A method and device for optimizing experimental schemes for chemical defense and decontamination material consumption

Abstract

The present invention discloses a method and device for optimizing a chemical defense and decontamination material consumption experimental plan. The method comprises the following steps: obtaining experimental factor information and experimental equipment information; screening and processing the experimental factor information to obtain key factor information; the key factor information includes a plurality of key factors; processing the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information; designing a plan based on the key factor information and the factor level information to obtain initial experimental plan information; and simulating and deducing the initial experimental plan information to obtain simulation result information. It can be seen that the present invention is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, thereby reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental plan combination explosion.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for optimizing a chemical defense and decontamination material consumption experimental plan. Background Art

[0002] At present, the existing design methods of chemical defense and decontamination material consumption experimental schemes mainly include k There are several experimental scheme designs, such as factor-based experimental scheme design, orthogonal sampling-based experimental scheme design, Latin square sampling-based experimental scheme design, and uniform sampling-based experimental scheme design. However, the above design methods have the following two problems: the number of simulation experiments and the amount of calculation will increase rapidly with the increase of factors and levels. When the factors and levels continue to increase, the number of experiments will tend to be infinite, which will eventually lead to the inability to effectively carry out simulation experiments; using any experimental scheme design method independently, it is difficult to effectively select the most typical combination factors and design effective factor combinations, and it is difficult to make scientific and reasonable predictions on the consumption of chemical defense and decontamination materials. Therefore, a method and device for optimizing the experimental scheme for the consumption of chemical defense and decontamination materials is provided to eliminate unreasonable experimental factors and levels, compress the experimental scope, and thereby reduce the number of experiments, improve experimental efficiency, and solve the problem of experimental scheme combination explosion. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and device for optimizing the experimental scheme of chemical defense and decontamination material consumption, which can obtain simulation result information for determining the experimental scheme of chemical defense and decontamination material consumption through comprehensive processing of experimental factor information and experimental equipment information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of explosion of experimental scheme combinations.

[0004] In order to solve the above technical problems, the first aspect of the embodiment of the present invention discloses a method for optimizing a chemical defense and decontamination material consumption experimental plan, the method comprising:

[0005] Obtain experimental factor information and experimental equipment information;

[0006] Screening the experimental factor information to obtain key factor information; the key factor information includes several key factors;

[0007] Processing the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information;

[0008] Performing a program design on the key factor information and the factor level information to obtain initial experimental program information;

[0009] The initial experimental scheme information is simulated and deduced to obtain simulation result information; the simulation result information is used to optimize the initial experimental scheme information to obtain a chemical defense and decontamination material consumption experimental scheme.

[0010] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the screening process of the experimental factor information to obtain key factor information includes:

[0011] Calculating and processing the experimental factor information to obtain sensitivity value information; the experimental factor information includes a plurality of experimental factors; the sensitivity value information includes a plurality of sensitivity values; each of the experimental factors corresponds to a unique sensitivity value;

[0012] The experimental factor information is screened using a preset dynamic threshold judgment model and the sensitivity value information to obtain key factor information.

[0013] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the use of the preset dynamic threshold judgment model and the sensitivity value information to screen the experimental factor information to obtain key factor information includes:

[0014] performing grouping processing on the experimental factor information to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor;

[0015] Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value;

[0016] Performing trajectory expected value calculation processing on the sensitivity group information to obtain sensitivity trajectory expected value information; the sensitivity trajectory expected value information includes a plurality of sensitivity trajectory expected values; each of the factor groups corresponds to a unique sensitivity trajectory expected value;

[0017] Using a preset dynamic threshold judgment model, the factor group information and the sensitivity group information are calculated and processed to obtain dynamic threshold information; the dynamic threshold information includes a plurality of dynamic thresholds; each factor group corresponds to a unique dynamic threshold;

[0018] The dynamic threshold information and the sensitivity trajectory expected value information are used to judge and screen the factor group information to obtain key factor information.

[0019] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the use of the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information to obtain key factor information includes:

[0020] Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information to obtain target trajectory expected value information; the target trajectory expected value information includes a plurality of target trajectory expected values;

[0021] Using the target trajectory expected value information to match the factor group information to obtain target factor group information;

[0022] Determine whether the target factor group information meets a search termination condition, and obtain a search judgment result; the search termination condition is related to the number of key factors in the target factor group;

[0023] When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process of the factor group information and the sensitivity value information is triggered to obtain sensitivity group information;

[0024] When the search judgment result is yes, key factor information is determined according to the target factor group information.

[0025] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the performing of a scheme design on the key factor information and the factor level information to obtain initial experimental scheme information includes:

[0026] Constructing a combination experiment design table according to the key factor information and the factor level information; the combination experiment design table includes information of several experimental combination factors;

[0027] According to the combination experiment design table, initial experimental scheme information is determined; the initial experimental scheme information includes a plurality of initial experimental schemes; the number of the initial experimental schemes is consistent with the number of the experimental combination factor information.

