated thin-wall cable trench.

[0024] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0025] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0026] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0027] By implementing the embodiments of the present application, a target evaluation index set for evaluating prefabricated thin-walled cable trenches is determined, and the standard value corresponding to each evaluation index is determined based on the collected multiple sample data, and the objective weight corresponding to each evaluation index is determined based on the objective weighting method; after obtaining the actual evaluation index values ​​of multiple prefabricated thin-walled cable trenches, each evaluation index of each prefabricated thin-walled cable trench is scored based on the standard value corresponding to each evaluation index, and multiple scoring groups are obtained. The evaluation results of each prefabricated thin-walled cable trench can be determined based on the multiple scoring groups and the objective weights corresponding to each evaluation index, and finally the prefabricated thin-walled cable trench with the best comprehensive performance is selected based on the multiple evaluation results. The prefabricated thin-walled cable trench with the best comprehensive performance is used in power grid construction, which improves construction efficiency, reduces costs and ensures project quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0029] Figure 1 It is a schematic flow chart of a method for optimizing a prefabricated thin-wall cable trench provided in an embodiment of the present application;

[0030] Figure 2 It is a structural schematic diagram of a prefabricated thin-wall cable trench optimization device provided in an embodiment of the present application;

[0031] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] The following is an explanation of the relevant contents, concepts, meanings, technical issues, technical solutions, beneficial effects, etc. involved in the embodiments of the present application.

[0036] First, some terms involved in this application are explained:

[0037] Coefficient of variation: The coefficient of variation is a statistic used to measure the relative dispersion of a data set. It is mainly determined by calculating the ratio of the standard deviation to the mean, and is usually expressed as a percentage.

[0038] See also Figure 1 , Figure 1 1 is a schematic flow chart of a method for optimizing a prefabricated thin-wall cable trench provided in an embodiment of the present application, the method including but not limited to the following steps:

[0039] S101. Determine a target evaluation index set for evaluating prefabricated thin-wall cable trenches; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection.

[0040] Among them, prefabricated thin-wall cable trenches are prefabricated components used in power grid construction. By prefabricating prefabricated thin-wall cable trenches, they can be used in urban power grid construction, industrial facilities, commercial buildings and other occasions due to their advantages of fast installation, small construction interference, consistent appearance, and easy quality control, providing an orderly and safe path for cables. By selecting appropriate prefabricated thin-wall cable trenches, the efficiency of cable maintenance and replacement can be improved, and the impact of cable laying on the surrounding environment can be reduced.

[0041] In the embodiment of the present application, if a suitable prefabricated thin-walled cable trench is to be selected, the quality, economy, reliability and other indicators of the prefabricated thin-walled cable trench can be evaluated according to the dimensions of force, structural performance, construction difficulty, economy, time saving, low carbon and environmental protection, and then the prefabricated thin-walled cable trench with the best comprehensive performance can be selected. Therefore, a target evaluation index set for evaluating the prefabricated thin-walled cable trench can be determined, and the target evaluation index set includes force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection. It should be noted that the embodiment of the present application evaluates the prefabricated thin-walled cable trench through the six evaluation indicators. Of course, other indicators can also be selected for evaluation, such as earthquake resistance, sound insulation effect, thermal insulation performance, etc., which are not limited here.

[0042] Among them, in the stress dimension evaluation index, the stress condition of the prefabricated thin-walled cable trench can be analyzed by analyzing the bending moment of the prefabricated thin-walled cable trench. Therefore, the vertical and longitudinal loads can be analyzed to obtain the vertical and longitudinal bending moments, and the vertical and longitudinal bending moments can be weighted to obtain the final combined bending moment.

[0043] The line load of the prefabricated thin-wall cable trench itself can be used as the vertical load, which can be calculated using the following formula:

[0044] q g =γ g bh

[0045] In the above formula, q g is the line load of the prefabricated thin-wall cable trench itself, in Newton per meter; γ g is the unit volume weight of the prefabricated thin-walled cable trench, in Newtons per cubic meter; b is the length of the side plate of the prefabricated thin-walled cable trench, in meters; h is the thickness of the side plate of the prefabricated thin-walled cable trench, in meters.

[0046] Furthermore, the bending moment of the prefabricated thin-walled cable trench under its own line load can be calculated by the following formula:

[0047]

[0048] In the above formula, M g is the bending moment of the prefabricated thin-wall cable trench under its own linear load, in Newton-meter; q g is the line load of the prefabricated thin-wall cable trench itself; l is the length of the prefabricated thin-wall cable trench, in meters.

[0049] After the prefabricated thin-walled cable trench is buried in the construction site, backfill soil is carried out. Therefore, the static soil side pressure generated by the soil around the prefabricated thin-walled cable trench on the prefabricated thin-walled cable trench can be calculated. According to the static soil side pressure, the longitudinal load of the prefabricated thin-walled cable trench can be calculated. The static soil side pressure can be calculated by the following formula:

[0050]

[0051] In the above formula, E0 is the static soil side pressure, in Newtons per square meter; γ is the unit volume weight of the backfill soil, in Newtons per cubic meter; h is the burial depth of the prefabricated thin-walled cable trench, that is, the distance from the bottom of the prefabricated thin-walled cable trench to the ground, in meters; K0 is the static soil side pressure coefficient, which is a proportional coefficient used to describe the pressure of the soil on the prefabricated thin-walled cable trench in the absence of other external forces; q is the uniformly distributed load, which means the load evenly distributed on the prefabricated thin-walled cable trench, in Newtons per square meter.

[0052] Furthermore, according to the bending moment equivalence principle, the longitudinal load of the prefabricated thin-walled cable trench under static soil side pressure can be calculated, which can be calculated by the following formula:

[0053] q w =E0×b

[0054] In the above formula, q w is the soil side pressure line load, in Newton per meter; E0 is the static soil side pressure; b is the load distribution width, in meter.

[0055] Furthermore, the bending moment of the prefabricated thin-walled cable trench under the soil side pressure line load can be calculated by the following formula:

[0056]

[0057] In the above formula, M w is the bending moment of the prefabricated thin-wall cable trench under the soil side pressure line load, in Newton meter; q w is the soil side pressure line load; l is the length of the prefabricated thin-walled cable trench, in meters.

[0058] Furthermore, after obtaining the bending moment of the prefabricated thin-walled cable trench under its own line load and the bending moment of the prefabricated thin-walled cable trench under the soil side pressure line load, the bending moments under the two different loads are combined to obtain the combined bending moment. According to the combined bending moment, the stress condition of the prefabricated thin-walled cable trench can be analyzed, wherein the calculation formula of the combined bending moment is as follows:

[0059] M=K g M g +K w M w

[0060] In the above formula, M is the combined bending moment in Newton meters. g M is the bending moment of the prefabricated thin-wall cable trench under its own linear load; w K is the bending moment of the prefabricated thin-wall cable trench under the soil side pressure line load; g K is the vertical load partial factor, generally taken as 1.3; w It is the partial factor of longitudinal load and is generally taken as 1.5.

