researchers have shown that the neural network models can be used to find solutions for many optimization problems. Most of these models are energy based models and there is no guarantee the network converges to a glo...
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Cooperative problem solving can be viewed as a complex activity requiring harmonious and dynamic interaction between active agents and passive agents. This problem is currently being addressed by the research communit...
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Cooperative problem solving can be viewed as a complex activity requiring harmonious and dynamic interaction between active agents and passive agents. This problem is currently being addressed by the research community at various levels of abstraction. Broadly, this paper analyzes the problem of cooperative problem solving from a database perspective and argues that recent advances in database technology facilitate development of a viable solution to the above problem. Specifically, in this paper, we first analyze the problem of cooperative problem solving to identify its underlying key characteristics. Based upon our analysis, we partition the problem space into classes along a spectrum and indicate the level of cooperation required. We propose near-term as well as long-term solutions for cooperative problem solving that progressively enhances the functionality of databasesystems by synthesizing appropriate abstractions and techniques. Furthermore, we identify problems, such as agent capability modeling that require further research to address the most general form of cooperative problem solving.
An integrated model for real time alarm processing in a real world terminal power station is applied. The integrated model is a combination of a generic neuro-expert system model, object model, and UNIX operating syst...
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An integrated model for real time alarm processing in a real world terminal power station is applied. The integrated model is a combination of a generic neuro-expert system model, object model, and UNIX operating system process (UOSP) model. It is shown how the massive parallelism and fast execution features of ANNs help to cope with real-time system constraints like data variability and fast response time. For further enhancing reliability, a practical use of competing expert system-artificial neural networks (ES-ANN) objects is proposed.< >
Neural network (or parallel distributed processing) models have been shown to have some potential for solving optimisation problems. Most formulations result in NP-complete problems and solutions rely on energy based ...
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Neural network (or parallel distributed processing) models have been shown to have some potential for solving optimisation problems. Most formulations result in NP-complete problems and solutions rely on energy based models, so there is no guarantee that the network converges to a global optimal solution. In this paper, we propose a non-energy based neural shortest path network based on the principle of dynamic programming and least take all network. No problem of local minima exists and it guarantees to reach the optimal solution. The network can work purely in an asynchronous mode which greatly increases the computation speed.
Most neural network models are energy based models and there is no guarantee that the network converges to a global optimal solution. A new neural shortest path network model is proposed in which no special convergenc...
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Most neural network models are energy based models and there is no guarantee that the network converges to a global optimal solution. A new neural shortest path network model is proposed in which no special convergence procedure needs to be performed. The network can work in a purely asynchronous mode, and is guaranteed to reach the global optimal solution.< >
This paper critically studies approaches that use the theory of fuzzy sets for multi objective decision making with linear programming. Two main approaches are distinguished: one that converts the problem into a singl...
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Various types of CNNs are summarized and the taxonomy of CNN is given according to the different types of grids, processors, interactions, and modes of operation. Next, the CNN Universal Machine is introduced. The arc...
The programmability (as a stored program) of the CNN Universal Machine is discussed first. It is shown why and in which sense this machine is universal. A new type of algorithm, the analogic one, is introduced. The ap...
A novel real-time scheduler was developed to implement an interactive user interface for an existing state-of-the-art, hand-held blood analyzer. A software-timer-based scheduler was designed and implemented and guaran...
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In order to broaden the scope of application of NN's there has been a recent surge of interest in combining artificial neural networks with expert systems to solve real world *** two approaches need to be integrat...
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In order to broaden the scope of application of NN's there has been a recent surge of interest in combining artificial neural networks with expert systems to solve real world *** two approaches need to be integrated in a way that we exploit their strengths and cover their *** generalizing effects of neural nets need to be safely used especially in real-time *** this paper we propose a generic neuro - expert system model which can be used in various problem domains(especially engineering).In order to realize the strengths of both artificial neural nets and expert systems,the model is integrated into an object model and a unix OS process *** is followed by the application of the integrated model to a practical real-time system,mainly alarm processing in power systems.
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