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Relevant bibliographies by topics / Swarm verification

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Journal articles
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Academic literature on the topic 'Swarm verification'

Author: Grafiati

Published: 31 May 2023

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Journal articles on the topic "Swarm verification"

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Holzmann, Gerard J., Rajeev Joshi, and Alex Groce. "Swarm Verification Techniques." IEEE Transactions on Software Engineering 37, no. 6 (2011): 845–57. http://dx.doi.org/10.1109/tse.2010.110.

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LU, Nan, Xiaodong WANG, Zheng TANG, and Pei HE. "Modeling method of unmanned aerial vehicle swarm behavior based on spatiotemporal hybrid Petri net." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 4 (2022): 812–18. http://dx.doi.org/10.1051/jnwpu/20224040812.

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The more and more widely used UAV swarm operations have received great attention in the new global military revolution of informatization, and the integrated modeling of UAV swarms has great significance and value for the testing and verification of combat modes. Aiming at the modeling and simulation requirements of combat scenarios, taking the collaborative combat process of heterogeneous UAV swarms as the research object, starting from the modeling of a single UAV, on the basis of the formalization and mathematical description of the single combat process, this paper employs Petri nets based

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Wijs, Anton. "Informed Swarm Verification of Infinite-State Systems." Electronic Proceedings in Theoretical Computer Science 73 (November 11, 2011): 19. http://dx.doi.org/10.4204/eptcs.73.4.

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Dixon, Clare, Alan F. T. Winfield, Michael Fisher, and Chengxiu Zeng. "Towards temporal verification of swarm robotic systems." Robotics and Autonomous Systems 60, no. 11 (2012): 1429–41. http://dx.doi.org/10.1016/j.robot.2012.03.003.

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Sharmila D , A. V. Pra.bu, N. Selvaganesh,. "AUTHORSHIP VERIFICATION USING MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM." Psychology and Education Journal 58, no. 1 (2021): 4262–66. http://dx.doi.org/10.17762/pae.v58i1.1492.

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Digital forensics is the study of recovery and investigation of the materials found in digital devices, mainly in computers. Forensic authorship analysis is a branch of digital forensics. It includes tasks such as authorship attribution, authorship verification, and author profiling. In Authorship verification, with a given a set of sample documents D written by an author A and an unknown document d, the task is to find whether document d is written by A or not. Authorship verification has been previously done using genetic algorithms, SVM classifiers, etc. The existing system creates an ensem

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Huang, Ai Ming, and Mao Ling Pen. "Multi Biometrics Fusion Identity Verification Based on Particle Swarm Optimization." Applied Mechanics and Materials 44-47 (December 2010): 3195–99. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3195.

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In recent years, biometrics has become one of the most promising identity verification technologies. For the limitations, it is difficult for single mode biometrics to meet requirements of modern identity verification. The paper introduced several common biometrics verification methods and procedures. The limitations of single mode biometrics were also provided and data fusion technology was introduced to solve the problem. On the basis of this, Particle Swarm Optimization (PSO) neural network algorithm was used to construct multi biometrics verification system. The results of experiment based

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Wang, Chuanyun, Yang Su, Jingjing Wang, Tian Wang, and Qian Gao. "UAVSwarm Dataset: An Unmanned Aerial Vehicle Swarm Dataset for Multiple Object Tracking." Remote Sensing 14, no. 11 (2022): 2601. http://dx.doi.org/10.3390/rs14112601.

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In recent years, with the rapid development of unmanned aerial vehicles (UAV) technology and swarm intelligence technology, hundreds of small-scale and low-cost UAV constitute swarms carry out complex combat tasks in the form of ad hoc networks, which brings great threats and challenges to low-altitude airspace defense. Security requirements for low-altitude airspace defense, using visual detection technology to detect and track incoming UAV swarms, is the premise of anti-UAV strategy. Therefore, this study first collected many UAV swarm videos and manually annotated a dataset named UAVSwarm d

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Huang, Yixin, Xiaojia Xiang, Han Zhou, Dengqing Tang, and Yihao Sun. "Online Identification-Verification-Prediction Method for Parallel System Control of UAVs." Aerospace 8, no. 4 (2021): 99. http://dx.doi.org/10.3390/aerospace8040099.

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In order to solve the problem of how to efficiently control a large-scale swarm Unmanned Aerial Vehicle (UAV) system, which performs complex tasks with limited manpower in a non-ideal environment, this paper proposes a parallel UAV swarm control method. The key technology of parallel control is to establish a one-to-one artificial UAV system corresponding to the aerial swarm UAV on the ground. This paper focuses on the computational experiments algorithm for artificial UAV system establishment, including data processing, model identification, model verification and state prediction. Furthermor

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V. Gayetri Devi, S., C. Nalini, and N. Kumar. "An efficient software verification using multi-layered software verification tool." International Journal of Engineering & Technology 7, no. 2.21 (2018): 454. http://dx.doi.org/10.14419/ijet.v7i2.21.12465.

