Predicting Wind Turbine Blade Fault Condition to Enhance Wind Energy Harvest Through Classification via Regression Classifier

Joshuva, A.; Arjun, M.; Murugavel, R.; Shridhar, Vijay; Gangadhar, G. S. Sriram; Dhanush, S. S.

doi:10.1007/978-981-15-7245-6_2

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…Decision tree algorithms create a sequence of rules to increase knowledge gain, enabling classifying data from a model composed of branches and leaves (Eti & İnel, 2019). For this technique, there are some models, such as ID3, C4.5, and J48, which is an evolution of the latter (Joshuva et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

“…The ROC curve or area demonstrates the relationship between the sensitivity (VP rate) and specificity (FP rate) of the classifier; the higher the value, the better the curve is fitted (Gadotti et al, 2022a). However, the J48 classifier aims to generate a decision tree based on labeled data, involving qualitative variables, and it is the best algorithm to use this technique (Joshuva et al, 2020). To induce a decision tree, it divides a complex problem into simpler ones, applying the same strategy again until getting to a final solution (Costa et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

“…A CVR classifier uses regression methods to create a binary class by generating a regression model for each class value (Joshuva et al, 2020). Figure 2 presents the decision tree for the J48 algorithm using the 66%-and 10-fold techniques.…”

Section: Resultsmentioning

confidence: 99%

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FITTING Data Mining Settings for Ranking Seed Lots

et al. 2023

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To enhance speed and agility in interpreting physiological quality tests of seeds, The use of algorithms has emerged. This study aimed to identify suitable machine learning models to assist in the precise management of seed lot quality. Soybean lots from two companies were assessed using the Supplied Test Set, Cross-Validation (with 8, 10, and 12 folds), and Percentage Split (with 66% and 70%) methods. Variables analyzed through Tetrazolium tests included vigor, viability, mechanical damage, moisture damage, bed bug damage, and water content. Method performance was determined by Kappa, Precision, and ROC Area metrics. Classification Via Regression and J48 algorithms were employed. The technique utilizing 66% of data for training achieved 93.55% accuracy, with Precision and ROC Area reaching 94.50% for the J48 algorithm. Applying the crossvalidation method with 10 folds resulted in 90.22% of correctly classified instances, with a ROC Area outcome like the previous method. Tetrazolium Vigor was the primary attribute used. However, these results are specific to this study's database, and careful planning is necessary to select the most effective application methods.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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FITTING Data Mining Settings for Ranking Seed Lots

et al. 2023

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“…The process of identifying the operation at optimal level in an induction machine using Lab VIEW [1] developed virtually off-grid. Evaluation of induction generator on optimal results is partly achieved using EMTP -ATP [2]. The model for generators can be used for examine and estimate the control strategies using simulation for variable speed [3].The mathematical model assumed that a wind turbine and the rotor also solved the problem to obtain the optimal design for a small-scale turbine the can be formulated in terms of the pitch angle and working mode [4].…”

Section: Introductionmentioning

confidence: 99%

Implementating the optimal operation point of Induction Generator using LabVIEW

Marshiana¹,

Geetha²,

Krishnamoorthy³

et al. 2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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Wind system permits adjustable operation for numerous wind generators which are parallel coupled for the production of power by dispensing with the necessity of voltage requirement. The operational operating point is observed for the induction generator for the production of power. A model prescient control calculation was developed to check the capacity of the power generated in the micro grid. This offers an enhanced transient response regarding the development and control of the working conditions of inverters. The analysis of the system is made by measuring the speed of the windmill and the outcomes are obtained using LabVIEW.

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