This paper believes that complex feedback systems are very common and important in the modern engineering technology. It is very difficult to resolve the optimum problem of the complex feedback system. But it has impo...This paper believes that complex feedback systems are very common and important in the modern engineering technology. It is very difficult to resolve the optimum problem of the complex feedback system. But it has important practical value. This paper decomposed the complex feedback system into many subsystems by means of the decomposing method. First, optimize each subsystem on the optimization basis. Second optimize the whole system step by step. Finally, we provide an example of the optimal design of the heat-exchanger used in chemical processes.展开更多
This paper establishes a very important scientific solution to science of complexity for physicists, and presents a multidisciplinary involved physics and engineering. The innovative solution for complex systems prese...This paper establishes a very important scientific solution to science of complexity for physicists, and presents a multidisciplinary involved physics and engineering. The innovative solution for complex systems presented here is verified on the basis of principles in engineering such as feed-back-system analysis using the classical control theory. This paper proposes that a complex system is a closed-loop system with a negative feedback element and is a solvable problem. A complex system can be analyzed using the system analysis theory in control engineering, and its behavior can be realized using a specially designed simulator.展开更多
This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic pr...This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic problem. The solution is not derived from conventional physics based on reductionism, but rather from engineering sciences such as the feedback systems analysis method and engineering principles. Furthermore, this paper presents the conception of the solution to scientists for solving the problem. Moreover, nobody can doubt this research based on simulator. Complex systems are not mysterious science and not black box.展开更多
Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are ...Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks＇ own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism ave solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality a increases, the prevalence decreases more greatly with the same immunization g. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.展开更多
文摘This paper believes that complex feedback systems are very common and important in the modern engineering technology. It is very difficult to resolve the optimum problem of the complex feedback system. But it has important practical value. This paper decomposed the complex feedback system into many subsystems by means of the decomposing method. First, optimize each subsystem on the optimization basis. Second optimize the whole system step by step. Finally, we provide an example of the optimal design of the heat-exchanger used in chemical processes.
文摘This paper establishes a very important scientific solution to science of complexity for physicists, and presents a multidisciplinary involved physics and engineering. The innovative solution for complex systems presented here is verified on the basis of principles in engineering such as feed-back-system analysis using the classical control theory. This paper proposes that a complex system is a closed-loop system with a negative feedback element and is a solvable problem. A complex system can be analyzed using the system analysis theory in control engineering, and its behavior can be realized using a specially designed simulator.
文摘This paper presents an innovative solution regarding complex systems to scientists, and prepares a novel system simulator for complex systems. A complex system in nature is not a black box but a solvable systematic problem. The solution is not derived from conventional physics based on reductionism, but rather from engineering sciences such as the feedback systems analysis method and engineering principles. Furthermore, this paper presents the conception of the solution to scientists for solving the problem. Moreover, nobody can doubt this research based on simulator. Complex systems are not mysterious science and not black box.
基金Project supported by the National Natural Science Foundation of China （Grant No 10375022）.
文摘Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks＇ own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism ave solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality a increases, the prevalence decreases more greatly with the same immunization g. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.
