The ART-2 network is a typical adaptive resonance theory based neural network approach for clustering purpose and has been successfully used in many fields. However, one of the fatal shortcomings of traditional ART-2 ...
详细信息
The ART-2 network is a typical adaptive resonance theory based neural network approach for clustering purpose and has been successfully used in many fields. However, one of the fatal shortcomings of traditional ART-2 is that its final results heavily depend on a pre-defined fixed vigilance threshold parameter, which makes it infeasible to be applied in different complicated applications. Another disadvantage of traditional ART-2 method is that the number of categories in the network will increase all the time with the continuous input. Considering these points, an improved algorithm of ART-2 has been presented in this paper called the Robust ART-2. We first systematically analyze the dynamic changes of the optimal vigilance threshold with the succession inputs and propose a new adaptive method to make the network itself can automatically choose the optimal threshold in various situations. Then we introduce a constraint parameter to confine the scale of ART-2 network by limiting the maximal number of categories of network. Simulation experiments including artificial and benchmark data sets demonstrate the effectiveness of our algorithm.
Cognitive radio networks have made a dramatic shift towards variously cooperative paradigm to achieve fast, reliable spectrum sensing and effective spectrum usage in recent past In this paper, we develop a Flexibl...
详细信息
Cognitive radio networks have made a dramatic shift towards variously cooperative paradigm to achieve fast, reliable spectrum sensing and effective spectrum usage in recent past In this paper, we develop a Flexibly Cooperative Spectrum Sensing and Allocation (FCSSA) framework in cognitive radio networks. The proposed FCSSA framework captures the essential interactive function between cooperative spectrum sensing and allocation, which allows licensed channel and secondary users bargaining on their decisions, such as the enforceable requirements of spectrum sensing time, energy detection threshold and secondary users' payment for spectrum access, to maximize their utilities respectively. Moreover, we apply Stackelberg game to formulate the joint cooperative spectrum sensing and allocation design. The leader (authorized agent of licensed channel) decides spectrum sensing time and energy detection threshold according to the predictable behavior of secondary users. The followers (secondary users) make their payment decision underlying a non-cooperative game according to the limited information from licensed channel. Numeric simulations verify that our proposed jointly design framework in cooperative spectrum sensing and allocation can increase the agility and effectiveness of dynamic spectrum usage.
Social learning focuses on the opinion dynamics in the society, which has attracted more and more researchers recently. Different from the existing results on the consensus of social learning in complex networks with ...
详细信息
Social learning focuses on the opinion dynamics in the society, which has attracted more and more researchers recently. Different from the existing results on the consensus of social learning in complex networks with one true state, in this paper we study the social learning in the network society with multi-true-states. A new network social learning model is constructed, where agents from different groups receive different signal sequences generated by different true states. Each agent updates his belief by combining a Bayesian rule on the external signal and a non-Bayesian rule related with his neighboring agents. We analyze the dynamical process, and find that the beliefs of all agents are oscillating all the time and can not access to their corresponding true states, which is totally different from the consensus on social learning with one-true-state. Furthermore, by calculating the largest Lyapunov exponents, chaos is found in the social learning with multi-true-sates.
Ash deposition on heat transfer surfaces still to be a significant problem in power plant utility boilers. The effective ways to deal with this problem are accuracy on-line monitoring of ash fouling and soot-blowing. ...
详细信息
Ash deposition on heat transfer surfaces still to be a significant problem in power plant utility boilers. The effective ways to deal with this problem are accuracy on-line monitoring of ash fouling and soot-blowing. In this paper, the on-line ash fouling monitoring dynamic models of coal-fired utility boiler's heat transfer surfaces are proposed. The fundamental principle of the models is dynamic heat balance method. Finally, taking the economizer of a certain 300MW power plant utility boiler as the object of consideration, ash fouling of the transfer surface has been calculated with real time data from the DCS. The calculation results show the effectiveness of the dynamic models mentioned above. Some preliminary results analysis are shown aiming at the situation that the cleanliness factor has a obvious increased but its not corresponding to the soot-blowing point. The dynamic models are contributed to ash fouling monitoring and optimization of the soot-blowing.