[0061] Among them, in the structural performance evaluation index, the prefabricated thin-walled cable trench can be compared with the ordinary prefabricated cable trench to obtain the structural performance index of the prefabricated thin-walled cable trench. The structural performance of the prefabricated thin-walled cable trench is calculated by the following formula:

[0062]

[0063] In the above formula, N is the structural performance index, which is used to measure the structural performance of prefabricated thin-walled cable trench relative to ordinary prefabricated cable trench; k1 is the wall thickness evaluation factor of prefabricated thin-walled cable trench; b1 is the wall thickness of prefabricated thin-walled cable trench; b is the wall thickness of ordinary prefabricated cable trench; k2 is the compressive strength evaluation factor of prefabricated thin-walled cable trench; p1 is the compressive strength of prefabricated thin-walled cable trench; p is the compressive strength of ordinary prefabricated cable trench.

[0064] Among them, in the construction difficulty evaluation index, the prefabricated thin-walled cable trench is scored by calculating the construction efficiency of the prefabricated thin-walled cable trench. The calculation formula for the construction efficiency is as follows:

[0065] CEI=ω1×TE+ω2×CE+ω3×QE

[0066] In the above formula, CEI is the construction efficiency; TE is the time efficiency, which can be determined by comparing the ratio of the completion time of the prefabricated thin-walled cable trench to that of the ordinary prefabricated cable trench; ω1 is the weight of the time efficiency; CE is the cost efficiency, which can be measured by the ratio of the construction cost of the prefabricated thin-walled cable trench to the construction cost of the ordinary prefabricated cable trench; ω2 is the weight of the cost efficiency; QE is the quality efficiency; it can be evaluated by indicators such as the dimensional accuracy of the prefabricated thin-walled cable trench, the strength of the connection nodes, the flexibility of the structural combination, and the utilization rate of the materials, and is evaluated according to the three dimensions of strong, medium, and weak; ω3 is the weight of the quality efficiency, where ω1+ω2+ω3=1;

[0067] Among them, in the economic evaluation index, the economic index of the prefabricated thin-walled cable trench can be obtained by calculating the economic benefits of the prefabricated thin-walled cable trench and the ordinary prefabricated cable trench, which can be calculated by the following formula:

[0068]

[0069] In the above formula, EPI is the economic benefit index, expressed in percentage; ICS is the initial cost savings, which can be quantified by the cost savings compared with ordinary prefabricated cable trenches; OMS is the operation and maintenance savings; EB is the environmental benefit, which can be determined by calculating the economic value brought by reducing material waste, waste generation, carbon emissions, etc.; II is the initial investment, which can be determined by calculating the one-time expenses such as the purchase cost, transportation and installation costs of the prefabricated thin-wall cable trench.

[0070] Among them, in the time saving evaluation index, the total time saving can be determined by calculating the time saved in construction and the time saved in management, which can be calculated by the following formula:

[0071] TMEI=CST J +MST J

[0072] In the above formula, TMEI is the total time saved; CST is J To save time during construction, it means that the direct construction time is shortened by using prefabricated thin-wall cable trench; MST J Time saved for management, which refers to the indirect management time saved by the project management team due to the shortened construction period.

[0073] Among them, in the low-carbon environmental protection evaluation index, by measuring the energy consumption and carbon emission saving indicators of the prefabricated thin-wall cable trench technology compared with the ordinary prefabricated cable trench throughout the life cycle, the environmental protection and energy saving index of the prefabricated thin-wall cable trench is obtained, which can be calculated by the following formula:

[0074] ESEI=CEC+MEC+REC+LEC-ECC

[0075] In the above formula, ESEI is the environmental protection and energy saving index; CEC is the production energy saving, which means that in the production stage, due to the use of high-efficiency production lines and economies of scale, the energy consumption of prefabricated thin-walled cable trenches is reduced compared with ordinary prefabricated cable trenches; MEC is the transportation energy saving, which means that in the transportation stage, the transportation cost of prefabricated thin-walled cable trenches is compared with the transportation cost of ordinary prefabricated cable trenches. The energy saving; REC is the installation energy saving, which means that the installation cost of prefabricated thin-walled cable trenches is compared with the installation cost of ordinary prefabricated cable trenches. The energy saving during the service life period indicates the energy consumption reduction of the operation and maintenance cost of prefabricated thin-walled cable trenches during the entire life cycle; ECC is the initial additional energy consumption, which indicates the one-time additional energy consumption generated during the design, production and new material use stages.

[0076] In one possible embodiment, a target evaluation index set for evaluating the prefabricated thin-walled cable trench can be determined, and the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection. Based on the above specific calculation formula for each evaluation index, the evaluation index value corresponding to each evaluation index can be obtained, and the prefabricated thin-walled cable trench can be comprehensively evaluated according to the evaluation index value.

[0077] S102, obtaining a target sample data set, determining a standard value corresponding to each evaluation indicator in the target evaluation indicator set according to the target sample data set, and obtaining a standard value set; the target sample data set includes evaluation indicator values ​​of multiple prefabricated thin-wall cable trench samples.

[0078] The target sample data set is used to determine the standard value of each evaluation index in the target evaluation index set, which includes the evaluation index values ​​of multiple prefabricated thin-wall cable trench samples. The prefabricated thin-wall cable trench samples can be obtained by collecting the construction data of historical cable trenches and determining the evaluation index value of each evaluation index of the prefabricated thin-wall cable trench samples from the construction data. Obtaining multiple prefabricated thin-wall cable trench samples can ensure the calculation of reliable standard values ​​of each evaluation index.

[0079] Specifically, after obtaining the target sample data set, the target sample data set is comprehensively analyzed to determine a standard value for each evaluation indicator. Since the steps for calculating the corresponding standard value of each evaluation indicator in the target evaluation indicator set are the same, any evaluation indicator can be selected as the target evaluation indicator for calculation. Multiple data corresponding to the target evaluation indicator in the target sample data set can be obtained, and the multiple data can be calculated to obtain the average value, median, etc. of the target evaluation indicator, and then the weight of the average value and median in the standard value is determined, and finally the standard value of the target evaluation indicator is determined.

[0080] Optionally, the above step S102, obtaining a target sample data set, and determining a standard value corresponding to each evaluation indicator in the target evaluation indicator set according to the target sample data set to obtain a standard value set, may further include the following steps:

[0081] A21. Determine a target evaluation indicator; the target evaluation indicator is any evaluation indicator in the target evaluation indicator set;

[0082] A22, acquiring an evaluation index value corresponding to the target evaluation index from the target sample data set to obtain a first evaluation index value set; the first evaluation index value set includes a plurality of evaluation index values;

[0083] A23, determining a target maximum index value, a target minimum index value, a target median and a target average value in the first evaluation index value set;

[0084] A24. Determine a first weight based on a first preset formula, where the first preset formula is as follows:

[0085]

[0086] In the formula, α 11 is the first weight; CX is the first evaluation index value set; Max(CX) is the target maximum index value; Min(CX) is the target minimum index value; CX z is the median of the target;

[0087] A25. Determine a second weight based on a second preset formula, where the second preset formula is as follows:

[0088]

[0089] In the formula, β 11 is the second weight; CX p is the target average value;

[0090] A26. Determine the third weight and the fourth weight according to a third preset formula, wherein the third preset formula is as follows:

[0091]

[0092] Wherein, α1 is the third weight; β1 is the fourth weight;

[0093] A27. Determine the standard value corresponding to the target evaluation index according to a fourth preset formula. The fourth preset formula is as follows:

[0094] CX b =α1CX z +β1CX p

[0095] Where, CX b is the standard value corresponding to the target evaluation indicator;

[0096] A28. Determine the standard value corresponding to each evaluation indicator in the target evaluation indicator set according to the standard value corresponding to the target evaluation indicator, and obtain the standard value set.

