Predicting financial activity with evolutionary fuzzy case-based reasoning

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

“…Based on comparison results, they reported that the proposed model can effectively improve the forecasting performance and outperforms other models. Other examples of this type of comparisons are done by [275][276][277][278]. Table 20 presents the brief results of these comparisons.…”

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis

“…Moreover, Lee and Wang's study used the Pima Indians Dataset, but we use real cases from Mansura University Hospitals in Egypt. [96] Diagnosis of liver disorder 85 Begum et al [97] Diagnosis of stress 80 Petrovic et al [88] Radiotherapy planning 84.72 Non-medical Li et al [98] Financial application 92.36 Arias-Aranda et al [99] Knowing the relationship between flexibility and operations strategy…”

Small sample-oriented case-based kernel predictive modeling and its economic forecasting applications under n-splits-k-times hold-out assessment

“…The results showed that the new algorithms of case representation and case retrieval outperformed classical ones. Meanwhile, Lin and Ho (2009) attempted to construct a hybrid CBR algorithm using GAs and fuzzy k nearest neighbor (kNN), to optimize feature weighting and compute case similarity, respectively. Meanwhile, Kim (2009) investigated the simultaneous use of GA in feature selection and feature weighting, and demonstrated that the hybrid optimization could improve the predictive performance of CBR.…”