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A fuzzy evidence accrual system is applied to the problem of sustainable manufacturing. The evidence accrual system can incorporate nonnumeric information as inputs, allowing calculations that combine the three pillars of sustainability: environment, social factors, and economics. This is performed using a fuzzy Kalman filter, a technique previously applied to situational assessment in defense and...
We present a near-optimal deterministic filter for systems that evolve on the unit circle. Unlike suboptimal filtering algorithms that rely on approximations of the system, the proposed approach preserves the non-linear system model. This leads to an explicit bound on the optimality gap in terms of the tracking error. Specifically, the optimality gap is bounded by a term that is fourth-order in the...
This paper deals with the problem of cooperative tracking using large groups of sensor nodes. A Kalman filter-like estimator is implemented and tested for this purpose. The focus of this paper is to examine the effect of the sensor density in the monitored area on the accuracy of the tracking results. The work is mainly motivated by the fact that the target position information issued by a sensor...
Based on the analysis of the standard Particle Swarm Optimization and the characteristic of typical multi-intersection for urban trunk road, a traffic flow forecasting model using dynamic recursion neural network is presented. The feature of this network is that the output of the hidden layer connects to the input of itself through the delay and storage of the context layer. The method of self-connection...
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