In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clus...The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.展开更多
In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and r...In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.展开更多
Rural territorial function follows the trend to develop from agricultural production space to a complex of cultural heritage,food security,social stability,quality of living,etc.Based on the rural area＇s territorial ...Rural territorial function follows the trend to develop from agricultural production space to a complex of cultural heritage,food security,social stability,quality of living,etc.Based on the rural area＇s territorial function to both urban and rural areas and its evolution law,index system of rural development evaluation,covering rural production function,rural consumption function,regional sustaining function,and individual development function were constructed in this paper.Case study based on Shandong Province and entropy method showed that the rural development in Shandong Province was neither stable nor orderly,and some of rural territorial functions were under fluctuation.The simulation result was close to the actual situation in rural areas of Shandong Province,and therefore,it would provide some experience for scientific evaluation of rural development in other regions.In the end,policy suggestion to cope with rural function transition was provided,namely further promoting the rural economic development,and breaking away from various factors that restricted the value realization,natural increment,and equitable distribution of rural production factors,and therefore,it would receive a sustainable rural development.展开更多
System of systems architecture（SoSA） has received increasing emphasis by scholars since Zachman ignited its flame in 1987. Given its complexity and abstractness, it is critical to validate and evaluate SoSA to ensur...System of systems architecture（SoSA） has received increasing emphasis by scholars since Zachman ignited its flame in 1987. Given its complexity and abstractness, it is critical to validate and evaluate SoSA to ensure requirements have been met.Multiple qualities are discussed in the literature of SoSA evaluation, while research on functionality is scarce. In order to assess SoSA functionality, an extended influence diagram（EID） is developed in this paper. Meanwhile, a simulation method is proposed to elicit the conditional probabilities in EID through designing and executing SoSA. An illustrative anti-missile architecture case is introduced for EID development, architecture design, and simulation.展开更多
To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solve...To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱ could well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
Teaching evaluation on a WebGIS course is a multi-objective nonlinear high-dimensional NP-hard problem. The index system for the teaching evaluation of a WebGIS course, including teacher- and student-oriented sub-syst...Teaching evaluation on a WebGIS course is a multi-objective nonlinear high-dimensional NP-hard problem. The index system for the teaching evaluation of a WebGIS course, including teacher- and student-oriented sub-systems, is first established and used for questionnaires from 2013 to 2017. The multi-objective nonlinear high-dimensional evaluation model is constructed and then solved via dynamic self-adaptive teaching–learning-based optimization (DSATLBO). DSATLBO is based on teaching–learning-based optimization with five improvements: dynamic nonlinear self-adaptive teaching factor, extracurricular tutorship factor, dynamic self-adaptive learning factor, multi-way learning factor, and non-dominated sorting factor. WebGIS teaching performance is fully evaluated based on questionnaires and DSATLBO. Optimal weights and weighted scores from DSATLBO are compared with those from the non-dominated sorting genetic algorithm-II using the Pareto front, coverage to two sets, and spacing of the non-dominated solution sets to validate the performance of DSATLBO. The results show that DSATLBO can be uniformly distributed along the Pareto front. Therefore, DSATLBO can efficiently and feasibly solve the multi-objective nonlinear high-dimensional teaching evaluation model of a WebGIS course. The proposed teaching evaluation method can help reflecting the quality of all aspects of classroom teaching and guide the professional development of students.展开更多
In order to assess the differences between the human body thermal sensation in naturally ventilated space and that in air-conditioned space,the fuzzy evaluation model was adopted in the research of thermal sensation i...In order to assess the differences between the human body thermal sensation in naturally ventilated space and that in air-conditioned space,the fuzzy evaluation model was adopted in the research of thermal sensation in naturally ventilated space.Based on the questionnaires and field measurements,the membership functions were presented by the statistic of the covering frequency to the fuzzy subset.Dry-bulb temperature was taken as the only independent variable for membership functions.The maximum values of membership grades are all at 0.5 or so,which is a distinction character on thermal comfort of naturally ventilated space.By the calculating results of membership grades value to different fuzzy evaluation subsets,the Predicted Mean Vote(PMV)was obtained.Furthermore,energy coefficient(Ea)was introduced to calculate the energy consumption,and the prediction methods of residential building energy consumption were also discussed.Finally,the importance of evaluation model of thermal sense is shown through the energy consumption prediction in a specific residential building.展开更多
