Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters

Hui, Xianfei; Sun, Baiqing; Jiang, Hui; Sengupta, Indranil

doi:10.1080/07362994.2022.2094960

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2023

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“…A proposed machine learning algorithm extracts feature from the discharge curve to estimate SOH and SOC. Hui et al 32) used fuzzy and machine learning to improve the classical BN-S algorithm to analyze price fluctuations in the stock exchange. Results show that the refined BN-S model is better than the classical BN-S model in terms of long-term dependence.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of SPV Power Plant Based On Real-Time Data

Laxmi Kant Sagar,

D Bhagwan Das

2023

Evergreen

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To guarantee maximum performance and reliability of solar plants, the probability of occurrence of improper operations should be very low. For that, a fault diagnosis expert system can be one of the solutions that can figure out the improper operations very precisely and suggest corrective actions. In this study, we will use a hybrid approach for fault detection, i.e., a knowledgebased and data-driven approach, i.e., fuzzy logic and machine learning. A fuzzy model will sense the real-time data and classify it into good or faulty. The fuzzy simulation model, thus, developed, will be used to generate a large amount of training data required for machine learning methods. Further clustering techniques are applied to the available database to determine which improper operation (fault) has the highest probability of occurrence.

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Section: Introductionmentioning

confidence: 99%