[0028] As an optional implementation manner, in the first aspect of the embodiment of the present invention, constructing a combination experimental design table according to the key factor information and the factor level information includes:

[0029] Determine the number of rows in the table according to the number of factors in the key factor information;

[0030] Constructing table information corresponding to each key factor according to a common divisor relationship among the number of table rows, the factor level information, and the number of factors in the key factor information;

[0031] Based on all the tabular information, a combined experimental design table is determined.

[0032] As an optional implementation manner, in the first aspect of the embodiment of the present invention, after simulating and deducing the initial experimental plan information to obtain simulation result information, the method further includes:

[0033] Performing regression analysis on the simulation result information to obtain confidence information;

[0034] Determining whether the confidence information meets the confidence level, and obtaining a confidence determination result;

[0035] When the confidence judgment result is negative, optimizing the key factor information, and triggering the step of processing the key factor information using the experimental equipment information to obtain factor level information;

[0036] When the confidence judgment result is yes, the chemical defense and decontamination material consumption experimental plan is determined according to the initial experimental plan information.

[0037] A second aspect of an embodiment of the present invention discloses a device for optimizing a chemical defense and decontamination material consumption experimental plan, the device comprising:

[0038] Acquisition module, used to obtain experimental factor information and experimental equipment information;

[0039] A first processing module is used to screen the experimental factor information to obtain key factor information; the key factor information includes a plurality of key factors;

[0040] A second processing module is configured to process the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information;

[0041] A design module is used to design a scheme based on the key factor information and the factor level information to obtain initial experimental scheme information;

[0042] The simulation module is used to simulate and deduce the initial experimental plan information to obtain simulation result information; the simulation result information is used to optimize the initial experimental plan information to obtain a chemical defense and decontamination material consumption experimental plan.

[0043] As an optional implementation, in the second aspect of the embodiment of the present invention, the first processing module screens the experimental factor information to obtain the key factor information in the following manner:

[0044] Calculating and processing the experimental factor information to obtain sensitivity value information; the experimental factor information includes a plurality of experimental factors; the sensitivity value information includes a plurality of sensitivity values; each of the experimental factors corresponds to a unique sensitivity value;

[0045] The experimental factor information is screened using a preset dynamic threshold judgment model and the sensitivity value information to obtain key factor information.

[0046] As an optional implementation, in the second aspect of the embodiment of the present invention, the first processing module uses a preset dynamic threshold judgment model and the sensitivity value information to screen the experimental factor information, and the specific method of obtaining the key factor information is as follows:

[0047] performing grouping processing on the experimental factor information to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor;

[0048] Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value;

[0049] Performing trajectory expected value calculation processing on the sensitivity group information to obtain sensitivity trajectory expected value information; the sensitivity trajectory expected value information includes a plurality of sensitivity trajectory expected values; each of the factor groups corresponds to a unique sensitivity trajectory expected value;

[0050] Using a preset dynamic threshold judgment model, the factor group information and the sensitivity group information are calculated and processed to obtain dynamic threshold information; the dynamic threshold information includes a plurality of dynamic thresholds; each factor group corresponds to a unique dynamic threshold;

[0051] The dynamic threshold information and the sensitivity trajectory expected value information are used to judge and screen the factor group information to obtain key factor information.

[0052] As an optional implementation, in the second aspect of the embodiment of the present invention, the first processing module uses the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information, and the specific method of obtaining the key factor information is:

[0053] Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information to obtain target trajectory expected value information; the target trajectory expected value information includes a plurality of target trajectory expected values;

[0054] Using the target trajectory expected value information to match the factor group information to obtain target factor group information;

[0055] Determine whether the target factor group information meets a search termination condition, and obtain a search judgment result; the search termination condition is related to the number of key factors in the target factor group;

[0056] When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process of the factor group information and the sensitivity value information is triggered to obtain sensitivity group information;

[0057] When the search judgment result is yes, key factor information is determined according to the target factor group information.

[0058] As an optional implementation, in the second aspect of the embodiment of the present invention, the design module performs a scheme design on the key factor information and the factor level information to obtain the initial experimental scheme information in the following specific manner:

[0059] Constructing a combination experiment design table according to the key factor information and the factor level information; the combination experiment design table includes information of several experimental combination factors;

[0060] According to the combination experiment design table, initial experimental scheme information is determined; the initial experimental scheme information includes a plurality of initial experimental schemes; the number of the initial experimental schemes is consistent with the number of the experimental combination factor information.

[0061] As an optional implementation, in the second aspect of the embodiment of the present invention, the specific manner in which the design module constructs the combined experimental design table according to the key factor information and the factor level information is:

[0062] Determine the number of rows in the table according to the number of factors in the key factor information;

[0063] Constructing table information corresponding to each key factor according to a common divisor relationship among the number of table rows, the factor level information, and the number of factors in the key factor information;

[0064] Based on all the tabular information, a combined experimental design table is determined.

