Military target selection method based on multi-factor dynamic balance

Abstract

The invention relates to a military target selection method based on multi-factor dynamic balance, and the method comprises the following steps: S1, quantifying the importance of a military target, and achieving the military target selection based on multi-factor dynamic balance; s2, determining an initial importance degree of a target, and introducing a combat resource constraint coefficient, and S3, introducing a battlefield situation influence factor, and updating the importance degree of the target after the timeliness is considered; s4, the comprehensive priority of the military targets is calculated in combination with the adjusted target importance, and combat actions are executed; and S5, after target selection is completed, further combining with a related combat background, determining a target capability index, calculating a target capability vector and a matrix before and after strike, and evaluating military target strike efficiency. The target priority is adjusted in real time through the dynamic mathematical model, more scientific and accurate selection of military targets is achieved, and the military resource utilization efficiency and combat effectiveness are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of geographic information system technology and military targets, and particularly to a method for selecting military targets based on multi-factor dynamic weighing. Background Art

[0002] In modern warfare, the situation changes rapidly, and the selection of military targets has become a core factor determining the outcome of battles. In a complex battlefield environment, there are many factors such as geographical constraints, enemy defense strategies, and the limited resources of our side. How to accurately and efficiently determine the strike targets and achieve the optimal allocation of military resources has become a difficult problem that urgently needs to be solved in the military field. Among them, the importance of military targets plays a crucial role in determining the selection of military strike targets, is the premise for formulating scientific and effective military strike plans, and has an irreplaceable role in ensuring the success of combat operations. However, in actual combat scenarios, relying solely on importance ranking to select targets has obvious limitations. In the case of limited resources, it may lead to insufficient subsequent combat resources because priority is given to selecting targets with high importance but huge attack costs; the battlefield situation changes dynamically, and targets that were originally highly important may no longer be the optimal choice due to enemy defense adjustments or changes in our combat plans; at the same time, targets also have timeliness, and the value of some key targets will be greatly reduced if they cannot be struck within a specific time.

[0003] Based on this, it is extremely urgent to deeply study the method for selecting military targets. This requires not only fully considering the importance of the targets themselves, but also comprehensively weighing multiple factors dynamically, such as the real-time status of resources, the real-time changes in the battlefield situation, and the timeliness of the targets. On the basis of knowing the importance of military targets, an attempt should be made to explore a more comprehensive and scientific target selection method in order to effectively improve combat effectiveness and provide strong support for military decision-making. Summary of the Invention

[0004] Based on the previous evaluation of target importance, the present invention incorporates factors such as combat resource constraints, dynamic changes in the battlefield situation, and target timeliness, and determines the optimal target selection sequence through a dynamic mathematical model. Its principle is that military operations are a complex dynamic system. A single target importance is not sufficient to comprehensively guide target selection. Various factors that change in real time must be comprehensively considered to achieve the efficient use of military resources and the maximization of combat benefits. By scientifically evaluating and dynamically adjusting target selection, it is ensured that commanders can maximize the results with limited resources, and at the same time seize the opportunity to achieve the success of combat operations.

[0005] The present invention provides a method for selecting military targets based on multi-factor dynamic weighing, including the following steps:

[0006] Step S1: Quantify the importance of military targets. Considering factors such as combat resource constraints, dynamic changes in the battlefield situation, and target timeliness, determine the optimal target selection sequence through a dynamic mathematical model to achieve military target selection based on multi-factor dynamic trade-offs.

[0007] Step S2: Determine the initial importance of targets. Introduce the combat resource constraint coefficient and screen out the targets within the range that can be afforded by resources.

[0008] Step S3: Introduce the battlefield situation impact factor, calculate the dynamic adjustment coefficient of the battlefield situation, and update the target importance affected by the battlefield situation; introduce the target timeliness factor and update the target importance considering timeliness.