This article describes a split-range tuning method based on the well developed IMC-PID controller for the parameters of the MacPID controller. The goal is to simplify the tuning complexity. Detailed tuning procedure i...
详细信息
This article describes a split-range tuning method based on the well developed IMC-PID controller for the parameters of the MacPID controller. The goal is to simplify the tuning complexity. Detailed tuning procedure is provided. The FOPTD model is employed to compare the proposed idea with the well known tuning methods, such as Ziegler-Nichols, Cohen-Coon and MacPID method to illustrate the simplicity and the practicality of our strategy.
In recent years, fault prediction method, which means forecast process fault in an early time based on the current condition of the system, has attracted more and more attention by companies and scientists. However, i...
详细信息
In recent years, fault prediction method, which means forecast process fault in an early time based on the current condition of the system, has attracted more and more attention by companies and scientists. However, it still has many problems in this area, especially for its application in industrial process. In the present work, a multi-step ahead fault prediction method combining principle component analysis, empirical mode decomposition and extreme learning machine are developed to realize early prediction of fault. The application of the presented method is illustrated with respect to simulated data collected from the Tennessee Eastman process. The experimental results demonstrate the effectiveness of the proposed method.
An optimal excitation controller based on the theory of linear optimal control is designed. TMS320LF2407 is used as its core unit. Taking advantage of the features of DSP such as high performance processing capabiliti...
详细信息
An optimal excitation controller based on the theory of linear optimal control is designed. TMS320LF2407 is used as its core unit. Taking advantage of the features of DSP such as high performance processing capabilities, plenty of peripherals on chip and high real-time control, man functions are realized such as rapid AC sampling, PID control algorithm, digital phase-shifted triggering and etc. The operating results show that the controller has higher control accuracy and better stability.
The collaborative nature of industrial wireless network system (IWNS) brings several advantages over traditional wired industrial monitoring and controlsystems, while commercial products and real-world deployments of...
详细信息
The collaborative nature of industrial wireless network system (IWNS) brings several advantages over traditional wired industrial monitoring and controlsystems, while commercial products and real-world deployments of IWNS are faced with harsh reliability and predictability issues, which are mainly attributed to the unreliable nature of individual wireless link. In this paper, we research Multi-Hop Multi-Channel wireless communication link (WCL). We model Multi-Hop Multi-Channel WCL at first, and then we present a optimal transmission scheduling policy based on join allocation of slots and channels problem. Following that, we relax the problem into a Subprime solution which is suitable for engineering application. At last, we developed testbed and achieved expectation result that Multi Hop Multi-Channel employing our transmission scheduling policy improved reliability obviously.
The fault diagnosis performance of Fisher Discriminant Analysis(FDA) method is superior to Principle Component Analysis(PCA) by taking into account both normal and fault data for modeling. For the cases with insuffici...
详细信息
The fault diagnosis performance of Fisher Discriminant Analysis(FDA) method is superior to Principle Component Analysis(PCA) by taking into account both normal and fault data for modeling. For the cases with insufficient fault data, a diagnosis strategy is developed based on Bootstrap and phase-based Recursive Multi-way Fisher Discriminant Analysis(RMFDA). By this method, modeling data was constructed by Bootstrap. Besides, the diagnosis information of the previous phase was introduced in the next phase for MFDA modeling by combining recursive method. The effectiveness of the proposed method is demonstrated by applying it to the hydraulic tube tester.
作者：
Qing SongXiaofan WangDepartment of Automation
Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China
Computing the shortest paths in graphs is a fundamental problem with numerous applications. The rapid growth of network in size and complexity has made it necessary to decrease the execution time of the shortest path ...
详细信息
ISBN:
(纸本)9781612848006
Computing the shortest paths in graphs is a fundamental problem with numerous applications. The rapid growth of network in size and complexity has made it necessary to decrease the execution time of the shortest path algorithm. We develop an effective graph partition method to retrieve Balanced Traversing Distance partitions and constitute a hierchical graph model based on the decomposed network for accelerating the path queries. We then propose a new heuristic hierarchical routing algorithm that can significantly reduce the search space by pruning unpromising subgraph branches. We evaluate our approach experimentally under different network partition schemes to show the gain in performance.
暂无评论