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab...To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.展开更多
The reliability of electromechanical product is usually determined by the fault number and working time traditionally. The shortcoming of this method is that the product must be in service. To design and enhance the r...The reliability of electromechanical product is usually determined by the fault number and working time traditionally. The shortcoming of this method is that the product must be in service. To design and enhance the reliability of the electromechanical product, the reliability evaluation method must be feasible and correct. Reliability evaluation method and algorithm were proposed. The reliability of product can be calculated by the reliability of subsystems which can be gained by experiment or historical data. The reliability of the machining center was evaluated by the method and algorithm as one example. The calculation result shows that the solution accuracy of mean time between failures is 97.4% calculated by the method proposed in this article compared by the traditional method. The method and algorithm can be used to evaluate the reliability of electromechanical product before it is in service.展开更多
Aerospace microelectronic technology has become the core competence of aerospace technology. For evaluating the aerospace microelectronic industry, it is necessary to change descriptive language of goal to quantitativ...Aerospace microelectronic technology has become the core competence of aerospace technology. For evaluating the aerospace microelectronic industry, it is necessary to change descriptive language of goal to quantitative index that can be measured. Knowing quantified goals or tree structure and array of general goal system, with certain algorithm and processing each corresponding list or array, we can bring out a quantified general goal value. The multi-objective (multi-attribute) evaluation method and the relevant weight sum algorithm have been adopted to quantitatively evaluate and forecast the developing state of the industry. A practical example illustrates that the applied decision technique and the algorithm are feasible and effective.展开更多
Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby c...Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.展开更多
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
基金supported by the National Natural Science Foundation of China(71671090)the Aeronautical Science Foundation of China(2016ZG52068)+1 种基金the Liberal Arts and Social Sciences Foundation of the Ministry of Education(MOE)in China(15YJCZH189)the Qinglan Project for Excellent Youth or Middle-aged Academic Leaders in Jiangsu Province
文摘The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.
基金Project(51074051)supported by the National Natural Science Foundation of ChinaProject(N110307001)supported by the Fundamental Research Funds for the Central Universities,China
文摘In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.
基金Supported by National Natural Science Foundation of China (40635029,40771014)
文摘Rural territorial function follows the trend to develop from agricultural production space to a complex of cultural heritage,food security,social stability,quality of living,etc.Based on the rural area＇s territorial function to both urban and rural areas and its evolution law,index system of rural development evaluation,covering rural production function,rural consumption function,regional sustaining function,and individual development function were constructed in this paper.Case study based on Shandong Province and entropy method showed that the rural development in Shandong Province was neither stable nor orderly,and some of rural territorial functions were under fluctuation.The simulation result was close to the actual situation in rural areas of Shandong Province,and therefore,it would provide some experience for scientific evaluation of rural development in other regions.In the end,policy suggestion to cope with rural function transition was provided,namely further promoting the rural economic development,and breaking away from various factors that restricted the value realization,natural increment,and equitable distribution of rural production factors,and therefore,it would receive a sustainable rural development.
基金supported by the National Natural Science Foundation of China(71571189)
文摘System of systems architecture（SoSA） has received increasing emphasis by scholars since Zachman ignited its flame in 1987. Given its complexity and abstractness, it is critical to validate and evaluate SoSA to ensure requirements have been met.Multiple qualities are discussed in the literature of SoSA evaluation, while research on functionality is scarce. In order to assess SoSA functionality, an extended influence diagram（EID） is developed in this paper. Meanwhile, a simulation method is proposed to elicit the conditional probabilities in EID through designing and executing SoSA. An illustrative anti-missile architecture case is introduced for EID development, architecture design, and simulation.