[0065] As an optional implementation manner, in the second aspect of the embodiment of the present invention, after the simulation module simulates and deduces the initial experimental plan information to obtain simulation result information, the device further includes:

[0066] A determination module, configured to perform regression analysis on the simulation result information to obtain confidence information;

[0067] Determining whether the confidence information meets the confidence level, and obtaining a confidence determination result;

[0068] When the confidence judgment result is negative, optimizing the key factor information, and triggering the step of processing the key factor information using the experimental equipment information to obtain factor level information;

[0069] When the confidence judgment result is yes, the chemical defense and decontamination material consumption experimental plan is determined according to the initial experimental plan information.

[0070] A third aspect of the present invention discloses another device for optimizing a chemical defense and decontamination material consumption experimental plan, the device comprising:

[0071] a memory storing executable program code;

[0072] a processor coupled to the memory;

[0073] The processor calls the executable program code stored in the memory to execute some or all of the steps in the method for optimizing the chemical defense and decontamination material consumption experimental plan disclosed in the first aspect of the embodiment of the present invention.

[0074] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the method for optimizing the consumption of chemical defense and decontamination materials disclosed in the first aspect of an embodiment of the present invention.

[0075] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0076] In an embodiment of the present invention, experimental factor information and experimental equipment information are obtained; the experimental factor information is screened and processed to obtain key factor information; the key factor information includes several key factors; the key factor information is processed using the experimental equipment information to obtain factor level information; the factor level information includes several level value information; each key factor corresponds to a unique level value information; a scheme is designed for the key factor information and the factor level information to obtain initial experimental scheme information; the initial experimental scheme information is simulated and deduced to obtain simulation result information; the simulation result information is used to optimize the initial experimental scheme information to obtain an experimental scheme for the consumption of chemical defense and decontamination materials. It can be seen that the present invention is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, thereby reducing the number of experiments, improving experimental efficiency, and solving the problem of explosion of experimental scheme combinations. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0078] Figure 1 This is a flow chart of a method for optimizing a chemical defense and decontamination material consumption experimental plan disclosed in an embodiment of the present invention;

[0079] Figure 2 This is a flow chart of another method for optimizing a chemical defense and decontamination material consumption experimental plan disclosed in an embodiment of the present invention;

[0080] Figure 3 This is a schematic diagram of the structure of a device for optimizing a chemical defense and decontamination material consumption experimental plan disclosed in an embodiment of the present invention;

[0081] Figure 4 This is a schematic structural diagram of another device for optimizing a chemical defense and decontamination material consumption experimental plan disclosed in an embodiment of the present invention;

[0082] Figure 5 It is a structural schematic diagram of another device for optimizing a chemical defense and decontamination material consumption experimental scheme disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0083] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0084] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different objects, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or device.

[0085] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0086] The present invention discloses a method and device for optimizing experimental plans for chemical defense and decontamination material consumption. By comprehensively processing experimental factor information and experimental equipment information, the method generates simulation results for determining experimental plans for chemical defense and decontamination material consumption. This method facilitates eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thereby reducing the number of experiments, improving experimental efficiency, and resolving the problem of experimental plan combination explosion. These are described in detail below.

[0087] Example 1

[0088] See also Figure 1 , Figure 1 This is a flow chart of a method for optimizing a chemical defense and decontamination material consumption experimental scheme disclosed in an embodiment of the present invention. Figure 1 The described method for optimizing the experimental program for consumption of chemical defense and decontamination materials is applied to a data processing system, such as a local server or cloud server for optimizing and managing the experimental program for consumption of chemical defense and decontamination materials, and is not limited in the embodiment of the present invention. Figure 1 As shown, the chemical defense and decontamination material consumption experimental program optimization method may include the following operations:

[0089] 101. Obtain experimental factor information and experimental equipment information.

[0090] 102. Screen and process the experimental factor information to obtain key factor information.

[0091] In the embodiment of the present invention, the above-mentioned key factor information includes several key factors.

[0092] 103. Use experimental equipment information to process key factor information and obtain factor level information.

[0093] In the embodiment of the present invention, the above-mentioned factor level information includes a plurality of level value information.

[0094] In the embodiment of the present invention, each of the above key factors corresponds to a unique level value information.

[0095] 104. Design a plan based on the key factor information and factor level information to obtain the initial experimental plan information.

[0096] 105. Simulate and deduce the initial experimental plan information to obtain simulation result information.

[0097] In an embodiment of the present invention, the above-mentioned simulation result information is used to optimize the initial experimental plan information to obtain an experimental plan for the consumption of chemical defense and decontamination materials.

[0098] Optionally, the above-mentioned experimental equipment information includes equipment type and / or equipment model, which is not limited in the embodiment of the present invention.

[0099] Optionally, the factor levels in the above-mentioned level value information include battlefield environment, and / or ammunition type, and / or target type, and / or damage requirements, which are not limited in this embodiment of the present invention.