[0097] Specifically, any evaluation indicator in the target evaluation indicator set can be determined as the target evaluation indicator, and by analyzing the target evaluation indicator, the standard value of the target evaluation indicator can be obtained. Specifically, the evaluation indicator value corresponding to the target evaluation indicator can be obtained from the target sample data set to obtain a first evaluation indicator value set, and the first evaluation indicator value set includes multiple evaluation indicator values. By calculating the target maximum indicator value, target minimum indicator value, target median and target average value in the first evaluation indicator value set, and based on these data, the third weight of the target median in the standard value and the fourth weight of the target average value in the standard value can be determined, and the target median and the target average value are weighted. Analysis is performed, and finally the standard value of the target evaluation indicator can be obtained.

[0098] In a possible embodiment, a first weight can be obtained according to the target maximum index value, the target minimum index value, the target median and the first preset formula, and the first weight represents a measure of the degree of dispersion of the evaluation index value relative to the median. A second weight can be obtained according to the target maximum index value, the target minimum index value, the target median, the target average value and the second preset formula, and the second weight represents a balance measure between the maximum and minimum values ​​of the evaluation index value. A third weight and a fourth weight can be obtained according to the first weight, the second weight and the third preset formula, and the third weight represents the proportion of the median in the standard value, and the fourth weight represents the proportion of the average in the standard value. The standard value of the target evaluation index can be obtained according to the target median, the target average value, the third weight, the fourth weight and the fourth preset formula.

[0099] In a possible embodiment, by calculating the standard values ​​of multiple evaluation indicators in the target evaluation indicator set, a standard value set is obtained. The standard value set provides a quantitative benchmark for evaluating the preset thin-walled cable trench. By calculating the gap between the actual evaluation indicator value and the standard value of the preset thin-walled cable trench, the evaluation score corresponding to each evaluation indicator in the preset thin-walled cable trench can be obtained.

[0100] Optionally, the above step A22, obtaining the evaluation index value corresponding to the target evaluation index from the target sample data set to obtain the first evaluation index value set, may also include the following steps:

[0101] B21. Obtaining evaluation index values ​​corresponding to the target evaluation index from the target sample data set to obtain n evaluation index values; n is a positive integer greater than 1;

[0102] B22, calculating the variance of the n evaluation index values ​​to obtain a first variance;

[0103] B23, calculating the variance of n-1 evaluation index values ​​after the n evaluation index values ​​are removed from the ith evaluation index value, to obtain n variances; the ith evaluation index value is any evaluation index value among the n evaluation index values;

[0104] B24, determining the smallest variance among the n variances to obtain a second variance;

[0105] B25. When the first variance and the second variance meet a first preset condition, determining that the evaluation index value corresponding to the second variance is an abnormal value;

[0106] B26. Remove the abnormal value from the n evaluation index values ​​to obtain a second evaluation index value set;

[0107] B27, determining a target supplementary value according to the abnormal value and the second evaluation index value set;

[0108] B28. Supplement the target supplement value to the second evaluation index value set to obtain the first evaluation index value set.

[0109] Among them, when collecting the construction data of historical cable trenches, outliers may appear due to measurement, data entry, human factors and other factors. Therefore, it is necessary to eliminate these outliers and construct a complete and reliable first evaluation index value set.

[0110] Specifically, the evaluation index value corresponding to the target evaluation index is obtained from the target sample data set to obtain n evaluation index values, where n is the number of collected sample data and n is a positive integer greater than 1. Based on each sample data, the evaluation index value set of the sample prefabricated thin-wall cable can be determined. Therefore, after determining the target evaluation index, n evaluation index values ​​can be obtained according to the target sample data set.

[0111] Further, the variance of n evaluation index values ​​is calculated to obtain a first variance, and then the variance of n-1 evaluation index values ​​after the n evaluation index values ​​are removed from the ith evaluation index value is calculated to obtain n variances, wherein the ith evaluation index value is any evaluation index value among the n evaluation index values, and the smallest variance among the n variances is determined to obtain a second variance, and when the first variance and the second variance meet a first preset condition, the evaluation index value corresponding to the second variance is determined to be an abnormal value.

[0112] In one possible embodiment, n evaluation index values ​​are obtained, and the first variance corresponding to the n evaluation index values ​​is obtained. Then, after removing the i-th evaluation index value, the variance of the remaining n-1 evaluation index values ​​is calculated. Repeating the process can obtain n variances, and the smallest variance among the n variances is determined to be the second variance. Assuming that the first preset condition is that five times the second variance is less than or equal to the first variance, at this time, if the first variance and the second variance meet the first preset condition, it means that after removing the evaluation index value corresponding to the second variance, the variance of the data set is significantly reduced, indicating that the evaluation index value has a greater impact on the stability of the overall data, and therefore, the evaluation index value is confirmed as an abnormal value.

[0113] Specifically, after the outlier is identified, the outlier is removed from the n evaluation index values ​​to obtain the second evaluation index value set. Since the second evaluation index value set is missing values, it may affect the accuracy and reliability of subsequent statistical analysis, so it is necessary to supplement the data. The target supplementary value that needs to be supplemented at the outlier position can be determined based on the outlier and the second evaluation index value set. After determining the target supplementary value, the target supplementary value is supplemented to the second evaluation index value set to obtain the first evaluation index value set, ensuring the integrity and reliability of the data set. The first evaluation index value set can be used to calculate the standard value of the target evaluation index.

[0114] Optionally, the following steps may also be included:

[0115] C21. Obtaining a preset first threshold;

[0116] C22. Obtain a target variance according to the product of the second variance and the preset first threshold;

[0117] C23. If the first variance is greater than or equal to the target variance, determine that the first variance and the second variance satisfy the first preset condition.

[0118] Specifically, the second variance is multiplied by a preset first threshold to obtain a target variance, wherein the preset first threshold may be a system default or pre-set value, and the value indicates the strictness of the abnormal value determination, and the smaller the value, the stricter the abnormal value determination. The size of the first variance and the target variance is determined, and if the first variance is greater than or equal to the target variance, it can be determined that the first variance and the second variance meet the first preset condition.

[0119] Optionally, the above step B27, determining the target supplementary value according to the abnormal value and the second evaluation index value set, may further include the following steps:

[0120] D21, determining the position of the abnormal value in the second evaluation index value set to obtain a target position;

[0121] D22, obtaining adjacent evaluation index values ​​adjacent to the target position in the second evaluation index value set, and obtaining b adjacent evaluation index values; b is a positive integer greater than 1;

[0122] D23, selecting sample evaluation index values ​​from the second evaluation index value set to obtain c sample evaluation index values; c is a positive integer greater than b;

[0123] D24, selecting b sample evaluation index values ​​from the c sample evaluation index values;

[0124] D25. Determine the correlation coefficient corresponding to each of the b sample evaluation index values ​​based on a preset regression algorithm to obtain b correlation coefficients;

[0125] D26. Input the b correlation coefficients and the b adjacent evaluation index values ​​into the preset linear regression equation to obtain the target supplement value.

