Occupant's identity and location are important information for lighting control in order to reduce the energy consumption while increasing livelihood. While active RFID system provides occupant's identity, it ...
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Occupant's identity and location are important information for lighting control in order to reduce the energy consumption while increasing livelihood. While active RFID system provides occupant's identity, it is nontrivial to localize the occupant's location in an indoor environment due to the multipath effect, the changing environment, and the unreliable communication link. In this paper, we implement a system with multiple active RFID readers, and develop a localization algorithm based on support vector machine (SVM). The algorithm uses round-robin comparison to localize the occupant to one of the multiple regions in a floor. The geometric relationship among the rooms and the historical localization data are used to further improve the localization accuracy. Numerical results demonstrate a high localization accuracy of this algorithm. We hope this work sheds insight on lighting control for energy saving and an increased livelihood.
Planning for a complex remanufacturing systems is often an NP-hard problem in terms of computational complexity and simulation is usually the only available but very time-consuming approach in many cases. Ordinal opti...
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Planning for a complex remanufacturing systems is often an NP-hard problem in terms of computational complexity and simulation is usually the only available but very time-consuming approach in many cases. Ordinal optimization offers an efficient framework for simulation based optimization approaches. In this paper, a new constrained ordinal optimization method is presented for solving remanufacturing planning problems. The scheme of "Horse Race" with Feasibility Modeal (HRFM) is developed to select the set of good enough plans. The rough set method in machine learning and knowledge discovery is applied to generate rules for feasibility determination. This method is compared with the Blind Picking with Feasibility Model (BPFM) method. Numerical testing of a practical remanufacturing system shows that the HRFM method presented in this paper is more efficient to meet the same required alignment probability.
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