Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal c...Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.展开更多
Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinfor...Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.展开更多
针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进IN...针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。展开更多
An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measur...An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.展开更多
A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the chara...A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.展开更多
Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of ...Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.展开更多
Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of O...Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type.展开更多
Most of the public key algorithms used in the exchange of information for power data transmission protocols are RSA. The core of the key part of this kind of algorithm system has not been announced. For the domestic s...Most of the public key algorithms used in the exchange of information for power data transmission protocols are RSA. The core of the key part of this kind of algorithm system has not been announced. For the domestic sensitive information data field, there are threats such as preset backdoors and security vulnerabilities. In response to the above problems, the article introduces a secure communication protocol based on the optimized Secret SM2 algorithm, which uses socket programming to achieve two-way encrypted communication between clients and services, and is able to complete the security protection of data encryption transmission, authentication, data tampering, etc., and proves through experiments that the security protocol is more secure than traditional methods, can effectively identify each other, carry out stable and controllable data encryption transmission, and has good applicability.展开更多
This paper presents an analysis of the KM (Karnik-Mendel) algorithms performance under real time implementation using 3 types: the non-iterative, the iterative and the enhanced, and their feasibility for real-time ...This paper presents an analysis of the KM (Karnik-Mendel) algorithms performance under real time implementation using 3 types: the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT (Nie-Tan) method that is one of the fastest and simplest defuzzification methods. Because the DC (direct current) servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA (field programmable gate array) module hardware which is one of the most used platforms in the industry. The results show that the E-KM (enhanced KM) algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.展开更多
We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 p...We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 patients, 21 patients in the newly-initiated group and 25 patients in the existing BOT group performed dose adjustment using 3-3-1 algorithm. HbA1c was significantly improved 4 weeks after the initiation from 8.5% ± 1.2% at baseline to 7.3% ± 0.7% at the final evaluation (p 0.01, vs. Baseline). The average daily insulin units increased throughout the study period from 10.1 ± 6.7 at baseline to 14.6 ± 8.9 units at the final evaluation. Weight didn’t significantly change throughout the study (p = 0.12). The incidents of hypoglycemia were 0.8/month during the insulin dose self-adjustment period and 0.4/month during the follow-up period. The 3-3-1 algorithm using insulin glargine provided a safe and simple dose adjustment and demonstrated its utility in patients who were newly introduced to insulin treatment as well as who were already on BOT.展开更多
Considering wireless sensor network characteristics,this paper uses network simulator,version2(NS-2)algorithm to improve Ad hoc on-demand distance vector(AODV)routing algorithm,so that it can be applied to wireless se...Considering wireless sensor network characteristics,this paper uses network simulator,version2(NS-2)algorithm to improve Ad hoc on-demand distance vector(AODV)routing algorithm,so that it can be applied to wireless sensor networks.After studying AODV routing protocol,a new algorithm called Must is brought up.This paper introduces the background and algorithm theory of Must,and discusses the details about how to implement Must algorithm.At last,using network simulator(NS-2),the performance of Must is evaluated and compared with that of AODV.Simulation results show that the network using Must algorithm has perfect performance.展开更多
This paper describes a routing algorithm for risk scanning agents using ant colony algorithm in P2P(peerto peer) network. Every peer in the P2P network is capable of updating its routing table in a real-time way, wh...This paper describes a routing algorithm for risk scanning agents using ant colony algorithm in P2P(peerto peer) network. Every peer in the P2P network is capable of updating its routing table in a real-time way, which enables agents to dynamically and automatically select, according to current traffic condition of the network, the global optimal traversal path. An adjusting mechanism is given to adjust the routing table when peers join or leave. By means of exchanging pheromone intensity of part of paths, the algorithm provides agents with more choices as to which one to move and avoids prematurely reaching local optimal path. And parameters of the algorithm are determined by lots of simulation testing. And we also compare with other routing algorithms in unstructured P2P network in the end.展开更多
We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar...We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar to that of a Heisenberg chain.All the solutions of the given Q2SAT problem span the subspace of the degenerate ground states.The Hamiltonian is adiabatically evolved so that the system stays in the degenerate subspace.Our numerical results suggest that the time complexity of our algorithm is O(n^(3.9))for yielding non-trivial solutions for problems with the number of clauses m=dn(n-1)/2(d■0.1).We discuss the advantages of our algorithm over the known quantum and classical algorithms.展开更多
Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one...Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.展开更多
基金funded by the National Natural Science Foundation of China,grant number 42074176,U1939204。
文摘Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.