[0126] Specifically, after obtaining n evaluation index values, each evaluation index value has its corresponding position. This position can be a subscript or a relative position with other evaluation indexes. This position can be used to determine the position of the abnormal value in the second evaluation index value set and obtain the target position. The target position indicates that the data at this position in the second evaluation index value set is empty.

[0127] Furthermore, adjacent evaluation index values ​​adjacent to the target position in the second evaluation index value set are obtained to obtain b adjacent evaluation index values, where b is a positive integer greater than 1. Then, sample evaluation index values ​​are selected from the second evaluation index value set to obtain c sample evaluation index values, where c is a positive integer greater than b. B sample evaluation index values ​​are selected from the c sample evaluation index values ​​to ensure the diversity and randomness of the samples.

[0128] Next, the b sample evaluation index values ​​are used to establish a regression model, and the correlation coefficients of the sample evaluation index values ​​can be calculated based on a preset regression algorithm to obtain b correlation coefficients, wherein the preset regression algorithm can be linear regression, polynomial regression, etc. The b correlation coefficients and the b adjacent evaluation index values ​​are input into a preset linear regression equation to obtain a target supplement value. In the embodiment of the present application, the preset linear regression equation is a polynomial regression equation.

[0129] It should be noted that the target supplementary value is an estimated substitute for the outlier, which is used to fill the missing data in the second evaluation indicator set to obtain a complete set of first evaluation indicator values, ensuring the integrity and reliability of the data for further analysis and evaluation.

[0130] S103, determining the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method, and obtaining an objective weight set.

[0131] Among them, the objective weighting method can be one of the following: entropy weight method, standard deviation method and CRITIC method. The objective weighting method can be used to determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set.

[0132] Specifically, the degree of influence of each evaluation indicator in the target evaluation indicator set on the prefabricated thin-wall cable trench can be determined, and then a score can be given according to the degree of influence. An evaluation matrix can be constructed based on the scoring results, and the evaluation matrix can be analyzed and processed accordingly based on the objective weighting method to obtain the objective weight corresponding to each evaluation indicator.

[0133] Optionally, the above step S103, determining the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain the objective weight set, may also include the following steps:

[0134] A31, determining the influence degree of each evaluation index in the target evaluation index set on the prefabricated thin-wall cable trench, and obtaining multiple influence degrees;

[0135] A32, scoring the evaluation indicators corresponding to the target evaluation indicator set based on the multiple impact levels to obtain multiple evaluation score groups; each evaluation score group includes multiple evaluation scores;

[0136] A33, constructing a target evaluation matrix based on the multiple evaluation score groups; the behavior evaluation indicators of the target evaluation matrix are listed as evaluation scores;

[0137] A34, normalizing the target evaluation matrix to obtain a target standard matrix;

[0138] A35, determining the standardized sum of each evaluation indicator according to the target standard matrix, and obtaining a plurality of standardized sums;

[0139] A36. Determine the entropy value corresponding to each evaluation index according to the multiple standardizations to obtain multiple entropy values;

[0140] A37. Determine the objective weight corresponding to each evaluation indicator according to the multiple entropy values ​​to obtain the objective weight set.

[0141] Specifically, firstly, an influence degree analysis is performed on each evaluation indicator in the target evaluation indicator set to determine the specific influence degree of each evaluation indicator on the performance of prefabricated thin-wall cable trenches, and each evaluation indicator is scored based on these influence degrees to obtain multiple evaluation score groups, each evaluation score group includes multiple evaluation scores, and a target evaluation matrix for calculating the objective weights corresponding to different evaluation indicators can be constructed based on multiple evaluation score groups, wherein the target evaluation matrix is ​​an m×n matrix, the rows of the target evaluation matrix represent evaluation indicators, that is, there are m evaluation indicators, and the columns represent corresponding evaluation scores, that is, each evaluation indicator has n evaluation scores.

[0142] Furthermore, in order to ensure the comparability of the evaluation results, the target evaluation matrix can be normalized to obtain the target standard matrix, where different processing strategies can be adopted according to different evaluation indicators. For example, for evaluation indicators with larger evaluation index values, indicating better performance, forward processing is adopted, otherwise, reverse processing is adopted. For forward processing, the following formula is shown:

[0143]

[0144] In the above formula, v i ` j is the normalized evaluation index value of the positive index, that is, the jth evaluation score of the ith evaluation index; v j is all the evaluation scores of the i-th evaluation index of the target evaluation matrix; v ij is the jth evaluation score of the i-th evaluation indicator in the target evaluation matrix; max{v i} is the maximum value of the i-th evaluation index among all evaluation scores; min{v i} is the minimum value of the i-th evaluation index among all evaluation scores.

[0145] For the inverse processing, the following formula is shown:

[0146]

[0147] In the above formula, v i ` j is the evaluation index value after the inverse index is normalized, that is, the jth evaluation score of the ith evaluation index; v j is all the evaluation scores of the i-th evaluation index of the target evaluation matrix; v ij is the jth evaluation score of the i-th evaluation indicator in the target evaluation matrix; max{v i} is the maximum value of the i-th evaluation index among all evaluation scores; min{v i} is the minimum value of the i-th evaluation index among all evaluation scores.

[0148] Furthermore, the standardized sum of each evaluation index is determined according to the target standard matrix to obtain multiple standardized sums, wherein the standardized sum calculation formula is as follows:

[0149]

[0150] In the above formula, f i is the standardized sum of the i-th evaluation index; v i ` j is the normalized evaluation index value, that is, the j-th evaluation score of the ith evaluation index; m means there are m evaluation indicators.

[0151] Furthermore, according to multiple standardizations and the entropy value corresponding to each evaluation index, multiple entropy values ​​are obtained. The entropy value reflects the amount of information of the evaluation index. The larger the value, the higher the variability of the evaluation index and the lower the contribution to the comprehensive evaluation. The calculation formula of the index entropy value is as follows:

[0152]

[0153] In the above formula, H i is the entropy value of the i-th evaluation index; m means there are m evaluation indicators; f i is the standardized sum of the i-th evaluation index.

[0154] Furthermore, the objective weight corresponding to each evaluation indicator is determined according to the multiple entropy values ​​to obtain the objective weight set, wherein the objective weight calculation formula corresponding to each evaluation indicator is as follows:

[0155]

[0156] In the above formula, ω iis the objective weight of the i-th evaluation index; H i is the entropy value of the i-th evaluation index; m means there are m evaluation indicators.

[0157] Optionally, before step A34, normalizing the target evaluation matrix to obtain the target standard matrix, the following steps may also be included:

[0158] B31, calculating the coefficient of variation corresponding to each evaluation indicator according to the target evaluation matrix to obtain multiple coefficients of variation;

[0159] B32. Obtain a target coefficient of variation; the target coefficient of variation is any coefficient of variation among the multiple coefficients of variation;

[0160] B33. When the target coefficient of variation is greater than a preset second threshold, determining an evaluation index corresponding to the target coefficient of variation to obtain a target evaluation index to be processed;

[0161] B34, re-scoring the target pending evaluation indicators to obtain a plurality of pending evaluation scores;

[0162] B35. Replace the evaluation scores corresponding to the target evaluation indicators to be processed in the target evaluation matrix with the multiple evaluation scores to be processed.

