Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867203
Lujun Li, Yanhong Duan, Hui Xie, Changxi Li
Classical conflict is used to express conflict degree in DST. But many studies show that it is not efficient in measuring conflict, because it only consider non-inclusive between evidences. To solve this problem, a new modified measure method of evidence conflict is proposed, which is based on conflict coefficient K and relative coefficient between evidences. It not only reflects the non-inclusive, but also reflects the differences between evidences. Then this paper gives two kinds of self-adaptive fusion model on the basis of DST and PCR5. It is proved by simulation that they are effective in dealing with conflict information. They converge quickly and help the system make the right decision logically. At last, comparison and analysis have be done between two models and some advices are given.
{"title":"Study on self-adaptive fusion model with DST and PCR5","authors":"Lujun Li, Yanhong Duan, Hui Xie, Changxi Li","doi":"10.1109/IMCEC.2016.7867203","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867203","url":null,"abstract":"Classical conflict is used to express conflict degree in DST. But many studies show that it is not efficient in measuring conflict, because it only consider non-inclusive between evidences. To solve this problem, a new modified measure method of evidence conflict is proposed, which is based on conflict coefficient K and relative coefficient between evidences. It not only reflects the non-inclusive, but also reflects the differences between evidences. Then this paper gives two kinds of self-adaptive fusion model on the basis of DST and PCR5. It is proved by simulation that they are effective in dealing with conflict information. They converge quickly and help the system make the right decision logically. At last, comparison and analysis have be done between two models and some advices are given.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124155257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867481
Yu Fan, W. Zhu, Guangzhou Bai, Taibo Li
On the basis of explaining the principles of wavelet transform, neural network, and wavelet neural network, the paper examines two methods of face recognition: one is based on neural network, the other is based on wavelet neural network. The paper also offers the features and differences based on algorithmic simulation. The result of the stimulation reveals that face recognition using wavelet neural network can largely increase the accuracy rate.
{"title":"Face recognition based on wavelet transform and neural network","authors":"Yu Fan, W. Zhu, Guangzhou Bai, Taibo Li","doi":"10.1109/IMCEC.2016.7867481","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867481","url":null,"abstract":"On the basis of explaining the principles of wavelet transform, neural network, and wavelet neural network, the paper examines two methods of face recognition: one is based on neural network, the other is based on wavelet neural network. The paper also offers the features and differences based on algorithmic simulation. The result of the stimulation reveals that face recognition using wavelet neural network can largely increase the accuracy rate.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126373085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Whereas the existing TOA/AOA positioning algorithm based on wireless sensor network fails to consider position error of anchor node(AN) so as to affect the positioning accuracy, this paper proposes a hybrid TOA/AOA positioning algorithm based on GDOP-weighted fusion (G--TOA/AOA). The paper deduces Geometric Dilution of Precision (GDOP) of TOA/AOA positioning method based on single node (S-TOA/AOA). G-TOA/AOA algorithm utilizes GDOP of S-TOA/AOA to give corresponding weight to various rough estimates of blind node(BN), and weighted merge all rough estimates as position estimate of BN. Meanwhile, the paper deduces GDOP calculation formula of G-TOA/AOA algorithm. In the two different types of distribution situation of ANs, the paper analyzes the positioning accuracy of G-TOA/AOA algorithm. Simulation results show that positioning accuracy of G-TOA/AOA algorithm is superior to average weighted positioning algorithm and the positioning performance of G-TOA/AOA algorithm is better when ANs are in non-collinear distribution situation.