[0009] Step S4: Combine the adjusted target importance, calculate the comprehensive priority of military targets, sort all targets according to the magnitude of the priority, and take the target with the highest priority as the strike target to execute combat operations.

[0010] Step S5: After completing target selection, further combine the relevant combat background, determine the target capability indicators, calculate the target capability vectors and matrices before and after the strike, and evaluate the military target strike effectiveness.

[0011] The said Step S2 includes the following steps:

[0012] Step S21: Initialize and define parameters. Set the target importance as I i , with the value range of [1, 10]. The larger the value, the more important the target. Determine the total amount of our combat resources R and the amount of resources required for each target r i , set the initial time j = 0, and initialize the battlefield situation impact factor S ij and the target timeliness factor T ij .

[0013] Step S22: To ensure reasonable resource allocation, introduce the resource constraint coefficient λ, and its calculation formula is as follows:

[0014]

[0015] In the formula, R is the total amount of combat resources we possess, including ammunition, troops, equipment, etc.; the amount of resources required to attack target i is r i ; n is the total number of targets. Only when λr i < R, target i can be considered for selection within the range that can be afforded by resources. For example, if our total ammunition amount R = 1000 units and the ammunition required to attack target B is r B = 200 units, if the calculated λ = 0.8, then λr B ≤ 1000, and target B can be considered under resource constraints.

[0016] Furthermore, in actual combat, due to the complex and ever-changing battlefield situation, it continuously affects the selection of military targets. The battlefield situation is a complex multi-dimensional variable, including changes in the enemy's defense intensity, losses of our combat forces, etc. Therefore, it is necessary to continuously adjust the importance of the target affected by the battlefield situation. In addition, the actual value of the target changes over time and has a certain timeliness, and it is necessary to adjust its importance in combination with the timeliness situation. Finally, the importance of the target is updated with the two dynamic factors of the battlefield situation and time.

[0017] Therefore, step S3 includes the following steps:

[0018] Step S31: Considering the influence of the battlefield situation on the importance of the target, introduce the battlefield situation dynamic adjustment coefficient. The formula for the adjusted value of the target importance affected by the battlefield situation is:

[0019] ΔI ij =a j S ij I i

[0020] In the formula, S ij represents the battlefield situation influence factor faced by target i at time j, and its value range is [-1, 1]. A positive value indicates a favorable situation, and a negative value indicates an unfavorable situation. For example, if the enemy strengthens the air defense firepower near target C, making it more difficult for us to attack, at this time S cj = -0.3; a j represents the battlefield situation adjustment coefficient, which is a function of time j and reflects the degree of influence of the changing battlefield situation on target selection. It can be dynamically determined through machine learning algorithms based on historical data and real-time monitoring data.

[0021] Step S32: Considering the influence of time on the value of the target, introduce the target timeliness factor. The formula for the adjusted value of the target importance affected by timeliness is:

[0022]

[0023] In the formula, T ij represents the timeliness of target i at time j, and its value range is [0, 1]. For example, for the key equipment that the enemy is transferring, as time goes by, the possibility of its successful transfer increases, and the timeliness T ij gradually decreases.

[0024] Furthermore, comprehensively consider the importance of the target affected by the battlefield situation and timeliness, calculate the comprehensive priority of the target, and iterate this process.

[0025] Therefore, step S4 includes the following steps:

[0026] Step S41: Calculate the comprehensive priority P of the target by comprehensively considering the importance of the target after taking into account the battlefield situation and timeliness impact. ij The calculation formula is as follows:

[0027]

[0028] Step S42: Sort all the targets according to the magnitude of the comprehensive priority P ij and preferentially select the target with the largest P ij value as the current target for attack and execute the combat operation;

[0029] Step S43: Update the combat resources R, enter the next moment j = j + 1, and repeat the above steps until the combat mission is completed or there are no suitable targets to select.

[0030] Furthermore, after completing the target selection and executing the strike operation, it is necessary to accurately estimate the strike effect to provide strong support for subsequent combat decisions.