[0100] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can obtain simulation result information for determining the chemical defense and decontamination material consumption experimental scheme through comprehensive processing of experimental factor information and experimental equipment information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0101] In an optional embodiment, the above-mentioned screening process of the experimental factor information to obtain key factor information includes:

[0102] The experimental factor information is calculated and processed to obtain sensitivity value information; the experimental factor information includes several experimental factors; the sensitivity value information includes several sensitivity values; each experimental factor corresponds to a unique sensitivity value;

[0103] The preset dynamic threshold judgment model and sensitivity value information are used to screen the experimental factor information to obtain the key factor information.

[0104] In this optional embodiment, as an optional implementation, the specific method of calculating and processing the experimental factor information to obtain the sensitivity value information is as follows:

[0105] For any experimental factor, determine the optional maximum value and optional minimum value of the experimental factor according to the value range of the experimental factor;

[0106] Determine a first response value according to the optional maximum value;

[0107] Determine a second response value according to the optional minimum value;

[0108] Calculate the difference between the first response value and the second response value to obtain the sensitivity value corresponding to the experimental factor.

[0109] Optionally, a larger sensitivity value indicates a higher sensitivity of the experimental factor, and a smaller sensitivity value indicates a lower sensitivity of the experimental factor.

[0110] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can obtain key factor information by screening and processing the experimental factor information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0111] In another optional embodiment, the above-mentioned use of the preset dynamic threshold judgment model and sensitivity value information to screen the experimental factor information to obtain key factor information includes:

[0112] The experimental factor information is grouped to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor;

[0113] Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value;

[0114] Perform trajectory expectation calculation on the sensitivity group information to obtain sensitivity trajectory expectation value information; the sensitivity trajectory expectation value information includes a plurality of sensitivity trajectory expectation values; each factor group corresponds to a unique sensitivity trajectory expectation value;

[0115] The factor group information and sensitivity group information are calculated and processed using a preset dynamic threshold judgment model to obtain dynamic threshold information; the dynamic threshold information includes several dynamic thresholds; each factor group corresponds to a unique dynamic threshold;

[0116] Dynamic threshold information and sensitivity trajectory expected value information are used to judge and screen factor group information to obtain key factor information.

[0117] Optionally, the specific form of the above dynamic threshold judgment model is:

[0118]

[0119] Where R is the dynamic threshold; θ i is the sensitivity value corresponding to the i-th key factor, i = 1, 2, ... n; F j is the value corresponding to the jth key factor, j = 1, 2, ... n; is a random variable; n is the number of key factors in the factor group.

[0120] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can use the preset dynamic threshold judgment model and sensitivity value information to screen and process the experimental factor information to obtain key factor information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0121] In another optional embodiment, the dynamic threshold information and sensitivity trajectory expected value information are used to judge and screen the factor group information to obtain key factor information, including:

[0122] Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information, the target trajectory expected value information is obtained; the target trajectory expected value information includes a plurality of target trajectory expected values;

[0123] The target trajectory expected value information is used to match the factor group information to obtain the target factor group information;

[0124] Determine whether the target factor group information meets the search termination condition and obtain the search judgment result; the search termination condition is related to the number of key factors in the target factor group;

[0125] When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process between the factor group information and the sensitivity value information is triggered to obtain the sensitivity group information;

[0126] When the search judgment result is yes, the key factor information is determined based on the target factor group information.

[0127] In this optional embodiment, as an optional implementation, the above-mentioned method of using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information to obtain the target trajectory expected value information is as follows:

[0128] For any sensitivity trajectory expected value, determine whether the sensitivity trajectory expected value is greater than or equal to the dynamic threshold corresponding to the sensitivity trajectory expected value, and obtain a threshold judgment result;

[0129] When the threshold judgment result is yes, the sensitivity trajectory expected value is determined to be a target trajectory expected value.

[0130] Optionally, the above search termination condition is that the number of key factors in the target factor group is 1.

[0131] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can use dynamic threshold information and sensitivity trajectory expected value information to judge and screen factor group information, obtain key factor information, and be more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0132] Example 2

[0133] See also Figure 2 , Figure 2 This is a flow chart of another method for optimizing the experimental scheme of chemical defense and decontamination material consumption disclosed in an embodiment of the present invention. Figure 2 The described method for optimizing the experimental program for consumption of chemical defense and decontamination materials is applied to a data processing system, such as a local server or cloud server for optimizing and managing the experimental program for consumption of chemical defense and decontamination materials, and is not limited in the embodiment of the present invention. Figure 2 As shown, the chemical defense and decontamination material consumption experimental program optimization method may include the following operations:

[0134] 201. Obtain experimental factor information and experimental equipment information.

[0135] 202. Screen and process the experimental factor information to obtain key factor information.

[0136] 203. Use experimental equipment information to process key factor information and obtain factor level information.

