To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before app...To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.展开更多
Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they ...Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.展开更多
A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set ...A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set of sensors. Then, a hybrid estimation algorithm was designed to compute the estimates of the continuous and discrete states of the SLHS based on the observations from the selected sensors. As the sensor scheduling algorithm is designed such that the Bayesian decision risk is minimized, the true discrete state can be better identified. Moreover, the continuous state estimation performance of the proposed algorithm is better than that of hybrid estimation algorithms using only predetermined sensors. Finallyo the algorithms are validated through an illustrative target tracking example.展开更多
The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence m...The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence method to analyze fault information and make fault diagnosis. The paper implements the core part of the fault expert system the design of knowledge base and fault inference engine.展开更多
基金Project(51204082)supported by the National Natural Science Foundation of ChinaProject(KKSY201458118)supported by the Talent Cultivation Project of Kuning University of Science and Technology,China
文摘To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.
基金Supported by the National Science and Technology Major Project (No.2011ZX03005-004-04)the National Grand Fundamental Research 973 Program of China (No.2011CB302-905)+2 种基金the National Natural Science Foundation of China (No.61170058,61272133,and 51274202)the Research Fund for the Doctoral Program of Higher Education of China (No.20103402110041)the Suzhou Fundamental Research Project (No.SYG201143)
文摘Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.
基金Foundation item： Project（2012AA051603） supported by the National High Technology Research and Development Program 863 Plan of China
文摘A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set of sensors. Then, a hybrid estimation algorithm was designed to compute the estimates of the continuous and discrete states of the SLHS based on the observations from the selected sensors. As the sensor scheduling algorithm is designed such that the Bayesian decision risk is minimized, the true discrete state can be better identified. Moreover, the continuous state estimation performance of the proposed algorithm is better than that of hybrid estimation algorithms using only predetermined sensors. Finallyo the algorithms are validated through an illustrative target tracking example.
文摘The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence method to analyze fault information and make fault diagnosis. The paper implements the core part of the fault expert system the design of knowledge base and fault inference engine.