[0031] Therefore, the said step S5 includes the following steps:

[0032] Step S51: Determine the target capability indicators according to the relevant combat background, and focus on the capabilities that have a key impact on the combat process and outcome, including early warning and reconnaissance capabilities, strike and damage capabilities, information communication capabilities, and command and control capabilities;

[0033] Step S52: For the constructed target capability system, quantitatively assign each capability indicator of each selected target to obtain the capability vector V = [m1, m2,..., m n , and finally obtain the capability matrix M of all selected targets through calculation:

[0034]

[0035] In the formula, p is the number of selected targets, and n is the number of capability indicators.

[0036] Step S53: Combine the weapon type, strike method used in the combat, and the protection situation of the target to estimate the degree of decline of each target's capabilities. The calculation method of the target capability indicator value after the strike is:

[0037] m′ ki = m ki × (1 - a ki )

[0038] In the formula, m′ ki is the value of the i-th capability indicator of the k-th target after the strike; m ki is the value of the i-th capability indicator of the k-th target before the strike; a kiIt is the estimated decrease coefficient of the i-th capability index of the k-th target, with a value range of [0, 1]. It can be determined based on historical combat data, weapon effectiveness analysis, and expert experience. In simple cases, the value is 1.

[0039] Step S54: According to the calculated capability index values of each target after the strike, reconstruct the target capability vector V′ = [m1′, m2′, …, m n ′] and the capability matrix m′ after the strike;

[0040]

[0041] Step S55: To comprehensively evaluate the strike effect, introduce a strike effect evaluation index. The calculation formula is:

[0042]

[0043] Among them, the numerator represents the total sum of the differences in all capability indices of all selected targets before and after the strike, and the denominator represents the total sum of all capability indices of all selected targets before the strike. The larger the strike effect evaluation index E, the better the strike effect.

[0044] At the same time, the strike effect sub-index E of each target can also be calculated separately k :

[0045]

[0046] By analyzing E k , the strike effect of each target can be understood, providing a reference for whether to strike a specific target again in the future.

[0047] An electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the military target selection method based on multi-factor dynamic trade-off described above.

[0048] A computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, they implement the military target selection method based on multi-factor dynamic trade-off described above.

[0049] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows:

[0050] 1. Comprehensive consideration of multiple factors: Breaking through the limitations of traditional single importance evaluation, innovatively integrating multiple factors such as combat resource constraints, dynamic changes in the battlefield situation, and target timeliness, making military target selection more comprehensive and scientific, and meeting the actual needs of the modern complex battlefield environment.

[0051] 2. Dynamic real-time adjustment: By using a dynamic mathematical model to adjust the target priorities in real time, it can respond promptly to changes in the battlefield situation and the timeliness of targets, ensuring optimal target selection decisions can be made under different circumstances.

[0052] 3. Improve resource utilization efficiency: Introduce the combat resource constraint coefficient to screen out targets within the scope that resources can bear, avoiding the situation of insufficient subsequent combat resources caused by preferentially selecting targets with high importance but huge attack costs, and effectively improving the utilization efficiency of military resources.

[0053] 4. Enhance combat effectiveness: Based on a scientific target selection method, it can more accurately determine the strike targets, seize the opportunity to fight, and achieve the success of combat operations, thus effectively enhancing the overall combat effectiveness.

[0054] 5. Provide a scientific basis: After completing target selection and strikes, by determining the target capability indicators, calculating the target capability vectors and matrices before and after strikes, and evaluating the combat effectiveness of military targets, it provides a scientific basis for combat commanders to adjust combat plans, optimize resource allocation, and determine whether it is necessary to strike specific targets again.

[0055] 6. The algorithm process is clear and easy to understand: In the embodiments, based on a specific number of targets, the entire process from parameter setting, coefficient calculation to target priority determination and strike effectiveness evaluation is fully presented, making the algorithm execution process clearer and easier to understand, facilitating understanding and application.