[0137] 204. Design a plan based on the key factor information and factor level information to obtain the initial experimental plan information.

[0138] 205. Construct a combination experiment design table based on key factor information and factor level information.

[0139] In the embodiment of the present invention, the above-mentioned combination experiment design table includes information of several experimental combination factors.

[0140] 206. Determine the initial experimental plan information based on the combined experimental design table.

[0141] In the embodiment of the present invention, the initial experimental plan information includes several initial experimental plans.

[0142] In the embodiment of the present invention, the number of the initial experimental schemes is consistent with the number of experimental combination factor information.

[0143] In the embodiment of the present invention, for the specific technical details and technical terminology of steps 201 to 204, reference can be made to the detailed description of steps 101 to 104 in the first embodiment, and will not be repeated in detail in the embodiment of the present invention.

[0144] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can obtain simulation result information for determining the chemical defense and decontamination material consumption experimental scheme through comprehensive processing of experimental factor information and experimental equipment information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0145] In an optional embodiment, the above-mentioned construction of a combined experimental design table based on key factor information and factor level information includes:

[0146] Determine the number of rows in the table based on the number of factors in the key factor information;

[0147] Construct the table information corresponding to each key factor according to the common divisor relationship between the number of table rows, factor level information and the number of factors in the key factor information;

[0148] Based on all the tabular information, determine the combined experimental design table.

[0149] Optionally, each level of the key factor in the above combination experiment design table is only subjected to one experiment, and the experimental points of any two key factors are on the grid points of the plane, with only one experimental point in each row and column.

[0150] For example, the factors and factor levels of key factors include: agent type (nuclear attack, sarin gas attack, soman gas attack, VEX gas attack, biological attack), terrain (irrigated rice paddies, plains, hilly land, Gobi desert, alpine mountainous area), meteorological conditions (heavy rain, heavy snow, strong winds, heavy fog, sandstorms), and disinfection type (road disinfection, area disinfection, equipment disinfection, equipment elimination, personnel decontamination). Following the above method, the columns are constructed using the greatest common divisor of 1 for key factors 1 to 4 (agent type, terrain, meteorological conditions, and disinfection type) and the number of factor levels (5). The number of rows in the table is determined by the number of factor levels (5). The resulting combined experimental design table is as follows.

[0151] Type of poison Terrain conditions Weather conditions Disinfection type 1 nuclear attack plains Windy weather Equipment elimination 2 Sarin gas attack Gobi Desert sandstorm weather Road disinfection 3 Soman gas attack Water network rice fields Heavy snow Equipment disinfection 4 Vierx gas attack hilly land Foggy weather Personnel disinfection 5 Biological attack High and cold mountainous areas Heavy rain Area disinfection

[0152] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can construct a combination experimental design table based on key factor information and factor level information, which is more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0153] In another optional embodiment, after performing simulation on the initial experimental plan information to obtain simulation result information, the method further includes:

[0154] Perform regression analysis on the simulation result information to obtain confidence information;

[0155] Determine whether the confidence information meets the confidence level and obtain a confidence judgment result;

[0156] When the confidence judgment result is negative, the key factor information is optimized and triggered to process the key factor information using the experimental equipment information to obtain the factor level information;

[0157] When the confidence judgment result is yes, the chemical defense and decontamination material consumption experimental plan is determined based on the initial experimental plan information.

[0158] Optionally, based on the confidence level obtained, establish a chemical defense and decontamination material consumption experimental plan for the five key factors of the above-mentioned toxic agent type, terrain conditions, meteorological conditions and disinfection type, and determine the level values of the factor levels in the plan. According to the method of conducting one experiment for each key factor combination, a comprehensive experiment needs to be conducted for five times. 4 The orthogonal design method needs to be used for 5 simulation experiments. 2 However, the method of this application only needs to conduct 5 simulation experiments to ensure the experimental effect, which reduces the complexity of the experiment.

[0159] It can be seen that the implementation of the chemical defense and decontamination material consumption experimental scheme optimization method described in the embodiment of the present invention can comprehensively process the simulation result information to obtain the chemical defense and decontamination material consumption experimental scheme, which is more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0160] Example 3

[0161] See also Figure 3 , Figure 3 This is a schematic diagram of a device for optimizing the experimental scheme for chemical defense and decontamination material consumption disclosed in an embodiment of the present invention. Figure 3 The described device can be applied to a data processing system, such as a local server or cloud server for optimizing and managing experimental plans for consumption of chemical defense and decontamination materials, and the embodiments of the present invention do not limit this. Figure 3 As shown, the device may include:

[0162] Acquisition module, used to obtain experimental factor information and experimental equipment information;

[0163] The first processing module is used to screen the experimental factor information to obtain key factor information; the key factor information includes several key factors;

[0164] The second processing module is used to process the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information;

[0165] Design module, used to design schemes based on key factor information and factor level information to obtain initial experimental scheme information;

[0166] The simulation module is used to simulate and deduce the initial experimental plan information to obtain simulation result information; the simulation result information is used to optimize the initial experimental plan information to obtain a chemical defense and decontamination material consumption experimental plan.