[0163] Specifically, before normalizing the target evaluation matrix, the corresponding coefficient of variation of each evaluation indicator is first calculated according to its evaluation indicator value, and the target coefficient of variation is obtained by obtaining any coefficient of variation from multiple coefficients of variation. The relative discreteness of the evaluation indicator can be obtained by analyzing the target coefficient of variation, thereby determining the indicators that show high volatility or inconsistency in the evaluation indicator set.

[0164] Next, determine whether the target coefficient of variation is greater than the preset second threshold. If so, the evaluation index corresponding to the target coefficient of variation can be determined to obtain the target evaluation index to be processed. The preset second threshold can be a system default or pre-set, and when the target coefficient of variation is greater than the preset second threshold, it indicates that the corresponding evaluation index has great instability and needs further optimization.

[0165] Furthermore, after obtaining the target evaluation indicators to be processed, the target evaluation indicators to be processed are re-scored to further obtain accurate and reliable evaluation scores, and multiple evaluation scores to be processed are obtained. Then, the multiple evaluation scores to be processed replace the evaluation scores corresponding to the target evaluation indicators to be processed in the target evaluation matrix. In this way, the target evaluation matrix can be updated to ensure the robustness of the data in the target evaluation matrix.

[0166] In a possible embodiment, the objective weight corresponding to each evaluation indicator in the target evaluation indicator set is determined based on the objective weighting method to obtain an objective weight set. According to the objective weight set, the importance ratio of each evaluation indicator in the prefabricated thin-walled cable trench can be determined. After scoring each evaluation indicator in the prefabricated thin-walled cable trench, the comprehensive score of the prefabricated thin-walled cable trench can be determined based on the objective weight corresponding to each evaluation indicator.

[0167] S104. Obtain a plurality of prefabricated thin-wall cable trenches.

[0168] In the embodiment of the present application, it is necessary to evaluate and select a prefabricated thin-wall cable trench suitable for a specific power grid construction project from a plurality of prefabricated thin-wall cable trenches. Samples of a plurality of prefabricated thin-wall cable trenches can be obtained from a plurality of suppliers and manufacturers, and a prefabricated thin-wall cable trench with the best comprehensive performance can be selected by comprehensively analyzing the plurality of prefabricated thin-wall cable trenches.

[0169] S105. Determine the actual evaluation index value of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches based on the target evaluation index set to obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values.

[0170] In an embodiment of the present application, the actual evaluation index value of each prefabricated thin-walled cable trench in a plurality of prefabricated thin-walled cable trenches can be determined through the calculation formula of each evaluation index, and the actual evaluation index value represents the actual performance of the prefabricated thin-walled cable trench on each evaluation index, thereby obtaining a plurality of actual evaluation index value groups, each actual evaluation index value group including a plurality of actual evaluation index values.

[0171] In one possible embodiment, by analyzing the actual evaluation index values, it is possible to determine the hardness and strength characteristics of the materials used in the prefabricated thin-walled cable trench, the relationship between the shape of the prefabricated thin-walled cable trench and its internal structure, the difficulty of engineering construction using the prefabricated thin-walled cable trench, the economy of the application of the prefabricated thin-walled cable trench, the time cost of the construction of the prefabricated thin-walled cable trench, and the carbon reduction effect of the application of the prefabricated thin-walled cable trench.

[0172] S106. Score each of the plurality of prefabricated thin-wall cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups.

[0173] Specifically, the prefabricated thin-wall cable trench can be quantitatively scored according to the standard value set, which represents the ideal or average expected performance level of each evaluation indicator. The scoring rules of the evaluation indicators are set by the standard value set, and the prefabricated thin-wall cable trench is scored according to the scoring rules to obtain the actual score of the evaluation indicator value.

[0174] Specifically, any prefabricated thin-walled cable trench is obtained from multiple prefabricated thin-walled cable trenches to obtain a target prefabricated thin-walled cable trench. The target prefabricated thin-walled cable trench has a corresponding actual evaluation index value for each evaluation index. The score corresponding to each evaluation index is determined according to the scoring rules and the actual evaluation index value, and then a scoring group of the target prefabricated thin-walled cable trench is obtained. Multiple scoring groups can be obtained according to multiple prefabricated thin-walled cable trenches.

[0175] Optionally, the above step S106, scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups, may further include the following steps:

[0176] A61, determining a target actual evaluation index value group; the target actual evaluation index value group is any actual evaluation index value group among the multiple actual evaluation index value groups;

[0177] A62, selecting any evaluation index from the target actual evaluation index value group to obtain the target actual evaluation index value;

[0178] A63, determining a standard value corresponding to the target actual evaluation index value according to the standard value set, and obtaining a target standard value;

[0179] A64, determining a mapping relationship between an evaluation index value and an evaluation score according to the target actual evaluation index value and the target standard value, and obtaining a target mapping relationship;

[0180] A65. Determine a target evaluation score according to the target actual evaluation index value and the target mapping relationship;

[0181] A66. Determine the multiple scoring groups according to the target evaluation scores.

[0182] Specifically, any actual evaluation indicator value group is selected from multiple actual evaluation indicator value groups to obtain a target actual evaluation indicator value group. Since the scoring rules have a unified standard for each evaluation indicator, any evaluation indicator is selected from the target actual evaluation indicator value group to obtain a target actual evaluation indicator value. The mapping relationship between the evaluation indicator value and the evaluation score is determined according to the target actual evaluation indicator value and the target standard value to obtain a target mapping relationship. The target evaluation score is determined according to the target actual evaluation indicator value and the target mapping relationship, and then multiple scoring groups are determined according to the target evaluation score.

[0183] In a possible embodiment, for the target evaluation index, its standard value is CX b The actual evaluation index value of prefabricated thin-wall cable trench is CX i , if CX i =CX b, it is considered that the prefabricated thin-wall cable trench has reached the benchmark value under this target evaluation index, and the score is 60 points; if CX i Every super CX b 3%, then based on 60 points plus 5 points each time, for example, CX b The standard value is 60, CX i The actual evaluation index value is 63.6, so CX i Ultra CX b 6%, the score of prefabricated thin-wall cable trench under this target evaluation index is 70 points; if CX i Each low CX b 1%, then based on 60 points minus 5 points each time, for example, CX b The standard value is 60, CX i The actual evaluation index value is 59.4, so CX i Low CX b 1%, and the score of prefabricated thin-wall cable trench under this target evaluation indicator is 55 points.

[0184] S107. Determine an evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups to obtain a plurality of evaluation results.

[0185] Among them, the objective weight set reflects the importance and influence of different evaluation indicators in the overall performance evaluation. Therefore, the comprehensive score of the prefabricated thin-wall cable trench can be obtained according to the scoring group of evaluation indicators in the prefabricated thin-wall cable trench.

[0186] Specifically, the score of each evaluation index of the prefabricated thin-wall cable trench is multiplied by the objective weight corresponding to the evaluation index to calculate a weighted score, and the weighted score of each evaluation index is summed to obtain the evaluation result of the prefabricated thin-wall cable trench, and finally the evaluation result of each prefabricated thin-wall cable trench in multiple prefabricated thin-wall cable trenches is obtained to obtain multiple evaluation results.