[0056] 7. Adapt to battlefield complexity: Fully considering the complex and ever-changing battlefield situation, such as changes in the enemy's defense intensity and the depletion of our combat power, by introducing battlefield situation impact factors and corresponding adjustment coefficients, continuously adjust the importance of targets affected by the battlefield situation, making target selection more adaptable to the actual battlefield situation.

[0057] 8. Consider target timeliness: Pay attention to the change of target value over time, introduce the target timeliness factor to adjust the target importance, reflecting the impact of the dynamic change of target value on combat decisions, and avoiding missing the strike opportunity for key targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is the overall algorithm flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0059] The embodiments of the technical solution of the present invention will be described in detail below in conjunction with the attached tables. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, so they are only used as examples and cannot be used to limit the protection scope of the present invention. It should be noted that unless otherwise specified, the technical terms or scientific terms used in this application should be the ordinary meanings understood by those skilled in the art to which the present invention belongs. The present invention will be further described in detail below in conjunction with the attached tables and specific embodiments.

[0060] Embodiment: Refer to Figure 1 , a military target selection method based on multi-factor dynamic trade-off, comprising the following steps:

[0061] Step S1: Quantify the importance of military targets, and combine factors such as combat resource constraints, dynamic changes in the battlefield situation, and target timeliness. Through a dynamic mathematical model, determine the optimal target selection sequence to achieve military target selection based on multi-factor dynamic trade-off;

[0062] Step S2: Determine the initial importance of the target, introduce a combat resource constraint coefficient, and screen out the targets within the range that can be tolerated by the resources;

[0063] Step S3: Introduce a battlefield situation influence factor, calculate the dynamic adjustment coefficient of the battlefield situation, and update the importance of the target affected by the battlefield situation; introduce a target timeliness factor, and update the importance of the target considering timeliness;

[0064] Step S4: Combine the adjusted target importance, calculate the comprehensive priority of military targets, sort all targets according to the size of the priority, and use the target with the largest priority as the strike target to execute combat operations;

[0065] Step S5: After completing the target selection, further combine the relevant combat background, determine the target ability index, calculate the target ability vector and matrix before and after the strike, and evaluate the military target strike effectiveness. The algorithm flow is as follows Figure 1 shown.

[0066] In this embodiment, based on 10 targets, the full process from parameter setting, coefficient calculation to target priority determination is presented completely, making the algorithm execution process clearer and easier to understand.

[0067] Step 1: Determine the initial importance of the target, introduce a combat resource constraint coefficient, and screen out the targets within the range that can be tolerated by the resources;

[0068] Step (1): Parameter initialization definition, select 10 military targets, and the known initial target importance is I i , and at the same time set the total amount of our combat resources R to 300, and the resource amount required for each target attack is r i , and the detailed information is shown in Table 1.

[0069] Table 1 Information Table of 10 Military Targets

[0070] Target number Target importance Resources required for attack 1 8 40 2 6 30 3 7 35 4 5 25 5 9 50 6 4 20 7 7 32 8 6 28 9 8 45 10 5 22

[0071] Step (2): First, calculate the total resources required for all targets:

[0072]

[0073] Secondly, calculate the resource constraint coefficient of this embodiment of the present invention according to the resource constraint coefficient λ. The calculation formula is as follows:

[0074]

[0075] The calculated λ≈0.92. According to λr i <R, it can be judged that all targets can be considered under resource constraints.