基金This research was funded by the Project of the National Natural Science Foundation of China,Grant Number 62106283.
文摘Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.
文摘针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。
文摘An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.
基金This project was supported by Science and Technology Research Emphasis Fund of Ministry of Education(204010) .
文摘A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.
文摘Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.
文摘Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type.
文摘Most of the public key algorithms used in the exchange of information for power data transmission protocols are RSA. The core of the key part of this kind of algorithm system has not been announced. For the domestic sensitive information data field, there are threats such as preset backdoors and security vulnerabilities. In response to the above problems, the article introduces a secure communication protocol based on the optimized Secret SM2 algorithm, which uses socket programming to achieve two-way encrypted communication between clients and services, and is able to complete the security protection of data encryption transmission, authentication, data tampering, etc., and proves through experiments that the security protocol is more secure than traditional methods, can effectively identify each other, carry out stable and controllable data encryption transmission, and has good applicability.
文摘This paper presents an analysis of the KM (Karnik-Mendel) algorithms performance under real time implementation using 3 types: the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT (Nie-Tan) method that is one of the fastest and simplest defuzzification methods. Because the DC (direct current) servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA (field programmable gate array) module hardware which is one of the most used platforms in the industry. The results show that the E-KM (enhanced KM) algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.
文摘We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 patients, 21 patients in the newly-initiated group and 25 patients in the existing BOT group performed dose adjustment using 3-3-1 algorithm. HbA1c was significantly improved 4 weeks after the initiation from 8.5% ± 1.2% at baseline to 7.3% ± 0.7% at the final evaluation (p 0.01, vs. Baseline). The average daily insulin units increased throughout the study period from 10.1 ± 6.7 at baseline to 14.6 ± 8.9 units at the final evaluation. Weight didn’t significantly change throughout the study (p = 0.12). The incidents of hypoglycemia were 0.8/month during the insulin dose self-adjustment period and 0.4/month during the follow-up period. The 3-3-1 algorithm using insulin glargine provided a safe and simple dose adjustment and demonstrated its utility in patients who were newly introduced to insulin treatment as well as who were already on BOT.
文摘Considering wireless sensor network characteristics,this paper uses network simulator,version2(NS-2)algorithm to improve Ad hoc on-demand distance vector(AODV)routing algorithm,so that it can be applied to wireless sensor networks.After studying AODV routing protocol,a new algorithm called Must is brought up.This paper introduces the background and algorithm theory of Must,and discusses the details about how to implement Must algorithm.At last,using network simulator(NS-2),the performance of Must is evaluated and compared with that of AODV.Simulation results show that the network using Must algorithm has perfect performance.
基金Supported by the National Natural Science Foun-dation of China (60403027) Natural Science Foundation of HubeiProvince (2005ABA258) the Opening Foundation of State KeyLaboratory of Software Engineering (SKLSE05-07)
文摘This paper describes a routing algorithm for risk scanning agents using ant colony algorithm in P2P(peerto peer) network. Every peer in the P2P network is capable of updating its routing table in a real-time way, which enables agents to dynamically and automatically select, according to current traffic condition of the network, the global optimal traversal path. An adjusting mechanism is given to adjust the routing table when peers join or leave. By means of exchanging pheromone intensity of part of paths, the algorithm provides agents with more choices as to which one to move and avoids prematurely reaching local optimal path. And parameters of the algorithm are determined by lots of simulation testing. And we also compare with other routing algorithms in unstructured P2P network in the end.
基金Project supported by the National Key R&D Program of China(Grant Nos.2017YFA0303302 and 2018YFA0305602)the National Natural Science Foundation of China(Grant No.11921005)Shanghai Municipal Science and Technology Major Project,China(Grant No.2019SHZDZX01)。
文摘We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar to that of a Heisenberg chain.All the solutions of the given Q2SAT problem span the subspace of the degenerate ground states.The Hamiltonian is adiabatically evolved so that the system stays in the degenerate subspace.Our numerical results suggest that the time complexity of our algorithm is O(n^(3.9))for yielding non-trivial solutions for problems with the number of clauses m=dn(n-1)/2(d■0.1).We discuss the advantages of our algorithm over the known quantum and classical algorithms.
基金Project supported by the National Natural Science Foundation of China (No. 60302004)the Natural Science Foundation of HubeiProvince, China (No. 2005ABA264)
文摘Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.