Titlebook: Applications of Soft Computing in Time Series Forecasting; Simulation and Model Pritpal Singh Book 2016 Springer International Publishing S

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https://doi.org/10.1007/978-3-322-85564-0 of FLRs, determination of weight for each FLR, and defuzzification of fuzzified time series values. To resolve the problem associated with the determination of length of intervals, this study suggests a new time series data discretization technique. After generating the intervals, the historical ti

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Allgemeine Pharmakologie der Muskeln In this chapter, we introduce a model to deal with forecasting problems of two-factors. The proposed model is designed using FTS and ANN. In a FTS, the length of intervals in the universe of discourse always affects the results of forecasting. Therefore, an ANN based technique is employed for deter

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https://doi.org/10.1007/978-3-663-07194-5n forecasting models. Therefore, in this chapter, we have intended to introduce a new Type-2 FTS model that can utilize more observations in forecasting. Later, this Type-2 model is enhanced by employing PSO technique. The main motive behind the utilization of the PSO with the Type-2 model is to adj

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https://doi.org/10.1007/978-3-319-26293-2Fuzzy Time Series Modeling; Type 2 Fuzzy Time Series Model; Hybrid Neuro-fuzzy Models; FTS-PSO Model; M-

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