Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When opera...Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.展开更多
Journal of Systems Engineering and Electronics (Indexed by Science Citation Index,Engineering Index) With the rapid development of mega-constellations,orbital gaming,on-orbit servicing and the advent of the AI era,spa...Journal of Systems Engineering and Electronics (Indexed by Science Citation Index,Engineering Index) With the rapid development of mega-constellations,orbital gaming,on-orbit servicing and the advent of the AI era,space intelligent sensing and manipulation has become a cutting-edge research hotspot in the space domain,attracting growing attention from scholars worldwide.展开更多
This research conducts a comprehensive experimental study of the entire filling system process at the Weishan Lake Rare Earth Mine(WSLREM)in Shandong Province,encompassing tailings thickening,feeding,slurry preparatio...This research conducts a comprehensive experimental study of the entire filling system process at the Weishan Lake Rare Earth Mine(WSLREM)in Shandong Province,encompassing tailings thickening,feeding,slurry preparation,and pipeline transportation.It proposes a complete and efficient upgrade solution for an intelligent paste filling system.The results show that the F1 flocculant was selected to prepare a flocculant solution with a solution concentration of 0.1%.The unit consumption is set to 25 g·t^(-1),and the flocculation and sedimentation effects are optimal when the mass concentration is 15%,with an underflow concentration of 62%.The selection experiment of cementitious material shows that the effect of using new cementitious material is better than that of traditional 32.5R Portland cement.At the same time,rheological experiments on the filling slurry were carried out,and the filling transportation pressure was studied by combining theoretical calculations with numerical simulations.The research results have guiding significance for the debugging of filling pumps and the selection of a filling pipeline.After the application of industrial transformation,the underflow concentration of the sand silo was 64%–66%,the slurry concentration was 68%–72%,the addition range of the cementing material was 1∶16–1∶4,and the filling capacity was 40–60 m^(3)·h^(-1).The intelligent upgrade and transformation of the filling system have yielded remarkable results,providing significant reference value for the intelligent filling transformation of similar mines.展开更多
The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on sta...The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on static evaluation methods.Therefore,this paper proposes a dynamic multi-round decision evaluation method based on the characteristics of multi-round unmanned aerial vehicle air combat under opponent’s optimal strategy.In order to determine objective weights,an improved multi-attribute decision making method is proposed,which incorporates the proximity as a correction coefficient for evaluation indicators,utilizing the cosine similarity instead of Euclidean distance,and incorporating both actual and theoretical objective weights to prevent data mutations.Subsequently,the game theory is employed to reasonably adjust subjective and objective weights to obtain comprehensive weights.To address the issues related to the ambiguity and randomness during the evaluation process,a reverse cloud generator is utilized to determine the center of gravity of the cloud model using comprehensive weights while employing the weighted deviation degree for evaluating air combat decision-making effectiveness.By activating the cloud generator through the cloud model,the optimal strategies for each round of air combat are determined,thereby completing the dynamic evaluations for multi-round sequential decision-making processes.Finally,the feasibility and effectiveness of the proposed method are verified through simulations.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.展开更多
Deep reinforcement learning algorithms are revolutionizing intelligent decision-making in air combat,drawing widespread attention and extensive research.However,air combat agents trained with these algorithms face sig...Deep reinforcement learning algorithms are revolutionizing intelligent decision-making in air combat,drawing widespread attention and extensive research.However,air combat agents trained with these algorithms face significant challenges,such as limited decision-making capacities due to adversarial training against relatively fixed and singular expert strategies,and a lack of interpretability and reliability in their decisionmaking processes.To tackle these issues,this paper proposes a self-play training mechanism based on policy switching and opponent selection,allowing air combat agents to refine their capabilities via engaging with previous versions of themselves.Additionally,an explainable decision tree model is developed to clarify the decision logic of these agents.Simulations and results demonstrate that the proposed self-play training approach significantly enhances the decision-making abilities of air combat agents,with late-stage agents showing a 38%improvement over early-stage agents in confrontations with an expert strategy.Moreover,the explainable decision tree model effectively elucidates the decision logic and achieves an 86%win rate against the expert strategy,comparable to the 88%win rate of the air combat agents.展开更多