[0076] Step 2: Introduce the battlefield situation influence factor, calculate the battlefield situation dynamic adjustment coefficient, and update the target importance after being affected by the battlefield situation; introduce the target timeliness factor and update the target importance after considering timeliness;

[0077] Step (1): Assume that the current time j = 1, and obtain the battlefield situation influence factor S of each target through battlefield monitoring and analysis ij and the target timeliness factor T ij , and the specific values are shown in Table 2:

[0078] Table 2 Battlefield Situation Influence and Target Timeliness Factor

[0079] Target number Battlefield situation impact factor Target timeliness factor 1 -0.15 0.8 2 0.1 0.75 3 -0.08 0.85 4 0.12 0.7 5 -0.2 0.9 6 0.05 0.8 7 -0.1 0.88 8 0.06 0.78 9 -0.25 0.92 10 0.1 0.72

[0080] Step (2): Considering the influence of the battlefield situation on the target importance, the formula for the adjusted value of the target importance after being affected by the battlefield situation is:

[0081] ΔI ij =a j S ij I i

[0082] In the formula, S ij represents the battlefield situation influence factor faced by target i at time j, and its value range is [-1, 1]. A positive value indicates a favorable situation, and a negative value indicates an unfavorable situation; a j represents the battlefield situation adjustment coefficient, which is a function of time j, reflecting the influence degree of the change of the battlefield situation over time on target selection, and can be dynamically determined through machine learning algorithms based on historical data and real-time monitoring data. The present invention determines the battlefield situation dynamic adjustment coefficient a through machine learning algorithms jis 0.5, and the adjusted value of the target importance affected by the battlefield situation is calculated according to the above formula.

[0083] Step (3): Consider the impact of time on the target value. The formula for the adjusted value of the target importance affected by timeliness is:

[0084]

[0085] In the formula, T ij represents the timeliness of target i at time j, and its value range is [0, 1]. For example, for the key equipment that the enemy is transferring, as time goes by, the possibility of its successful transfer increases, and the timeliness T ij gradually decreases. The adjusted value of the target importance affected by timeliness is calculated according to the above formula.

[0086] Step (4): The results of the adjusted value of the target importance affected by the battlefield situation and timeliness are calculated according to the formula, as shown in Table 3.

[0087] Table 3 Target Importance Adjustment Table

[0088] Target number Adjustment value of battlefield situation impact importance Adjustment value of timeliness impact importance 1 -0.6 1.6 2 0.3 1.5 3 -0.28 1.05 4 0.3 1.5 5 -0.9 0.9 6 0.1 0.8 7 -0.35 0.84 8 0.18 1.32 9 -1 0.64 10 0.25 1.4

[0089] The results show that the battlefield situation influence factor has a significant dynamic adjustment effect on the target priority. Taking Target 1 as an example, the battlefield situation influence factor S 1j = -0.15, which reduces the adjusted value of the importance and lowers its priority. While for Target 2, S 2j = 0.1, bringing a positive adjusted value of the importance and enhancing its priority in the current situation. This shows that accurately grasping the changes in the battlefield situation in a timely manner is crucial for reasonably adjusting the target attack order; in addition, the target timeliness cannot be ignored either. For example, for Target 5, although the battlefield situation has a negative adjustment on its importance, due to the relatively high timeliness factor, part of the negative impact is offset, maintaining a relatively high priority. This reflects the impact of the dynamic change of the target value over time on the combat decision-making.

[0090] Step Three: Combine the adjusted target importance, calculate the comprehensive priority of military targets, sort all targets according to the size of the priority, and take the target with the highest priority as the strike target to execute combat operations.

[0091] Step (1): Considering the target importance affected by both the battlefield situation and timeliness, calculate the comprehensive priority of the target. The formula for the comprehensive priority P ij is as follows:

[0092]

[0093] Calculated according to the above formula, the target comprehensive priority results of the embodiments of the present invention are shown in Table 4 as follows:

[0094] Table 4 Target Priority Results

[0095] Target number Target priority Pij 1 9 2 7.8 3 7.77 4 6.8 5 9 6 4.9 7 7.49 8 7.5 9 7.64 10 6.65

[0096] Step (2): Sort all the targets according to the size of the comprehensive priority P ij The result shows that P 1j =P 5j =9 is the largest. Therefore, it is preferred to select Target 1 and Target 5 as the current targets to be struck first, and then strike them in order according to the sorting, and execute the combat operation;

[0097] Step (3): Update the combat resources R, enter the next moment j = j + 1, and repeat the above steps until the combat mission is completed or there are no suitable targets to select.