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Rapid advancements in Software Verification and Validation have been critical in the wide development of tools and techniques to identify potential Concurrent bugs and hence verify the software correctness. A concurrent program has multiple processes and shared objects. Each process is a sequential program and they use the shared objects for communication for completion of a task. The primary objective of this survey is retrospective review of different tools and methods used for the verification of real-time concurrent software. This paper describes the proposed tool ‘F-JAVA’ for multithreade

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Zhang, Hong, and Masumi Ishikawa. "The performance verification of an evolutionary canonical particle swarm optimizer." Neural Networks 23, no. 4 (2010): 510–16. http://dx.doi.org/10.1016/j.neunet.2009.12.002.

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Dissertations / Theses on the topic "Swarm verification"

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Cheng, Xueqi. "Exploring Hybrid Dynamic and Static Techniques for Software Verification." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/26216.

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With the growing importance of software on which human lives increasingly depend, the correctness requirement of the underlying software becomes especially critical. However, the increasing complexities and sizes of modern software systems pose special challenges on the effectiveness as well as efficiency of software verification. Two major obstacles include the quality of test generation in terms of error detection in software testing and the state space explosion problem in software formal verification (model checking). In this dissertation, we investigate several hybrid techniques that exp

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Puri, Prateek. "Design Validation of RTL Circuits using Binary Particle Swarm Optimization and Symbolic Execution." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/55815.

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Over the last two decades, chip design has been conducted at the register transfer (RT) Level using Hardware Descriptive Languages (HDL), such as VHDL and Verilog. The modeling at the behavioral level not only allows for better representation and understanding of the design, but also allows for encapsulation of the sub-modules as well, thus increasing productivity. Despite these benefits, validating a RTL design is not necessarily easier. Today, design validation is considered one of the most time and resource consuming aspects of hardware design. The high costs associated with late dete

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Gent, Kelson Andrew. "High Quality Test Generation at the Register Transfer Level." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73544.

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Integrated circuits, from general purpose microprocessors to application specific designs (ASICs), have become ubiquitous in modern technology. As our applications have become more complex, so too have the circuits used to drive them. Moore's law predicts that the number of transistors on a chip doubles every 18-24 months. This explosion in circuit size has also lead to significant growth in testing effort required to verify the design. In order to cope with the required effort, the testing problem must be approached from several different design levels. In particular, exploiting the Register

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Fournier, Émilien. "Accélération matérielle de la vérification de sûreté et vivacité sur des architectures reconfigurables." Electronic Thesis or Diss., Brest, École nationale supérieure de techniques avancées Bretagne, 2022. http://www.theses.fr/2022ENTA0006.

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Le Model-Checking est une technique automatisée, utilisée dans l’industrie pour la vérification, enjeu majeur pour la conception de systèmes fiables, cadre dans lequel performance et scalabilité sont critiques. La vérification swarm améliore la scalabilité par une approche partielle reposant sur l’exécution concurrente d’analyses randomisées. Les architectures reconfigurables promettent des gains de performance significatifs. Cependant, les travaux existant souffrent d’une conception monolithique qui freine l’exploration des opportunités des architectures reconfigurable. De plus, ces travaux s

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Liu, Xuan-You, and 劉軒佑. "Simulation of Swarm Intelligence in Pollution Sources Searching and Verification of Group Flight Formation." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/293xxw.

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碩士<br>國立中山大學<br>資訊工程學系研究所<br>107<br>This thesis presents a group UAV navigation system for air pollution search. The system consists of a number of unmaned aerial vehicles equipped with air pollution sensors. The communication among the drones is through the Message Queuing Telemetry Transport （MQTT） protocol. In addition, the information collected by the sensors mounted on the drones will immediately be transmitted and presented visually on the control panel. Furthermore, an improved swarm intelligence algorithm for pollution source search is proposed to allow the drones to search for multipl

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Chien, Shih-Hai, and 錢世海. "A Study on Calculating the Optimal Turn-on Angle of Multilevel Cascade Inverter with Particle Swarm Optimization to Reduce Total Harmonic Distortion and the Verification of Hardware-in-the-loop." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/31463317801239457041.

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碩士<br>國立聯合大學<br>電機工程學系碩士班<br>102<br>The optimal switch conduction angle to solve the cascade multilevel inverter is regarded as the research subject in this study. The voltage on the power switches of a cascade multilevel inverter could be applied to high-power environments. Nevertheless, it is necessary to use the modulation strategy to have the output waveform approach sine waves, where the harmonic optimization staircase waveform strategy in step modulation could reduce the switching frequency. However, nonlinear equations need to be solved for calculating the optimal switch conduction angl

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Book chapters on the topic "Swarm verification"

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Wijs, Anton. "Towards Informed Swarm Verification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20398-5_30.

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Cavalcanti, Ana, Alvaro Miyazawa, Augusto Sampaio, Wei Li, Pedro Ribeiro, and Jon Timmis. "Modelling and Verification for Swarm Robotics." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98938-9_1.

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Konur, Savas, Clare Dixon, and Michael Fisher. "Formal Verification of Probabilistic Swarm Behaviours." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15461-4_42.