[0167] It can be seen that implementation Figure 3 The described chemical defense and decontamination material consumption experimental scheme optimization device can obtain simulation result information for determining the chemical defense and decontamination material consumption experimental scheme through comprehensive processing of experimental factor information and experimental equipment information. It is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0168] In another optional embodiment, Figure 4 As shown, the first processing module screens the experimental factor information to obtain the key factor information in the following manner:

[0169] The experimental factor information is calculated and processed to obtain sensitivity value information; the experimental factor information includes several experimental factors; the sensitivity value information includes several sensitivity values; each experimental factor corresponds to a unique sensitivity value;

[0170] The preset dynamic threshold judgment model and sensitivity value information are used to screen the experimental factor information to obtain the key factor information.

[0171] It can be seen that implementation Figure 4 The described device for optimizing experimental schemes for consumption of chemical defense and decontamination materials can obtain key factor information by screening and processing experimental factor information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of explosion of experimental scheme combinations.

[0172] In another optional embodiment, Figure 4 As shown, the first processing module uses the preset dynamic threshold judgment model and sensitivity value information to screen the experimental factor information, and the specific method of obtaining the key factor information is as follows:

[0173] The experimental factor information is grouped to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor;

[0174] Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value;

[0175] Perform trajectory expectation calculation on the sensitivity group information to obtain sensitivity trajectory expectation value information; the sensitivity trajectory expectation value information includes a plurality of sensitivity trajectory expectation values; each factor group corresponds to a unique sensitivity trajectory expectation value;

[0176] The factor group information and sensitivity group information are calculated and processed using a preset dynamic threshold judgment model to obtain dynamic threshold information; the dynamic threshold information includes several dynamic thresholds; each factor group corresponds to a unique dynamic threshold;

[0177] Dynamic threshold information and sensitivity trajectory expected value information are used to judge and screen factor group information to obtain key factor information.

[0178] It can be seen that implementation Figure 4 The described device for optimizing experimental schemes for consumption of chemical defense and decontamination materials can use a preset dynamic threshold judgment model and sensitivity value information to screen and process experimental factor information to obtain key factor information, which is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thereby reducing the number of experiments, improving experimental efficiency, and solving the problem of explosion of experimental scheme combinations.

[0179] In another optional embodiment, Figure 4 As shown, the first processing module uses the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information, and the specific method of obtaining the key factor information is as follows:

[0180] Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information, the target trajectory expected value information is obtained; the target trajectory expected value information includes a plurality of target trajectory expected values;

[0181] The target trajectory expected value information is used to match the factor group information to obtain the target factor group information;

[0182] Determine whether the target factor group information meets the search termination condition and obtain the search judgment result; the search termination condition is related to the number of key factors in the target factor group;

[0183] When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process between the factor group information and the sensitivity value information is triggered to obtain the sensitivity group information;

[0184] When the search judgment result is yes, the key factor information is determined based on the target factor group information.

[0185] It can be seen that implementation Figure 4 The described chemical defense and decontamination material consumption experimental scheme optimization device can use dynamic threshold information and sensitivity trajectory expected value information to judge and screen factor group information to obtain key factor information, which is more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0186] In another optional embodiment, Figure 4 As shown in the figure, the design module designs the key factor information and factor level information, and the specific method of obtaining the initial experimental plan information is as follows:

[0187] Construct a combination experiment design table based on key factor information and factor level information; the combination experiment design table includes information on several experimental combination factors;

[0188] According to the combination experiment design table, the initial experimental plan information is determined; the initial experimental plan information includes several initial experimental plans; the number of initial experimental plans is consistent with the number of experimental combination factor information.

[0189] It can be seen that implementation Figure 4 The described chemical defense and decontamination material consumption experimental scheme optimization device can obtain simulation result information for determining the chemical defense and decontamination material consumption experimental scheme through comprehensive processing of experimental factor information and experimental equipment information. It is conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0190] In another optional embodiment, Figure 4 As shown in the figure, the specific way in which the design module constructs the combined experimental design table based on the key factor information and factor level information is as follows:

[0191] Determine the number of rows in the table based on the number of factors in the key factor information;

[0192] Construct the table information corresponding to each key factor according to the common divisor relationship between the number of table rows, factor level information and the number of factors in the key factor information;

[0193] Based on all the tabular information, determine the combined experimental design table.

[0194] It can be seen that implementation Figure 4The described device for optimizing experimental schemes for consumption of chemical defense and decontamination materials can construct a combination experimental design table based on key factor information and factor level information, which is more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of explosion of experimental scheme combinations.

