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Considerable research outcomes on stock index time-series prediction using classical (type-1) fuzzy sets are available in the literature. However, type-1 fuzzy sets cannot fully capture the uncertainty involved in prediction because of its limited representation capability. This paper fills the void. Here, we propose four chronologically improved methods of time-series prediction using interval type-2...
The paper incorporates new extensional strategies into the traditional multi-objective optimization algorithms to proficiently obtain the Pareto-optimal solutions in the presence of noise in the fitness landscapes. The first strategy, referred to as adaptive selection of sample size, is employed to assess the trade-off between accuracy in fitness estimation and the associated run-time complexity....
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