[0187] S108. Select a maximum value from the multiple evaluation results, and determine the prefabricated thin-wall cable trench corresponding to the maximum value as the target optimal prefabricated thin-wall cable trench.

[0188] Specifically, a maximum value is selected from multiple evaluation results. This maximum value indicates that under the current target evaluation index set, the comprehensive performance of multiple prefabricated thin-wall cable trenches is optimal. Therefore, the prefabricated thin-wall cable trench corresponding to the maximum value is determined as the target optimal prefabricated thin-wall cable trench.

[0189] In summary, by implementing the embodiments of the present application, a target evaluation index set for evaluating prefabricated thin-walled cable trenches can be determined, and the standard value corresponding to each evaluation index can be determined based on the collected multiple sample data, and the objective weight corresponding to each evaluation index can be determined based on the objective weighting method; after obtaining the actual evaluation index values ​​of multiple prefabricated thin-walled cable trenches, each evaluation index of each prefabricated thin-walled cable trench is scored based on the standard value corresponding to each evaluation index, and multiple scoring groups are obtained. The evaluation results of each prefabricated thin-walled cable trench can be determined based on the multiple scoring groups and the objective weights corresponding to each evaluation index, and finally the prefabricated thin-walled cable trench with the best comprehensive performance is selected based on the multiple evaluation results. Using the prefabricated thin-walled cable trench with the best comprehensive performance in power grid construction can improve construction efficiency, reduce costs and ensure project quality.

[0190] See also Figure 2 , Figure 2 1 is a schematic diagram of the structure of a prefabricated thin-wall cable trench optimization device provided in an embodiment of the present application. The prefabricated thin-wall cable trench optimization device 200 includes: a data acquisition unit 201, a data processing unit 202, a weight analysis unit 203, an evaluation analysis unit 204, and a data output unit 205, wherein:

[0191] The data acquisition unit 201 is used to determine a target evaluation index set for evaluating the prefabricated thin-wall cable trench; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, low carbon and environmental protection;

[0192] The data processing unit 202 is used to obtain a target sample data set, determine the standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of multiple prefabricated thin-wall cable trench samples;

[0193] The weight analysis unit 203 is used to determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set;

[0194] The data acquisition unit 201 is also used to acquire a plurality of prefabricated thin-wall cable trenches;

[0195] The data processing unit 202 is further used to determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set to obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values;

[0196] The evaluation and analysis unit 204 is used to score each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups;

[0197] The evaluation and analysis unit 204 is further used to determine the evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups, to obtain a plurality of evaluation results;

[0198] The data output unit 205 is used to select a maximum value from the multiple evaluation results, and determine the prefabricated thin-wall cable trench corresponding to the maximum value as the target optimal prefabricated thin-wall cable trench.

[0199] Optionally, in determining the standard value corresponding to each evaluation indicator in the target evaluation indicator set according to the target sample data set to obtain the standard value set, the data processing unit 202 is further used to:

[0200] Determine a target evaluation indicator; the target evaluation indicator is any evaluation indicator in the target evaluation indicator set;

[0201] Acquire an evaluation index value corresponding to the target evaluation index from the target sample data set to obtain a first evaluation index value set; the first evaluation index value set includes a plurality of evaluation index values;

[0202] Determine a target maximum index value, a target minimum index value, a target median and a target average value in the first evaluation index value set;

[0203] The first weight is determined based on a first preset formula, where the first preset formula is as follows:

[0204]

[0205] In the formula, α 11 is the first weight; CX is the first evaluation index value set; Max(CX) is the target maximum index value; Min(CX) is the target minimum index value; CX z is the median of the target;

[0206] The second weight is determined based on a second preset formula, where the second preset formula is as follows:

[0207]

[0208] In the formula, β 11 is the second weight; CX p is the target average value;

[0209] The third weight and the fourth weight are determined according to a third preset formula, and the third preset formula is as follows:

[0210]

[0211] Wherein, α1 is the third weight; β1 is the fourth weight;

[0212] The standard value corresponding to the target evaluation index is determined according to the fourth preset formula, and the fourth preset formula is as follows:

[0213] CX b =α1CX z +β1CX p

[0214] Where, CX b is the standard value corresponding to the target evaluation indicator;

[0215] The standard value corresponding to each evaluation indicator in the target evaluation indicator set is determined according to the standard value corresponding to the target evaluation indicator to obtain the standard value set.

[0216] Optionally, in the aspect of acquiring the evaluation index value corresponding to the target evaluation index from the target sample data set to obtain the first evaluation index value set, the data processing unit 202 is further used to:

[0217] Obtaining evaluation index values ​​corresponding to the target evaluation index from the target sample data set to obtain n evaluation index values; n is a positive integer greater than 1;

[0218] Calculating the variance of the n evaluation index values ​​to obtain a first variance;

[0219] Calculate the variance of n-1 evaluation index values ​​after the n evaluation index values ​​are removed from the ith evaluation index value to obtain n variances; the ith evaluation index value is any evaluation index value among the n evaluation index values;

[0220] Determine the smallest variance among the n variances to obtain a second variance;

[0221] When the first variance and the second variance meet a first preset condition, determining that the evaluation index value corresponding to the second variance is an abnormal value;

[0222] Removing the abnormal value from the n evaluation index values ​​to obtain a second evaluation index value set;

[0223] Determine a target supplement value according to the abnormal value and the second evaluation index value set;

[0224] The target supplement value is added to the second evaluation index value set to obtain the first evaluation index value set.

[0225] Optionally, the data processing unit 202 is further configured to:

[0226] Obtaining a preset first threshold;

[0227] Obtaining a target variance according to the product of the second variance and the preset first threshold;

[0228] If the first variance is greater than or equal to the target variance, it is determined that the first variance and the second variance satisfy the first preset condition.

[0229] Optionally, in determining the target supplementary value according to the abnormal value and the second evaluation index value set, the data processing unit 202 is further configured to:

[0230] Determine the position of the abnormal value in the second evaluation index value set to obtain a target position;

[0231] Obtaining adjacent evaluation index values ​​adjacent to the target position in the second evaluation index value set to obtain b adjacent evaluation index values; b is a positive integer greater than 1;

[0232] Selecting sample evaluation index values ​​from the second evaluation index value set to obtain c sample evaluation index values; c is a positive integer greater than b;

[0233] Selecting b sample evaluation index values ​​from the c sample evaluation index values;

[0234] Determine the correlation coefficient corresponding to each sample evaluation index value in the b sample evaluation index values ​​based on a preset regression algorithm to obtain b correlation coefficients;

[0235] The b correlation coefficients and the b adjacent evaluation index values ​​are input into the preset linear regression equation to obtain the target supplement value.