[0195] In another optional embodiment, Figure 4 As shown, after the simulation module simulates and deduces the initial experimental plan information to obtain simulation result information, the device further includes:

[0196] A determination module is used to perform regression analysis on the simulation result information to obtain confidence information;

[0197] Determine whether the confidence information meets the confidence level and obtain a confidence judgment result;

[0198] When the confidence judgment result is negative, the key factor information is optimized and triggered to process the key factor information using the experimental equipment information to obtain the factor level information;

[0199] When the confidence judgment result is yes, the chemical defense and decontamination material consumption experimental plan is determined based on the initial experimental plan information.

[0200] It can be seen that implementation Figure 4 The described chemical defense and decontamination material consumption experimental scheme optimization device can comprehensively process the simulation result information to obtain the chemical defense and decontamination material consumption experimental scheme, which is more conducive to eliminating unreasonable experimental factors and levels, compressing the experimental scope, and thus reducing the number of experiments, improving experimental efficiency, and solving the problem of experimental scheme combination explosion.

[0201] Example 4

[0202] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of another device for optimizing the experimental scheme of chemical defense and decontamination material consumption disclosed in an embodiment of the present invention. Figure 5 The described device can be applied to a data processing system, such as a local server or cloud server for optimizing and managing experimental plans for consumption of chemical defense and decontamination materials, and the embodiments of the present invention do not limit this. Figure 5 As shown, the device may include:

[0203] A memory 401 storing executable program code;

[0204] a processor 402 coupled to the memory 401;

[0205] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the method for optimizing the chemical defense and decontamination material consumption experimental plan described in Example 1 or Example 2.

[0206] Example 5

[0207] An embodiment of the present invention discloses a computer-readable storage medium that stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the method for optimizing the experimental plan for consumption of chemical defense and decontamination materials described in Example 1 or Example 2.

[0208] Example 6

[0209] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the method for optimizing the consumption experimental plan of chemical defense and decontamination materials described in Example 1 or Example 2.

[0210] The device embodiments described above are merely illustrative. Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0211] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0212] Finally, it should be noted that the method and device for optimizing the experimental scheme for consumption of chemical defense and decontamination materials disclosed in the embodiment of the present invention only disclose a preferred embodiment of the present invention, which is only used to illustrate the technical scheme of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical schemes recorded in the aforementioned embodiments, or to make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical schemes from the spirit and scope of the technical schemes of the various embodiments of the present invention.

Claims

1. A method for optimizing a chemical defense and decontamination material consumption experimental plan, characterized in that: The method comprises: Obtain experimental factor information and experimental equipment information; Screening the experimental factor information to obtain key factor information; the key factor information includes several key factors; Processing the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information; Performing a program design on the key factor information and the factor level information to obtain initial experimental program information; The initial experimental scheme information is simulated and deduced to obtain simulation result information; the simulation result information is used to optimize the initial experimental scheme information to obtain a chemical defense and decontamination material consumption experimental scheme; The screening of the experimental factor information to obtain key factor information includes: Calculating and processing the experimental factor information to obtain sensitivity value information; the experimental factor information includes a plurality of experimental factors; the sensitivity value information includes a plurality of sensitivity values; each of the experimental factors corresponds to a unique sensitivity value; Using a preset dynamic threshold judgment model and the sensitivity value information to screen the experimental factor information to obtain key factor information; The method of screening the experimental factor information using the preset dynamic threshold judgment model and the sensitivity value information to obtain key factor information includes: performing grouping processing on the experimental factor information to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor; Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value; Performing trajectory expected value calculation processing on the sensitivity group information to obtain sensitivity trajectory expected value information; the sensitivity trajectory expected value information includes a plurality of sensitivity trajectory expected values; each of the factor groups corresponds to a unique sensitivity trajectory expected value; Using a preset dynamic threshold judgment model, the factor group information and the sensitivity group information are calculated and processed to obtain dynamic threshold information; the dynamic threshold information includes a plurality of dynamic thresholds; each factor group corresponds to a unique dynamic threshold; Among them, the specific form of the dynamic threshold judgment model is: Where R is the dynamic threshold; θ i is the sensitivity value corresponding to the i-th key factor, i = 1, 2, ···n; F j is the value corresponding to the jth key factor, j = 1, 2, ···n; is a random variable; n is the number of key factors in the factor group; Using the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information to obtain key factor information; The method of using the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information to obtain key factor information includes: Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information to obtain target trajectory expected value information; the target trajectory expected value information includes a plurality of target trajectory expected values; Using the target trajectory expected value information to match the factor group information to obtain target factor group information; Determine whether the target factor group information meets a search termination condition, and obtain a search judgment result; the search termination condition is related to the number of key factors in the target factor group; When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process of the factor group information and the sensitivity value information is triggered to obtain sensitivity group information; When the search judgment result is yes, key factor information is determined according to the target factor group information.