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Escalante, Hugo Jair, Manuel Montes, and Luis Villaseñor. "Particle Swarm Model Selection for Authorship Verification." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_66.

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Nemati, Shahla, and Mohammad Ehsan Basiri. "Particle Swarm Optimization for Feature Selection in Speaker Verification." In Applications of Evolutionary Computation. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12239-2_39.

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Kosak, Oliver, Felix Bohn, Lennart Eing, et al. "Swarm and Collective Capabilities for Multipotent Robot Ensembles." In Leveraging Applications of Formal Methods, Verification and Validation: Engineering Principles. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61470-6_31.

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Dixon, Clare, Alan Winfield, and Michael Fisher. "Towards Temporal Verification of Emergent Behaviours in Swarm Robotic Systems." In Towards Autonomous Robotic Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23232-9_30.

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Piho, Paul, and Jane Hillston. "A Case Study of Policy Synthesis for Swarm Robotics." In Leveraging Applications of Formal Methods, Verification and Validation: Engineering Principles. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61470-6_29.

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Kosak, Oliver, Lukas Huhn, Felix Bohn, Constantin Wanninger, Alwin Hoffmann, and Wolfgang Reif. "Maple-Swarm: Programming Collective Behavior for Ensembles by Extending HTN-Planning." In Leveraging Applications of Formal Methods, Verification and Validation: Engineering Principles. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61470-6_30.

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He, Yang, Kai Qu, and Xiaokai Xia. "Simulation Verification of Cruise Missile Route Planning Based on Swarm Intelligence Algorithm." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-9195-0_44.

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Conference papers on the topic "Swarm verification"

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Holzmann, Gerard J., Rajeev Joshi, and Alex Groce. "Swarm Verification." In 2008 23rd IEEE/ACM International Conference on Automated Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/ase.2008.9.

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Lomuscio, Alessio, and Edoardo Pirovano. "Verifying Fault-Tolerance in Probabilistic Swarm Systems." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/46.

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We present a method for reasoning about fault-tolerance in unbounded robotic swarms. We introduce a novel semantics that accounts for the probabilistic nature of both the swarm and possible malfunctions, as well as the unbounded nature of swarm systems. We define and interpret a variant of probabilistic linear-time temporal logic on the resulting executions, including those arising from faulty behaviour by some of the agents in the swarm. We specify the decision problem of parameterised fault-tolerance, which concerns determining whether a probabilistic specification holds under possibly fault

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Manshor, Siti Hakimah, Shuzlina Abdul-Rahman, Yap May Lin, Sofianita Mutalib, and Azlinah Mohamed. "Signature verification using Particle Swarm Optimisation." In 2010 International Conference of Soft Computing and Pattern Recognition (SoCPaR). IEEE, 2010. http://dx.doi.org/10.1109/socpar.2010.5686089.

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Hart, Shae T., Nathan J. Metzger, Maximilian E. Reese, Robert T. McDonald, Michael A. Neumann, and Christopher A. Kitts. "Robotics Simulator for Development and Verification of Swarm Behaviors." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97622.

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Abstract Swarm control strategies allow for decentralized control of many simple robots to perform collective behaviors based on local interactions. We have created a new platform for developing and exploring swarm behaviors, supporting both simulation and experimental verification. The platform, designed entirely in Simulink, provides a simple implementation with satisfactory dynamics to replicate experimental trials on Santa Clara University’s Robotic Systems Laboratory’s Low-Cost Indoor Testbed. The platform allows for seamless transitions from simulation to experimentation on the testbed.

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Baojun, Tong, Hou Ligang, Wang Zhongchao, Wang Wensi, and Wang Jinhui. "Intelligent car platform for swarm algorithm verification." In 2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI). IEEE, 2017. http://dx.doi.org/10.1109/icemi.2017.8265765.

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Sauter, John A., and Kellen Bixler. "DSOARS: a swarm engineering and verification environment." In Unmanned Systems Technology XXI, edited by Charles M. Shoemaker, Paul L. Muench, and Hoa G. Nguyen. SPIE, 2019. http://dx.doi.org/10.1117/12.2518127.

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Zhang, Zhengkui, Brian Nielsen, and Kim G. Larsen. "Time optimal reachability analysis using swarm verification." In SAC 2016: Symposium on Applied Computing. ACM, 2016. http://dx.doi.org/10.1145/2851613.2851828.

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Fournier, Emilien, Ciprian Teodorov, and Loic Lagadec. "Dolmen: FPGA Swarm for Safety and Liveness Verification." In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2022. http://dx.doi.org/10.23919/date54114.2022.9774528.

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Yazdani, Fereshte, and Mehran Emadi Andani. "Verification based on palm vein by estimating wavelet coefficient with autoregressive model." In 2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC). IEEE, 2017. http://dx.doi.org/10.1109/csiec.2017.7940166.

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Fournier, Emilien, Ciprian Teodorov, and Loic Lagadec. "Carnac: Algorithm Variability for Fast Swarm Verification on FPGA." In 2021 31st International Conference on Field-Programmable Logic and Applications (FPL). IEEE, 2021. http://dx.doi.org/10.1109/fpl53798.2021.00038.

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