The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform

Ming Yang - One of the best experts on this subject based on the ideXlab platform.

  • Verification of Command and Control Models
    2007 2nd IEEE Conference on Industrial Electronics and Applications, 2007
    Co-Authors: Jin Cheng, Fei Liu, Ming Yang
    Abstract:

    Command and Control models, often represented as rules or fuzzy rules, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of Command and Control models. Based on an analysis of the characteristics of Command and Control models, this paper presents a fuzzy causality diagram-based verification method for Command and Control models. Firstly, a formal description method is developed to describe Command and Control models. Secondly, formally described Command and Control models are mapped to fuzzy causality diagram. Thirdly, formal verification criteria for Command and Control models are developed in order to validly and formally verify them, based on which verification is grouped into two classes: weak verification and strong verification. Finally, algorithms for weak and strong verification are developed, thus implementing formal verification of Command and Control models.

Jin Cheng - One of the best experts on this subject based on the ideXlab platform.

  • Verification of Command and Control Models
    2007 2nd IEEE Conference on Industrial Electronics and Applications, 2007
    Co-Authors: Jin Cheng, Fei Liu, Ming Yang
    Abstract:

    Command and Control models, often represented as rules or fuzzy rules, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of Command and Control models. Based on an analysis of the characteristics of Command and Control models, this paper presents a fuzzy causality diagram-based verification method for Command and Control models. Firstly, a formal description method is developed to describe Command and Control models. Secondly, formally described Command and Control models are mapped to fuzzy causality diagram. Thirdly, formal verification criteria for Command and Control models are developed in order to validly and formally verify them, based on which verification is grouped into two classes: weak verification and strong verification. Finally, algorithms for weak and strong verification are developed, thus implementing formal verification of Command and Control models.

Xiaocheng Liu - One of the best experts on this subject based on the ideXlab platform.

  • Mission-based Command and Control behavior model
    2016 IEEE International Conference on Mechatronics and Automation, 2016
    Co-Authors: Lin Sun, Yabing Zha, Peng Jiao, Xiaocheng Liu
    Abstract:

    The Command and Control behavior modeling is an important part of military analytical simulation. However, weaknesses including hard modeling, poor expansibility and little flexibility still exist in current Command and Control behavior models. In this paper, a mission-based Command and Control behavior model is designed, which consists of a Compound Mission Module as well as a General Mission Management Module. The Compound Mission Module based on improved hierarchical task network (HTN) not only supports hierarchical mission structuring but further extends HTN's ability of describing temporal and logical relations among sub-missions. This module helps to improve the expansibility and flexibility of the behavior model to some extent. The General Mission Management Module provides uniform mission management method and compound mission inner Controlling method for combat entities. It spares the effort of developers to design specific logics for mission management and thus makes them more concentrating on detailed lower level mission modeling. Experiment results show that this mission-based Command and Control behavior model not only reduces the difficulty of modeling but also improves its expansibility and flexibility.

Fei Liu - One of the best experts on this subject based on the ideXlab platform.

  • Verification of Command and Control Models
    2007 2nd IEEE Conference on Industrial Electronics and Applications, 2007
    Co-Authors: Jin Cheng, Fei Liu, Ming Yang
    Abstract:

    Command and Control models, often represented as rules or fuzzy rules, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of Command and Control models. Based on an analysis of the characteristics of Command and Control models, this paper presents a fuzzy causality diagram-based verification method for Command and Control models. Firstly, a formal description method is developed to describe Command and Control models. Secondly, formally described Command and Control models are mapped to fuzzy causality diagram. Thirdly, formal verification criteria for Command and Control models are developed in order to validly and formally verify them, based on which verification is grouped into two classes: weak verification and strong verification. Finally, algorithms for weak and strong verification are developed, thus implementing formal verification of Command and Control models.

Liao Xiao-lin - One of the best experts on this subject based on the ideXlab platform.

  • Simulation Method of Command and Control Process Based on Petri Net
    Computer Simulation, 2012
    Co-Authors: Liao Xiao-lin
    Abstract:

    Operational Command and Control process is an important factor for army combat efficiency.Based on characteristics of operational Command and Control process,the essential elements were analyzed,the modeling and simulation method of operational Command and Control process based on Petri net was proposed,and its fire rules and conflict analyze algorithm were established.Simulation environment of operational Command and Control process was designed and developed.Quantitative analysis was realized by simulation of operational Command and Control process,and provided the decision support for its optimize and improvement.