基金Supported by the National"Thirteenth Five-year Plan"National Key Program(2016YFD0701301)the Heilongjiang Provincial Achievement Transformation Fund Project(NB08B-011)。
文摘To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱ could well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
基金Project(41661026)supported by the National Natural Science Foundation of ChinaProject supported by the Fund for the Construction of Western-China First-class Specialty of Ningxia University,China
文摘Teaching evaluation on a WebGIS course is a multi-objective nonlinear high-dimensional NP-hard problem. The index system for the teaching evaluation of a WebGIS course, including teacher- and student-oriented sub-systems, is first established and used for questionnaires from 2013 to 2017. The multi-objective nonlinear high-dimensional evaluation model is constructed and then solved via dynamic self-adaptive teaching–learning-based optimization (DSATLBO). DSATLBO is based on teaching–learning-based optimization with five improvements: dynamic nonlinear self-adaptive teaching factor, extracurricular tutorship factor, dynamic self-adaptive learning factor, multi-way learning factor, and non-dominated sorting factor. WebGIS teaching performance is fully evaluated based on questionnaires and DSATLBO. Optimal weights and weighted scores from DSATLBO are compared with those from the non-dominated sorting genetic algorithm-II using the Pareto front, coverage to two sets, and spacing of the non-dominated solution sets to validate the performance of DSATLBO. The results show that DSATLBO can be uniformly distributed along the Pareto front. Therefore, DSATLBO can efficiently and feasibly solve the multi-objective nonlinear high-dimensional teaching evaluation model of a WebGIS course. The proposed teaching evaluation method can help reflecting the quality of all aspects of classroom teaching and guide the professional development of students.
基金Supported by National Natural Science Foundation of China(50508035)the National Science Foundation for Post-doctoral Scientists of China(20070411121)
文摘In order to assess the differences between the human body thermal sensation in naturally ventilated space and that in air-conditioned space,the fuzzy evaluation model was adopted in the research of thermal sensation in naturally ventilated space.Based on the questionnaires and field measurements,the membership functions were presented by the statistic of the covering frequency to the fuzzy subset.Dry-bulb temperature was taken as the only independent variable for membership functions.The maximum values of membership grades are all at 0.5 or so,which is a distinction character on thermal comfort of naturally ventilated space.By the calculating results of membership grades value to different fuzzy evaluation subsets,the Predicted Mean Vote(PMV)was obtained.Furthermore,energy coefficient(Ea)was introduced to calculate the energy consumption,and the prediction methods of residential building energy consumption were also discussed.Finally,the importance of evaluation model of thermal sense is shown through the energy consumption prediction in a specific residential building.
文摘To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.
基金Project(2013ZX04013047)supported by the Major Program of National Natural Science Foundation of ChinaProject(51275014)supported by the National Natural Science Foundation of China
文摘The reliability of electromechanical product is usually determined by the fault number and working time traditionally. The shortcoming of this method is that the product must be in service. To design and enhance the reliability of the electromechanical product, the reliability evaluation method must be feasible and correct. Reliability evaluation method and algorithm were proposed. The reliability of product can be calculated by the reliability of subsystems which can be gained by experiment or historical data. The reliability of the machining center was evaluated by the method and algorithm as one example. The calculation result shows that the solution accuracy of mean time between failures is 97.4% calculated by the method proposed in this article compared by the traditional method. The method and algorithm can be used to evaluate the reliability of electromechanical product before it is in service.
文摘Aerospace microelectronic technology has become the core competence of aerospace technology. For evaluating the aerospace microelectronic industry, it is necessary to change descriptive language of goal to quantitative index that can be measured. Knowing quantified goals or tree structure and array of general goal system, with certain algorithm and processing each corresponding list or array, we can bring out a quantified general goal value. The multi-objective (multi-attribute) evaluation method and the relevant weight sum algorithm have been adopted to quantitatively evaluate and forecast the developing state of the industry. A practical example illustrates that the applied decision technique and the algorithm are feasible and effective.
基金sponsored by the National Defense Science and Technology Key Laboratory Fund(Grant No.61422062205)the Equipment Pre-Research Fund(Grant No.JCKYS2022LD9)。
文摘Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.