{"title":"A hybrid TOA/AOA positioning method based on GDOP-weighted fusion and its Accuracy Analysis","authors":"Fanzeng Kong, Xiukun Ren, Nae Zheng, Guojun Chen, Jiaan Zheng","doi":"10.1109/IMCEC.2016.7867107","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867107","url":null,"abstract":"Whereas the existing TOA/AOA positioning algorithm based on wireless sensor network fails to consider position error of anchor node(AN) so as to affect the positioning accuracy, this paper proposes a hybrid TOA/AOA positioning algorithm based on GDOP-weighted fusion (G--TOA/AOA). The paper deduces Geometric Dilution of Precision (GDOP) of TOA/AOA positioning method based on single node (S-TOA/AOA). G-TOA/AOA algorithm utilizes GDOP of S-TOA/AOA to give corresponding weight to various rough estimates of blind node(BN), and weighted merge all rough estimates as position estimate of BN. Meanwhile, the paper deduces GDOP calculation formula of G-TOA/AOA algorithm. In the two different types of distribution situation of ANs, the paper analyzes the positioning accuracy of G-TOA/AOA algorithm. Simulation results show that positioning accuracy of G-TOA/AOA algorithm is superior to average weighted positioning algorithm and the positioning performance of G-TOA/AOA algorithm is better when ANs are in non-collinear distribution situation.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867371
Wang Yani, Wu Zhendong, Zhang Jianwu, Chen Hongli
With the development of science and the improvement of social information, Biological Recognition Technology (BIT) is becoming increasingly important. Among them, the fingerprint identification technology has become the hot spot because of its feasibility and reliability. The traditional fingerprint identification method relies on matching feature points to get the similarity. Undoubtedly, this method needs a long time to find the feature points, and with the rotation, scaling, damage and other problems of the fingerprint, the robustness is decreased seriously. Aiming at these problems, we propose a robust damaged fingerprint recognition algorithm, which is based on Convolution Neural Network (CNN) of deep learning. It not only has a high resistance to abnormal degeneration, and the recognition process is also simpler than the feature points matching algorithm. In the end of the essay, the recognition rate based on deep learning is compared with the fingerprint identification algorithm based on Kernel Principal Component Analysis (KPCA). Experiments' results show that fingerprint recognition based on deep learning has a higher robustness.
{"title":"A robust damaged fingerprint identification algorithm based on deep learning","authors":"Wang Yani, Wu Zhendong, Zhang Jianwu, Chen Hongli","doi":"10.1109/IMCEC.2016.7867371","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867371","url":null,"abstract":"With the development of science and the improvement of social information, Biological Recognition Technology (BIT) is becoming increasingly important. Among them, the fingerprint identification technology has become the hot spot because of its feasibility and reliability. The traditional fingerprint identification method relies on matching feature points to get the similarity. Undoubtedly, this method needs a long time to find the feature points, and with the rotation, scaling, damage and other problems of the fingerprint, the robustness is decreased seriously. Aiming at these problems, we propose a robust damaged fingerprint recognition algorithm, which is based on Convolution Neural Network (CNN) of deep learning. It not only has a high resistance to abnormal degeneration, and the recognition process is also simpler than the feature points matching algorithm. In the end of the essay, the recognition rate based on deep learning is compared with the fingerprint identification algorithm based on Kernel Principal Component Analysis (KPCA). Experiments' results show that fingerprint recognition based on deep learning has a higher robustness.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115867845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867524
Lei Zhu, X. Liang, Jiong Li, Rui Li
The study of single and bistatic radar scattering characteristics on stealth aircraft, for the future of collaborative detection on aircraft swarms is of great significance. Based on the characteristics analysis of stealth aircraft, using the software FEKO to establish stealth aircraft model, focusing on simulation research in different polarization ways, single and bistatic radar static RCS, through calculation and analysis to build database of single and bistatic radar static RCS about typical stealth aircraft, providing data support for target RCS dynamic study.
{"title":"Simulation analysis on static scattering characteristics of stealth aircraft","authors":"Lei Zhu, X. Liang, Jiong Li, Rui Li","doi":"10.1109/IMCEC.2016.7867524","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867524","url":null,"abstract":"The study of single and bistatic radar scattering characteristics on stealth aircraft, for the future of collaborative detection on aircraft swarms is of great significance. Based on the characteristics analysis of stealth aircraft, using the software FEKO to establish stealth aircraft model, focusing on simulation research in different polarization ways, single and bistatic radar static RCS, through calculation and analysis to build database of single and bistatic radar static RCS about typical stealth aircraft, providing data support for target RCS dynamic study.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"129 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130126009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867183
Peng Tian-qiang, Li Fang
Sparse Coding is a widely used method to represent an image. However, sparse coding and its improved algorithms have the problem of complex computation and long running time and so on. For these problems, we propose an image classification method based on hash codes and space pyramid, which encodes local feature points with hash codes instead of sparse coding. Firstly, extract the local feature points from the images. Second, learn binary auto-encoder hashing functions, which map the local feature points into hash codes. Third, perform binary k-means cluster on the binary hash codes and generate the binary visual vocabularies. Finally, Combine with spatial pyramid matching model, and represent the image by the histogram vector of space pyramid, which is used in image classification. Experimental results show that compared with other sparse coding methods, our method has the shorter time of learning vocabularies and faster encoder speed and higher classification accuracy.