[0236] Optionally, in determining the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain the objective weight set, the weight analysis unit 203 is further used to:

[0237] Determine the influence degree of each evaluation index in the target evaluation index set on the prefabricated thin-wall cable trench, and obtain multiple influence degrees;

[0238] Scoring the evaluation indicators corresponding to the target evaluation indicator set based on the multiple impact levels to obtain multiple evaluation score groups; each evaluation score group includes multiple evaluation scores;

[0239] Constructing a target evaluation matrix based on the multiple evaluation score groups; the behavior evaluation indicators of the target evaluation matrix are listed as evaluation scores;

[0240] Normalizing the target evaluation matrix to obtain a target standard matrix;

[0241] Determine the standardized sum of each evaluation indicator according to the target standard matrix to obtain multiple standardized sums;

[0242] According to the multiple standardizations and determining the entropy value corresponding to each evaluation indicator, a plurality of entropy values ​​are obtained;

[0243] The objective weight corresponding to each evaluation indicator is determined according to the multiple entropy values ​​to obtain the objective weight set.

[0244] Optionally, before normalizing the target evaluation matrix to obtain a target standard matrix, the weight analysis unit 203 is further used to:

[0245] Calculate the coefficient of variation corresponding to each evaluation indicator according to the target evaluation matrix to obtain multiple coefficients of variation;

[0246] Obtaining a target coefficient of variation; the target coefficient of variation is any coefficient of variation among the multiple coefficients of variation;

[0247] When the target coefficient of variation is greater than a preset second threshold, determining an evaluation index corresponding to the target coefficient of variation to obtain a target evaluation index to be processed;

[0248] Re-scoring the target pending evaluation indicators to obtain a plurality of pending evaluation scores;

[0249] The multiple to-be-processed evaluation scores replace the evaluation scores corresponding to the target to-be-processed evaluation indicators in the target evaluation matrix.

[0250] Optionally, in the aspect of scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups, the evaluation and analysis unit 204 is further used to:

[0251] Determine a target actual evaluation index value group; the target actual evaluation index value group is any actual evaluation index value group among the multiple actual evaluation index value groups;

[0252] Select any evaluation index from the target actual evaluation index value group to obtain the target actual evaluation index value;

[0253] Determine the standard value corresponding to the target actual evaluation index value according to the standard value set to obtain the target standard value;

[0254] Determine a mapping relationship between an evaluation index value and an evaluation score according to the target actual evaluation index value and the target standard value, and obtain a target mapping relationship;

[0255] Determine a target evaluation score according to the target actual evaluation index value and the target mapping relationship;

[0256] The multiple scoring groups are determined according to the target evaluation scores.

[0257] The prefabricated thin-walled cable trench optimization device 200 described in the present application can determine the target evaluation index set for evaluating the prefabricated thin-walled cable trench, and determine the standard value corresponding to each evaluation index based on the collected multiple sample data, and determine the objective weight corresponding to each evaluation index based on the objective weighting method; after obtaining the actual evaluation index values ​​of multiple prefabricated thin-walled cable trenches, score each evaluation index of each prefabricated thin-walled cable trench based on the standard value corresponding to each evaluation index, and obtain multiple scoring groups. The evaluation results of each prefabricated thin-walled cable trench can be determined according to the multiple scoring groups and the objective weight corresponding to each evaluation index, and finally the prefabricated thin-walled cable trench with the best comprehensive performance is selected based on the multiple evaluation results. Using the prefabricated thin-walled cable trench with the best comprehensive performance in power grid construction can improve construction efficiency, reduce costs and ensure project quality.

[0258] See also Figure 3 , Figure 3 : is a structural diagram of an electronic device provided in an embodiment of the present application, the electronic device may include a processor, a memory, a communication interface and one or more programs, the processor, the memory and the communication interface may be interconnected through a bus; the one or more programs are stored in the memory and configured to be executed by the processor; in the embodiment of the present application, the program includes instructions for executing the following steps:

[0259] Determine a target evaluation index set for evaluating prefabricated thin-wall cable trenches; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection;

[0260] Acquire a target sample data set, determine a standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of a plurality of prefabricated thin-wall cable trench samples;

[0261] Determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set;

[0262] Obtain multiple prefabricated thin-wall cable trenches;

[0263] Determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set, and obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values;

[0264] Scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups;

[0265] Determine an evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups to obtain a plurality of evaluation results;

[0266] A maximum value is selected from the multiple evaluation results, and the prefabricated thin-wall cable trench corresponding to the maximum value is determined as the target optimal prefabricated thin-wall cable trench.

[0267] The electronic device described in this application can determine the target evaluation index set for evaluating the prefabricated thin-wall cable trench, and determine the standard value corresponding to each evaluation index based on the collected multiple sample data, and determine the objective weight corresponding to each evaluation index based on the objective weighting method; after obtaining the actual evaluation index values ​​of multiple prefabricated thin-wall cable trenches, score each evaluation index of each prefabricated thin-wall cable trench based on the standard value corresponding to each evaluation index, and obtain multiple scoring groups. The evaluation results of each prefabricated thin-wall cable trench can be determined according to the multiple scoring groups and the objective weight corresponding to each evaluation index, and finally the prefabricated thin-wall cable trench with the best comprehensive performance is selected based on the multiple evaluation results. Using the prefabricated thin-wall cable trench with the best comprehensive performance in power grid construction can improve construction efficiency, reduce costs and ensure project quality.

[0268] An embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0269] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0270] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

[0271] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by executing software instructions by a processor. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (electrically EPROM, EEPROM), registers, hard disks, mobile hard disks, read-only compact disks (CD-ROMs) or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and the storage medium can also be present in a terminal device or a management device as discrete components.

[0272] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0273] The modules / units included in the devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least some of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as a chip, circuit module, etc.) or in different components of the chip module, or at least some of the modules / units may be implemented in the form of software programs. The software programs run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits. It is implemented in the form of a software program, which runs on a processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or, at least some modules / units can be implemented in the form of a software program, which runs on a processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in hardware such as circuits.

[0274] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only the specific implementation method of the embodiments of the present application and is not intended to limit the protection scope of the embodiments of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. A method for optimizing the prefabricated thin-wall cable trench, characterized in that: The method comprises: Determine a target evaluation index set for evaluating prefabricated thin-wall cable trenches; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, and low carbon and environmental protection; Acquire a target sample data set, determine a standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of a plurality of prefabricated thin-wall cable trench samples; Determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set; Obtain multiple prefabricated thin-wall cable trenches; Determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set, and obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values; Scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups; Determine an evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups to obtain a plurality of evaluation results; A maximum value is selected from the multiple evaluation results, and the prefabricated thin-wall cable trench corresponding to the maximum value is determined as the target optimal prefabricated thin-wall cable trench.

2. The method according to claim 1, characterized in that The step of determining the standard value corresponding to each evaluation indicator in the target evaluation indicator set according to the target sample data set to obtain the standard value set includes: Determine a target evaluation indicator; the target evaluation indicator is any evaluation indicator in the target evaluation indicator set; Acquire an evaluation index value corresponding to the target evaluation index from the target sample data set to obtain a first evaluation index value set; the first evaluation index value set includes a plurality of evaluation index values; Determine a target maximum index value, a target minimum index value, a target median and a target average value in the first evaluation index value set; The first weight is determined based on a first preset formula, where the first preset formula is as follows: In the formula, α 11 is the first weight; CX is the first evaluation index value set; Max(CX) is the target maximum index value; Min(CX) is the target minimum index value; CX z is the median of the target; The second weight is determined based on a second preset formula, where the second preset formula is as follows: In the formula, β 11 is the second weight; CX p is the target average value; The third weight and the fourth weight are determined according to a third preset formula, and the third preset formula is as follows: Wherein, α1 is the third weight; β1 is the fourth weight; The standard value corresponding to the target evaluation index is determined according to the fourth preset formula, and the fourth preset formula is as follows: CX b =α1CX z +β1CX p Where, CX b is the standard value corresponding to the target evaluation indicator; The standard value corresponding to each evaluation indicator in the target evaluation indicator set is determined according to the standard value corresponding to the target evaluation indicator to obtain the standard value set.