The design of Web-GIS based intelligent management decision-making system for soybean follows the life cycle standard of software engineering. Based on the analysis of the flow of soybean growth technology, the data f...The design of Web-GIS based intelligent management decision-making system for soybean follows the life cycle standard of software engineering. Based on the analysis of the flow of soybean growth technology, the data flow chart was protracted and the function from chart was brought in the course of the designing and realizing the system. By making use of the directed program tool such as VC, Java and multi-media technique the fimctions of decision-making system were realized. It will do a lot of for the theoretical and practical development of intelligent technology of agricultural information of Heilongjiang Province.展开更多
To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development...To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.展开更多
In order to rapidly and effectively meet the informative demand from commanding decision-making, it is important to build, maintain and mine the intelligence database. The type, structure and maintenance of military i...In order to rapidly and effectively meet the informative demand from commanding decision-making, it is important to build, maintain and mine the intelligence database. The type, structure and maintenance of military intelligence database are discussed. On this condition, a new data-mining arithmetic based on relation intelligence database is presented according to the preference information and the requirement of time limit given by the commander. Furthermore, a simple calculative example is presented to prove the arithmetic with better maneuverability. Lastly, the problem of how to process the intelligence data mined from the intelligence database is discussed.展开更多
This article started with an overview of the current technological status and engineering developments in the field of swarm munitions.It first introduced swarm behaviors and related swarm algorithms,and then provided...This article started with an overview of the current technological status and engineering developments in the field of swarm munitions.It first introduced swarm behaviors and related swarm algorithms,and then provided a comprehensive summary of the research progress in the field of swarm munitions from four aspects:Collaborative perception and detection,collaborative positioning and navigation,task allocation for swarms,and path planning for swarms.In summary,future developments in collaborative perception,planning,positioning,navigation,and decision-making for swarm munitions will trend towards intelligence,adaptability,and collaboration.It can enable swarm munitions to be better adapted to complex and dynamic battlefields,improving operational effectiveness and mission capabilities.展开更多
In commanding decision-making, the commander usually needs to know a lot of situations（intelligence） on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence perso...In commanding decision-making, the commander usually needs to know a lot of situations（intelligence） on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence personnel take some deceptive information released by the rival as intelligence data in the process of intelligence gathering. Since the failure of intelligence is likely to lead to a serious aftereffect, the recognition of intelligence is a very important problem. An elementary research on recognizing military intelligence and puts forward a systematic processing method are made. First, the types and characteristics of military intelligence are briefly discussed, a research thought of recognizing military intelligence by means of recognizing military hypotheses are presented. Next, the reasoning mode and framework for recognizing military hypotheses are presented from the angle of psychology of intelligence analysis and non-monotonic reasoning. Then, a model for recognizing military hypothesis is built on the basis of fuzzy judgement information given by intelligence analysts. A calculative example shows that the model has the characteristics of simple calculation and good maneuverability. Last, the methods that selecting the most likely hypothesis from the survival hypotheses via final recognition are discussed.展开更多
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation...To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.展开更多
The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and e...The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.展开更多
According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferen...According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.展开更多
In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuz...In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.展开更多
Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air comba...Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.展开更多
The manner and conditions of running the decision-making system with self-defense electronic jamming are given. After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with se...The manner and conditions of running the decision-making system with self-defense electronic jamming are given. After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming, a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established. Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on. The simulating result shows that this method is able to synthesize different targets which are not predominant. In this way, various features at the same time, as well as the same feature appearing at different time complement mutually; in addition, the accuracy and reliability of electronic jamming decision making are enhanced significantly.展开更多
文摘Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.