{"title":"Image classification based on hash codes and space pyramid","authors":"Peng Tian-qiang, Li Fang","doi":"10.1109/IMCEC.2016.7867183","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867183","url":null,"abstract":"Sparse Coding is a widely used method to represent an image. However, sparse coding and its improved algorithms have the problem of complex computation and long running time and so on. For these problems, we propose an image classification method based on hash codes and space pyramid, which encodes local feature points with hash codes instead of sparse coding. Firstly, extract the local feature points from the images. Second, learn binary auto-encoder hashing functions, which map the local feature points into hash codes. Third, perform binary k-means cluster on the binary hash codes and generate the binary visual vocabularies. Finally, Combine with spatial pyramid matching model, and represent the image by the histogram vector of space pyramid, which is used in image classification. Experimental results show that compared with other sparse coding methods, our method has the shorter time of learning vocabularies and faster encoder speed and higher classification accuracy.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130454237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867290
Zi-he Qiu, Ping Shi, Da Pan, Dixiu Zhong
Although there exists some methods for coin detection and recognition, it is still a challenging task, especially for coins in natural scene. This paper proposed a method to detect and recognize the coins in natural scene. In the detection part, the Hough detection method is applied to detect the coin areas in the images. Then radius ratio, color feature and relative position constraints are used to eliminate the noise circles. In the recognition part, a multilayer convolutional neural network is used to classify proposals and get the final recognition result. Experimental results show that the proposed method could successfully detect and recognize coins in the given images.
{"title":"Coin detection and recognition in the natural scene","authors":"Zi-he Qiu, Ping Shi, Da Pan, Dixiu Zhong","doi":"10.1109/IMCEC.2016.7867290","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867290","url":null,"abstract":"Although there exists some methods for coin detection and recognition, it is still a challenging task, especially for coins in natural scene. This paper proposed a method to detect and recognize the coins in natural scene. In the detection part, the Hough detection method is applied to detect the coin areas in the images. Then radius ratio, color feature and relative position constraints are used to eliminate the noise circles. In the recognition part, a multilayer convolutional neural network is used to classify proposals and get the final recognition result. Experimental results show that the proposed method could successfully detect and recognize coins in the given images.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134151087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867478
Xu Pengbo, Ji Guodong, Lu Libin, Tan Lining, Ning Jigan
UAV flight safety is the first issue of the UAV's attention. The establishment of a UAV flight monitoring system not only meets the needs of the army but also has important significance. This paper introduces the development status and trends of aircraft fault prediction and health management at home and abroad. The key technologies of UAV flight monitoring system are analyzed, Including flight state parameters acquisition technology, parameter data real-time analysis technology, system condition monitoring model established and system prediction model establishment, system security model, security model and the prediction model of flight safety online monitoring technology, security model and prediction model of control instruction technology assessment. Small unmanned aircraft motion model is established. The pitching Angle, roll Angle, yaw Angle and engine speed are simulated experiment. At last, the paper introduces the function and the significance of the UAV flight monitoring system.
{"title":"The key technology and simulation of UAV flight monitoring system","authors":"Xu Pengbo, Ji Guodong, Lu Libin, Tan Lining, Ning Jigan","doi":"10.1109/IMCEC.2016.7867478","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867478","url":null,"abstract":"UAV flight safety is the first issue of the UAV's attention. The establishment of a UAV flight monitoring system not only meets the needs of the army but also has important significance. This paper introduces the development status and trends of aircraft fault prediction and health management at home and abroad. The key technologies of UAV flight monitoring system are analyzed, Including flight state parameters acquisition technology, parameter data real-time analysis technology, system condition monitoring model established and system prediction model establishment, system security model, security model and the prediction model of flight safety online monitoring technology, security model and prediction model of control instruction technology assessment. Small unmanned aircraft motion model is established. The pitching Angle, roll Angle, yaw Angle and engine speed are simulated experiment. At last, the paper introduces the function and the significance of the UAV flight monitoring system.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134378896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867422
Zhiyuan He, Shaoqing Liu, J. Hu, Huawei Xu, Qingli Huang, Qunxing Liu
In this work, the electrical properties of AlGaN/GaN heterostructure grown on Si substrate with low-temperature AlN (LT-AlN) interlayers were investigated. Hall effect measurement was used to test the electrical properties of AlGaN/GaN heterostructure in all samples with different LT-AlN thickness. It is showed that the thickness of low-temperature AlN interlayers in the bufferlayer obviously effect the electrical properties of two-dimensional electron gas (2DEG) in the heterostructure channel. The sample with 15 nm LT-AlN interlayers reached the maximum electron mobility of 4090 cm2/Vs. Combined with XRD and AFM measurements, it is found that the dislocation density, surface roughness and stress conditions determined the electrical properties of 2DEG.