3. The method according to claim 2, characterized in that The step of acquiring the evaluation index value corresponding to the target evaluation index from the target sample data set to obtain a first evaluation index value set includes: Obtaining evaluation index values ​​corresponding to the target evaluation index from the target sample data set to obtain n evaluation index values; n is a positive integer greater than 1; Calculating the variance of the n evaluation index values ​​to obtain a first variance; Calculate the variance of n-1 evaluation index values ​​after the n evaluation index values ​​are removed from the ith evaluation index value to obtain n variances; the ith evaluation index value is any evaluation index value among the n evaluation index values; Determine the smallest variance among the n variances to obtain a second variance; When the first variance and the second variance meet a first preset condition, determining that the evaluation index value corresponding to the second variance is an abnormal value; Removing the abnormal value from the n evaluation index values ​​to obtain a second evaluation index value set; Determine a target supplement value according to the abnormal value and the second evaluation index value set; The target supplement value is added to the second evaluation index value set to obtain the first evaluation index value set.

4. The method according to claim 3, characterized in that The method further comprises: Obtaining a preset first threshold; Obtaining a target variance according to the product of the second variance and the preset first threshold; If the first variance is greater than or equal to the target variance, it is determined that the first variance and the second variance satisfy the first preset condition.

5. The method according to claim 4, characterized in that The determining of the target supplementary value according to the abnormal value and the second evaluation index value set includes: Determine the position of the abnormal value in the second evaluation index value set to obtain a target position; Obtaining adjacent evaluation index values ​​adjacent to the target position in the second evaluation index value set to obtain b adjacent evaluation index values; b is a positive integer greater than 1; Selecting sample evaluation index values ​​from the second evaluation index value set to obtain c sample evaluation index values; c is a positive integer greater than b; Selecting b sample evaluation index values ​​from the c sample evaluation index values; Determine the correlation coefficient corresponding to each sample evaluation index value in the b sample evaluation index values ​​based on a preset regression algorithm to obtain b correlation coefficients; The b correlation coefficients and the b adjacent evaluation index values ​​are input into the preset linear regression equation to obtain the target supplement value.

6. The method according to any one of claims 1 to 5, characterized in that: The objective weight corresponding to each evaluation indicator in the target evaluation indicator set is determined based on the objective weighting method to obtain an objective weight set, including: Determine the influence degree of each evaluation index in the target evaluation index set on the prefabricated thin-wall cable trench, and obtain multiple influence degrees; Scoring the evaluation indicators corresponding to the target evaluation indicator set based on the multiple impact levels to obtain multiple evaluation score groups; each evaluation score group includes multiple evaluation scores; Constructing a target evaluation matrix based on the multiple evaluation score groups; the behavior evaluation indicators of the target evaluation matrix are listed as evaluation scores; Normalizing the target evaluation matrix to obtain a target standard matrix; Determine the standardized sum of each evaluation indicator according to the target standard matrix to obtain multiple standardized sums; According to the multiple standardizations and determining the entropy value corresponding to each evaluation indicator, a plurality of entropy values ​​are obtained; The objective weight corresponding to each evaluation indicator is determined according to the multiple entropy values ​​to obtain the objective weight set.

7. The method according to claim 6, characterized in that Before normalizing the target evaluation matrix to obtain a target standard matrix, the method further includes: Calculate the coefficient of variation corresponding to each evaluation indicator according to the target evaluation matrix to obtain multiple coefficients of variation; Obtaining a target coefficient of variation; the target coefficient of variation is any coefficient of variation among the multiple coefficients of variation; When the target coefficient of variation is greater than a preset second threshold, determining an evaluation index corresponding to the target coefficient of variation to obtain a target evaluation index to be processed; Re-scoring the target pending evaluation indicators to obtain a plurality of pending evaluation scores; The multiple to-be-processed evaluation scores replace the evaluation scores corresponding to the target to-be-processed evaluation indicators in the target evaluation matrix.

8. The method according to any one of claims 1 to 5, characterized in that: The step of scoring each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups includes: Determine a target actual evaluation index value group; the target actual evaluation index value group is any actual evaluation index value group among the multiple actual evaluation index value groups; Select any evaluation index from the target actual evaluation index value group to obtain the target actual evaluation index value; Determine the standard value corresponding to the target actual evaluation index value according to the standard value set to obtain the target standard value; Determine a mapping relationship between an evaluation index value and an evaluation score according to the target actual evaluation index value and the target standard value, and obtain a target mapping relationship; Determine a target evaluation score according to the target actual evaluation index value and the target mapping relationship; The multiple scoring groups are determined according to the target evaluation scores.

9. A prefabricated thin-wall cable trench optimization device, characterized in that: The prefabricated thin-wall cable trench optimization device comprises: a data acquisition unit, a data processing unit, a weight analysis unit, an evaluation analysis unit, and a data output unit, wherein: The data acquisition unit is used to determine a target evaluation index set for evaluating the prefabricated thin-wall cable trench; the target evaluation index set includes: force dimension, structural performance, construction difficulty, economy, time saving, low carbon and environmental protection; The data processing unit is used to obtain a target sample data set, determine the standard value corresponding to each evaluation index in the target evaluation index set according to the target sample data set, and obtain a standard value set; the target sample data set includes evaluation index values ​​of multiple prefabricated thin-wall cable trench samples; The weight analysis unit is used to determine the objective weight corresponding to each evaluation indicator in the target evaluation indicator set based on the objective weighting method to obtain an objective weight set; The data acquisition unit is also used to acquire a plurality of prefabricated thin-wall cable trenches; The data processing unit is further used to determine the actual evaluation index value of each prefabricated thin-walled cable trench in the plurality of prefabricated thin-walled cable trenches based on the target evaluation index set to obtain a plurality of actual evaluation index value groups; each actual evaluation index value group includes a plurality of actual evaluation index values; The evaluation and analysis unit is used to score each of the plurality of prefabricated thin-walled cable trenches according to the standard value set and the plurality of actual evaluation index value groups to obtain a plurality of scoring groups; The evaluation and analysis unit is further used to determine the evaluation result of each prefabricated thin-wall cable trench in the plurality of prefabricated thin-wall cable trenches according to the objective weight set and the plurality of scoring groups, to obtain a plurality of evaluation results; The data output unit is used to select a maximum value from the multiple evaluation results, and determine the prefabricated thin-wall cable trench corresponding to the maximum value as the target optimal prefabricated thin-wall cable trench.

10. An electronic device, characterized in that: include: A processor, a memory, a communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for executing the steps in the method according to any one of claims 1 to 8.

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