We explore the tracking problem of a maneuvering target. Tracking agents with third-order kinematics can communicate with each other via wireless network. The communication network topology is arbitrary rather than switches among several fixed topologies. The information sharing and interaction among agents are position, velocity, and acceleration. Some sufficient conditions of tracking strategy have been proposed. Finally, a numerical example is employed to demonstrate the effectiveness of proposed tracking strategy.
Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches’ ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method’s rationality and feasibility when using different data from different sources.
Abstract:As a typical phenomenon of eutrophication pollution, algal bloom threatens public health and water security. The governance of algal bloom is largely affected by administrators' knowledge and experience, which may lead to a subjective and one-sided decision-making result. Meanwhile, experts in the specific field can provide professional support. How to utilize expert resources adequately and automatically has been a problem. This paper proposes an expert decision support technique for algal bloom governance based on text analysis methods. Firstly, the decision support mechanism is introduced to form a general decision-making framework. Secondly, the expert classification method is proposed to help with choosing suitable experts. Thirdly, a multi-criteria group decision-making method is presented based on the automatic analysis of experts' decision opinions. Finally, an experiment is conducted to verify the expert decision support technique. The results show the technique's feasibility and rationality. This paper describes experts' information and opinions with natural language, which can intuitively reflect the natural meaning. The expert decision support technique based on text analysis broadens the management thought of water pollution in urban lakes.
Tracking problem under a time-varying topology * Dong Li-Jing(董立静) a) , Chai Sen-Chun(柴森春) a) † , Zhang Bai-Hai(张百海) a) , and Nguang Sing-Kiong(阮盛强) b) a) School of Automation, Beijing Institute of Technology,Beijing 100081, China
Immunizations on small worlds of tree-based wireless sensor networks Li Qiao(李 峤) a) † , Zhang Bai-Hai(张百海) a) , Cui Ling-Guo(崔灵果) a) , Fan Zhun(范 衠) b) , and Athanasios V. Vasilakos c)
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