[0098] Step Four: After completing the target selection, further combine the relevant combat background, determine the target ability indicators, calculate the target ability vectors and matrices before and after the strike, and evaluate the combat effectiveness of the military target.

[0099] Step (1): Determine the target ability indicators according to the relevant combat background, and focus on the abilities that have a key impact on the combat process and outcome, including early warning and reconnaissance capabilities, strike and damage capabilities, information communication capabilities, and command and control capabilities. Among them, the early warning and reconnaissance capabilities include the detection range of the sea and air, the number of tracked targets, etc. If the enemy's early warning and reconnaissance capabilities are effectively weakened, the sea crossing and air assault operations of our side will be more concealed and sudden; the strike and damage capabilities include air defense and anti-missile, land strike, anti-ship capabilities, etc. Reducing the enemy's strike and damage capabilities can reduce the fire threat suffered by our side; the information communication capabilities cover the types of communication equipment, the number of support units, etc. Destroying the enemy's information communication capabilities can interfere with its command and coordination and make its combat system fall into chaos; the command and control capabilities are composed of the level of the command agency, the force command and control capabilities, etc. Striking the enemy's command and control nodes can disrupt its combat deployment and reduce its combat effectiveness;

[0100] Step (2): Quantify and assign each target ability system of the 10 targets to obtain the ability matrix M of the targets, as follows:

[0101]

[0102] Step (3): According to historical combat data, weapon effectiveness analysis, and expert experience, determine the estimated decrease coefficient a ki of each target ability indicator, and the specific value results are as follows:

[0103]

[0104] Step (4): Evaluate the strike effect according to the strike effect evaluation index calculation formula. The calculation formula is as follows:

[0105]

[0106] The calculated overall strike effect E = 0.365.

[0107] In addition, calculate the strike effect sub-index E of each target according to the following formula k :

[0108]

[0109] The strike effects of each target are shown in Table 5.

[0110] Table 5 Strike Effect Evaluation of Each Target

[0111]

[0112]

[0113] By analyzing E k , the strike effect of each target can be understood. The results show that the strike effect sub-indices of Targets 1, 5, and 9 are relatively high, while the strike effect sub-index of Target 6 is relatively low. It may be necessary to consider striking Target 6 again to better achieve the combat goal.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A military target selection method based on dynamic weighing of multiple factors, characterized in that: The following steps are involved: Step S1: Quantify the importance of military targets, combine combat resource constraints, dynamic changes in battlefield situation and target timeliness factors, determine the optimal target selection sequence through a dynamic mathematical model, and realize military target selection based on dynamic trade-offs of multiple factors; Step S2: Determine the initial importance of the target, introduce the combat resource constraint coefficient, and screen out the targets within the resource tolerance range; Step S3: introducing battlefield situation influencing factors, calculating battlefield situation dynamic adjustment coefficients, and updating target importance after being affected by battlefield situation; introducing target timeliness factors, and updating target importance after considering timeliness; Step S4: Calculate the comprehensive priority of the military target based on the adjusted target importance, sort all targets according to the priority, take the target with the highest priority as the strike target, and execute the combat operation; Step S5: After completing the target selection, further combine the relevant combat background to determine the target capability indicators, calculate the target capability vector and matrix before and after the strike, and evaluate the military target strike effectiveness.

2. A military target selection method based on multi-factor dynamic weighing according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: Parameter initialization definition, set the target importance to 1 i , the value range is [1,10]. The larger the value, the more important the target is. Determine the total amount of our combat resources R and the amount of resources required for each target r i , set the initial time j = 0, initialize the battlefield situation influence factor S ij and target timeliness factor T ij ; Step S22: To ensure reasonable allocation of resources, a resource constraint coefficient λ is introduced, and its calculation formula is as follows: Wherein, R is the total amount of combat resources owned by us, including ammunition, troops, and equipment; the amount of resources required to attack target i is r i ; n is the total number of targets. Only when λr i < R, target i will be considered for selection within the scope of resources that can be tolerated.