文摘Journal of Systems Engineering and Electronics (Indexed by Science Citation Index,Engineering Index) With the rapid development of mega-constellations,orbital gaming,on-orbit servicing and the advent of the AI era,space intelligent sensing and manipulation has become a cutting-edge research hotspot in the space domain,attracting growing attention from scholars worldwide.
基金Supported by the National Natural Science Foundation of China(52004152)Shandong Provincial Natural Science Foundation(ZR2024ME006,ZR2023QE133,ZR2020QE100)+2 种基金Small and Medium-sized Technology Enterprises in Shandong Province(2022TSGC2077)Shandong College Youth Science and Technology Support Program(2023KJ149)National Key Laboratory Open Project Open Fund(2023-JSKSSYS-06)。
文摘This research conducts a comprehensive experimental study of the entire filling system process at the Weishan Lake Rare Earth Mine(WSLREM)in Shandong Province,encompassing tailings thickening,feeding,slurry preparation,and pipeline transportation.It proposes a complete and efficient upgrade solution for an intelligent paste filling system.The results show that the F1 flocculant was selected to prepare a flocculant solution with a solution concentration of 0.1%.The unit consumption is set to 25 g·t^(-1),and the flocculation and sedimentation effects are optimal when the mass concentration is 15%,with an underflow concentration of 62%.The selection experiment of cementitious material shows that the effect of using new cementitious material is better than that of traditional 32.5R Portland cement.At the same time,rheological experiments on the filling slurry were carried out,and the filling transportation pressure was studied by combining theoretical calculations with numerical simulations.The research results have guiding significance for the debugging of filling pumps and the selection of a filling pipeline.After the application of industrial transformation,the underflow concentration of the sand silo was 64%–66%,the slurry concentration was 68%–72%,the addition range of the cementing material was 1∶16–1∶4,and the filling capacity was 40–60 m^(3)·h^(-1).The intelligent upgrade and transformation of the filling system have yielded remarkable results,providing significant reference value for the intelligent filling transformation of similar mines.
基金supported by the Major Projects for Science and Technology Innovation 2030(2018AAA0100805)National Natural Science Foundation of China(62373187).
文摘The evaluation of air combat decision-making has garnered significant attention due to its potential to effectively mitigate losses resulting from erroneous decisions.However,existing research primarily focuses on static evaluation methods.Therefore,this paper proposes a dynamic multi-round decision evaluation method based on the characteristics of multi-round unmanned aerial vehicle air combat under opponent’s optimal strategy.In order to determine objective weights,an improved multi-attribute decision making method is proposed,which incorporates the proximity as a correction coefficient for evaluation indicators,utilizing the cosine similarity instead of Euclidean distance,and incorporating both actual and theoretical objective weights to prevent data mutations.Subsequently,the game theory is employed to reasonably adjust subjective and objective weights to obtain comprehensive weights.To address the issues related to the ambiguity and randomness during the evaluation process,a reverse cloud generator is utilized to determine the center of gravity of the cloud model using comprehensive weights while employing the weighted deviation degree for evaluating air combat decision-making effectiveness.By activating the cloud generator through the cloud model,the optimal strategies for each round of air combat are determined,thereby completing the dynamic evaluations for multi-round sequential decision-making processes.Finally,the feasibility and effectiveness of the proposed method are verified through simulations.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
基金supported by the Joint Funds of the National Natural Science Foundation of China(U2341216).
文摘Deep reinforcement learning algorithms are revolutionizing intelligent decision-making in air combat,drawing widespread attention and extensive research.However,air combat agents trained with these algorithms face significant challenges,such as limited decision-making capacities due to adversarial training against relatively fixed and singular expert strategies,and a lack of interpretability and reliability in their decisionmaking processes.To tackle these issues,this paper proposes a self-play training mechanism based on policy switching and opponent selection,allowing air combat agents to refine their capabilities via engaging with previous versions of themselves.Additionally,an explainable decision tree model is developed to clarify the decision logic of these agents.Simulations and results demonstrate that the proposed self-play training approach significantly enhances the decision-making abilities of air combat agents,with late-stage agents showing a 38%improvement over early-stage agents in confrontations with an expert strategy.Moreover,the explainable decision tree model effectively elucidates the decision logic and achieves an 86%win rate against the expert strategy,comparable to the 88%win rate of the air combat agents.