{"title":"Influence of the low-temperature AlN interlayers on the electrical properties of AlGaN/GaN heterostructure on Si substrate","authors":"Zhiyuan He, Shaoqing Liu, J. Hu, Huawei Xu, Qingli Huang, Qunxing Liu","doi":"10.1109/IMCEC.2016.7867422","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867422","url":null,"abstract":"In this work, the electrical properties of AlGaN/GaN heterostructure grown on Si substrate with low-temperature AlN (LT-AlN) interlayers were investigated. Hall effect measurement was used to test the electrical properties of AlGaN/GaN heterostructure in all samples with different LT-AlN thickness. It is showed that the thickness of low-temperature AlN interlayers in the bufferlayer obviously effect the electrical properties of two-dimensional electron gas (2DEG) in the heterostructure channel. The sample with 15 nm LT-AlN interlayers reached the maximum electron mobility of 4090 cm2/Vs. Combined with XRD and AFM measurements, it is found that the dislocation density, surface roughness and stress conditions determined the electrical properties of 2DEG.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133092672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/IMCEC.2016.7867275
Hanqiao Huang, Y. Wang, Huan Zhou, Kangsheng Dong, Heming Liu
Path planning of the unmanned aerial vehicle(UAV) under the condition of uncertainty of environment remains a challenge because of many constraints. In this paper, a multiple unmanned combat aerial vehicle (multi-UCAV) cooperative autonomous attack path planning method under complex and uncertain environment is put forward. A general framework of multi-UCAV cooperative combat and autonomous attack is designed. Then, the relative movement situation of the UCAV formation is studied and the task assignment model for attacking multi-target is established. On this basis, an improved ant colony algorithm (ACA) is used to solve the corresponding optimal problem. By taking the three degrees of freedom model of UCAV as a core and considering various constraints such as aerodynamic characteristics, thrust variation, target projection area and threat area, an accurate cooperative autonomous attack path planning model for multi-UCAV is built and an improved rolling pseudospectral method(RPM) is applied to calculate the optimal trajectory from the current location to the launch acceptable region. Simulation results show that the proposed ACA and RPM can deal with the task assignment and path planning of multi-UCAV effectively, and they have higher precision and better real-time compared with some existed methods.
{"title":"Multi-UCAV cooperative autonomous attack path planning method under uncertain environment","authors":"Hanqiao Huang, Y. Wang, Huan Zhou, Kangsheng Dong, Heming Liu","doi":"10.1109/IMCEC.2016.7867275","DOIUrl":"https://doi.org/10.1109/IMCEC.2016.7867275","url":null,"abstract":"Path planning of the unmanned aerial vehicle(UAV) under the condition of uncertainty of environment remains a challenge because of many constraints. In this paper, a multiple unmanned combat aerial vehicle (multi-UCAV) cooperative autonomous attack path planning method under complex and uncertain environment is put forward. A general framework of multi-UCAV cooperative combat and autonomous attack is designed. Then, the relative movement situation of the UCAV formation is studied and the task assignment model for attacking multi-target is established. On this basis, an improved ant colony algorithm (ACA) is used to solve the corresponding optimal problem. By taking the three degrees of freedom model of UCAV as a core and considering various constraints such as aerodynamic characteristics, thrust variation, target projection area and threat area, an accurate cooperative autonomous attack path planning model for multi-UCAV is built and an improved rolling pseudospectral method(RPM) is applied to calculate the optimal trajectory from the current location to the launch acceptable region. Simulation results show that the proposed ACA and RPM can deal with the task assignment and path planning of multi-UCAV effectively, and they have higher precision and better real-time compared with some existed methods.","PeriodicalId":218222,"journal":{"name":"2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128936269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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