3. A military target selection method based on multi-factor dynamic weighing according to claim 1, characterized in that: The step S3 comprises the following steps: Step S31: Considering the impact of battlefield situation on target importance, a battlefield situation dynamic adjustment coefficient is introduced. The target importance adjustment value formula after being affected by the battlefield situation is: ΔI ij =a j S ij I i In the formula, S ij It represents the battlefield situation influencing factor faced by target i at time j, and its value range is [-1,1]. Positive values ​​indicate favorable situation, and negative values ​​indicate unfavorable situation. At this time, S cj =-0.3; a j It represents the battlefield situation adjustment coefficient, which is a function of time j. It reflects the influence of battlefield situation changes over time on target selection. It is dynamically determined by machine learning algorithm based on historical data and real-time monitoring data. Step S32: Considering the influence of time on the target value, the target timeliness factor is introduced. The formula for adjusting the target importance after being affected by timeliness is: Where, T ij Indicates the timeliness of target i at time j, and its value range is [0,1].

4. A military target selection method based on multi-factor dynamic weighing according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: Calculate the target's overall priority by comprehensively considering the battlefield situation and timeliness. ij The calculation formula is: Step S42: According to the comprehensive priority P ij Sort all targets by their size, giving priority to P ij The target with the largest value is taken as the current target to be attacked and the combat operation is carried out; Step S43: Update the combat resources R, enter the next moment j=j+1, and repeat the above steps until the combat mission is completed or there is no suitable target to choose.

5. The method for selecting a military target based on dynamic weighing of multiple factors according to claim 1 is characterized in that: Step S5 includes the following steps: Step S51: Determine target capability indicators based on relevant operational contexts, focusing on capabilities that have a key impact on the operational process and outcome, including early warning and reconnaissance capabilities, strike and damage capabilities, information and communication capabilities, and command and control capabilities; Step S52: For the constructed target capability system, quantify and assign values ​​to the capability indicators of each selected target to obtain the capability vector V = [m1, m2, ..., m n ], and finally obtain the capability matrix M of all selected targets by calculation: In the formula, p is the number of selected targets, n is the number of capability indicators, Step S53: Based on the weapon type, attack method and protection status of the target used in the operation, the degree of decline of each target's capabilities is estimated. The target capability index value after the attack is calculated as follows: m′ ki =m ki ×(1-a ki ) In the formula, m′ ki is the i-th capability index value of the k-th target after the attack; m ki is the i-th capability index value of the k-th target before attacking; a ki is the estimated reduction coefficient of the i-th capability indicator of the k-th target, with a value range of [0,1], which can be determined based on historical combat data, weapon effectiveness analysis and expert experience. In simple cases, the value is 1. Step S54: Reconstruct the target capability vector V′=[m1′,m2′,…,m n ′] and capability matrix m′; Step S55: In order to comprehensively evaluate the strike effect, a strike effect evaluation index is introduced, and the calculation formula is: The numerator represents the sum of the differences of all capability indicators of all selected targets before and after the attack, and the denominator represents the sum of all capability indicators of all selected targets before the attack. The larger the attack effect evaluation index E is, the better the attack effect is. At the same time, the strike effect index E of each target can be calculated separately k : In the formula, m′ ki is the i-th capability index value of the k-th target after the attack; m ki is the i-th capability index value before attacking the k-th target; by analyzing E k , understand the strike effect of each target and provide a reference for whether it is necessary to strike the specific target again in the future.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the military target selection method based on dynamic weighing of multiple factors as described in any one of claims 1 to 5 above is implemented.

7. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, a military target selection method based on dynamic weighing of multiple factors as described in any one of claims 1 to 5 is implemented.

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