Yu-Ming Lu

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Revenue forecasting is difficult but essential for companies that want to create high-quality revenue budgets, especially in an uncertain economic environment with changing government policies. Under these conditions, the subjective judgment of decision makers is a crucial factor in making accurate forecasts. This investigation develops a fuzzy(More)
This study develops the kernel intuitionistic fuzzy c-means clustering (KIFCM), and applies KIFCM in E-learning customer analysis. KIFCM combines intuitionistic fuzzy sets (IFSs) with kernel fuzzy c-means clustering (KFCM). The KIFCM has advantages of IFSs and KFCM which can effectively handle uncertain data and simultaneously map data to kernel space. The(More)
This study applies an intuitionistic type-2 fuzzy inference system (FIS) to e-learning system. This study utilizes the advantages of intuitionistic fuzzy set and type-2 fuzzy inference system, which have been proven to be most effective in uncertain environment, to recommend e-learning courses. The learning readiness is difficultly found in e-leaning(More)
Abstract—This paper proposes a robot deployment algorithm that overcomes unpredicted obstacle, and employs a full-coverage deployment with the minimal number of sensor nodes. Without providing the location information, a spiral movement rule is proposed for robot efficiently deploying sensors to achieve power conservation and full-coverage purposes.(More)
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