基金Heilongjiang Province Natural Science Fund Project (F0326)
文摘The design of Web-GIS based intelligent management decision-making system for soybean follows the life cycle standard of software engineering. Based on the analysis of the flow of soybean growth technology, the data flow chart was protracted and the function from chart was brought in the course of the designing and realizing the system. By making use of the directed program tool such as VC, Java and multi-media technique the fimctions of decision-making system were realized. It will do a lot of for the theoretical and practical development of intelligent technology of agricultural information of Heilongjiang Province.
文摘To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.
文摘In order to rapidly and effectively meet the informative demand from commanding decision-making, it is important to build, maintain and mine the intelligence database. The type, structure and maintenance of military intelligence database are discussed. On this condition, a new data-mining arithmetic based on relation intelligence database is presented according to the preference information and the requirement of time limit given by the commander. Furthermore, a simple calculative example is presented to prove the arithmetic with better maneuverability. Lastly, the problem of how to process the intelligence data mined from the intelligence database is discussed.
文摘This article started with an overview of the current technological status and engineering developments in the field of swarm munitions.It first introduced swarm behaviors and related swarm algorithms,and then provided a comprehensive summary of the research progress in the field of swarm munitions from four aspects:Collaborative perception and detection,collaborative positioning and navigation,task allocation for swarms,and path planning for swarms.In summary,future developments in collaborative perception,planning,positioning,navigation,and decision-making for swarm munitions will trend towards intelligence,adaptability,and collaboration.It can enable swarm munitions to be better adapted to complex and dynamic battlefields,improving operational effectiveness and mission capabilities.
文摘In commanding decision-making, the commander usually needs to know a lot of situations（intelligence） on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence personnel take some deceptive information released by the rival as intelligence data in the process of intelligence gathering. Since the failure of intelligence is likely to lead to a serious aftereffect, the recognition of intelligence is a very important problem. An elementary research on recognizing military intelligence and puts forward a systematic processing method are made. First, the types and characteristics of military intelligence are briefly discussed, a research thought of recognizing military intelligence by means of recognizing military hypotheses are presented. Next, the reasoning mode and framework for recognizing military hypotheses are presented from the angle of psychology of intelligence analysis and non-monotonic reasoning. Then, a model for recognizing military hypothesis is built on the basis of fuzzy judgement information given by intelligence analysts. A calculative example shows that the model has the characteristics of simple calculation and good maneuverability. Last, the methods that selecting the most likely hypothesis from the survival hypotheses via final recognition are discussed.
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
基金supported by the Research Innovation Project of Shanghai Education Committee (08YS19)the Excellent Young Teacher Project of Shanghai University
文摘To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.
基金Project(41574123)supported by the National Natural Science Foundation of ChinaProject(2015zzts250)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2013FY110800)supported by the National Basic Research Scientific Program of China
文摘The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.
文摘According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.
文摘In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.
基金supported by Major Projects for Science and Technology Innovation 2030(Grant No.2018AA0100800)Equipment Pre-research Foundation of Laboratory(Grant No.61425040104)in part by Jiangsu Province“333”project under Grant BRA2019051.
文摘Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.
基金the National Natural Science Fundation of China (10377014).
文摘The manner and conditions of running the decision-making system with self-defense electronic jamming are given. After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming, a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established. Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on. The simulating result shows that this method is able to synthesize different targets which are not predominant. In this way, various features at the same time, as well as the same feature appearing at different time complement mutually; in addition, the accuracy and reliability of electronic jamming decision making are enhanced significantly.
