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  • Open Access

    ARTICLE

    A Multi-Agent System for Environmental Monitoring Using Boolean Networks and Reinforcement Learning

    Hanzhong Zheng1, Dejie Shi2,*

    Journal of Cyber Security, Vol.2, No.2, pp. 85-96, 2020, DOI:10.32604/jcs.2020.010086

    Abstract Distributed wireless sensor networks have been shown to be effective for environmental monitoring tasks, in which multiple sensors are deployed in a wide range of the environments to collect information or monitor a particular event, Wireless sensor networks, consisting of a large number of interacting sensors, have been successful in a variety of applications where they are able to share information using different transmission protocols through the communication network. However, the irregular and dynamic environment requires traditional wireless sensor networks to have frequent communications to exchange the most recent information, which can easily generate high communication cost through the collaborative… More >

  • Open Access

    ARTICLE

    Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme

    Yueqi Hou1, Xiaolong Liang1, 2, Lyulong He1, Jiaqiang Zhang1, *, Jie Zhu3, Baoxiang Ren3

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1335-1349, 2020, DOI:10.32604/cmc.2020.06869

    Abstract Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications. This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme. The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors. We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously. The acceleration constraint is… More >

  • Open Access

    ARTICLE

    Exploring Urban Population Forecasting and Spatial Distribution Modeling with Artificial Intelligence Technology

    Yan Zou1,2,3,*, Shaoliang Zhang1, Yanhai Min1

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 295-310, 2019, DOI:10.32604/cmes.2019.03873

    Abstract The high precision population forecasting and spatial distribution modeling are very important for the theory and application of population sociology, city planning and Geo-Informatics. However, the two problems need to be solved for providing the high precision population information. One is how to improve the population forecasting precision of small area (e.g., street scale); another is how to improve the spatial resolution of urban population distribution model. To solve the two problems, some new methods are proposed in this contribution. (1) To improve the precision of small area population forecasting, a new method is developed based on the fade factor… More >

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