2. The method for optimizing the experimental scheme for chemical defense and decontamination material consumption according to claim 1 is characterized in that: The performing of scheme design on the key factor information and the factor level information to obtain initial experimental scheme information includes: Constructing a combination experiment design table according to the key factor information and the factor level information; the combination experiment design table includes information of several experimental combination factors; According to the combination experiment design table, initial experimental scheme information is determined; the initial experimental scheme information includes a plurality of initial experimental schemes; the number of the initial experimental schemes is consistent with the number of the experimental combination factor information.

3. The method for optimizing the experimental plan for chemical defense and decontamination material consumption according to claim 2 is characterized in that: The step of constructing a combined experimental design table according to the key factor information and the factor level information includes: Determine the number of rows in the table according to the number of factors in the key factor information; Constructing table information corresponding to each key factor according to a common divisor relationship among the number of table rows, the factor level information, and the number of factors in the key factor information; Based on all the tabular information, a combined experimental design table is determined.

4. The method for optimizing the experimental scheme for chemical defense and decontamination material consumption according to claim 1 is characterized in that: After simulating and deducing the initial experimental scheme information to obtain simulation result information, the method further includes: Performing regression analysis on the simulation result information to obtain confidence information; Determining whether the confidence information meets the confidence level, and obtaining a confidence determination result; When the confidence judgment result is negative, optimizing the key factor information, and triggering the step of processing the key factor information using the experimental equipment information to obtain factor level information; When the confidence judgment result is yes, the chemical defense and decontamination material consumption experimental plan is determined according to the initial experimental plan information.

5. A device for optimizing experimental schemes for chemical defense and decontamination material consumption, characterized in that: The device comprises: Acquisition module, used to obtain experimental factor information and experimental equipment information; A first processing module is used to screen the experimental factor information to obtain key factor information; the key factor information includes a plurality of key factors; A second processing module is configured to process the key factor information using the experimental equipment information to obtain factor level information; the factor level information includes a plurality of level value information; each key factor corresponds to a unique level value information; A design module is used to design a scheme based on the key factor information and the factor level information to obtain initial experimental scheme information; A simulation module is used to simulate and deduce the initial experimental plan information to obtain simulation result information; the simulation result information is used to optimize the initial experimental plan information to obtain a chemical defense and decontamination material consumption experimental plan; The screening of the experimental factor information to obtain key factor information includes: Calculating and processing the experimental factor information to obtain sensitivity value information; the experimental factor information includes a plurality of experimental factors; the sensitivity value information includes a plurality of sensitivity values; each of the experimental factors corresponds to a unique sensitivity value; Using a preset dynamic threshold judgment model and the sensitivity value information to screen the experimental factor information to obtain key factor information; The method of screening the experimental factor information using the preset dynamic threshold judgment model and the sensitivity value information to obtain key factor information includes: performing grouping processing on the experimental factor information to obtain factor group information; the factor group information includes at least one factor group; the factor group includes at least one experimental factor; Matching the factor group information and the sensitivity value information to obtain sensitivity group information; the sensitivity group information includes a plurality of sensitivity groups; the sensitivity group includes at least one sensitivity value; Performing trajectory expected value calculation processing on the sensitivity group information to obtain sensitivity trajectory expected value information; the sensitivity trajectory expected value information includes a plurality of sensitivity trajectory expected values; each of the factor groups corresponds to a unique sensitivity trajectory expected value; Using a preset dynamic threshold judgment model, the factor group information and the sensitivity group information are calculated and processed to obtain dynamic threshold information; the dynamic threshold information includes a plurality of dynamic thresholds; each factor group corresponds to a unique dynamic threshold; Among them, the specific form of the dynamic threshold judgment model is: Where R is the dynamic threshold; θ i is the sensitivity value corresponding to the i-th key factor, i = 1, 2, ···n; F j is the value corresponding to the jth key factor, j = 1, 2, ···n; is a random variable; n is the number of key factors in the factor group; Using the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information to obtain key factor information; The method of using the dynamic threshold information and the sensitivity trajectory expected value information to judge and screen the factor group information to obtain key factor information includes: Using the dynamic threshold information to judge and filter the sensitivity trajectory expected value information to obtain target trajectory expected value information; the target trajectory expected value information includes a plurality of target trajectory expected values; Using the target trajectory expected value information to match the factor group information to obtain target factor group information; Determine whether the target factor group information meets a search termination condition, and obtain a search judgment result; the search termination condition is related to the number of key factors in the target factor group; When the search judgment result is no, the factor group information is updated using the target factor group information, and the matching process of the factor group information and the sensitivity value information is triggered to obtain sensitivity group information; When the search judgment result is yes, key factor information is determined according to the target factor group information.

6. A device for optimizing experimental schemes for chemical defense and decontamination material consumption, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the chemical defense and decontamination material consumption experimental plan optimization method as described in any one of claims 1 to 4.

7. A computer storage medium, characterized in that The computer storage medium stores computer instructions, which, when called, are used to execute the method for optimizing the experimental plan for consumption of chemical defense and decontamination materials as described in any one of claims 1 to 4.

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