Decreasing wind speed extrapolation error via domain-specific feature extraction and selection
نویسندگان
چکیده
منابع مشابه
Forecasting of Wind Speed Using Feature Selection and Neural Networks
Wind energy is rapidly increasing and it is becoming a significant contributor to the electricity grid. Wind speed is an important factor in wind power production and integration. This paper presents a wind speed forecasting using feature selection method and bagging neural network. Feature selection plays an essential role in the machine learning environment and especially in the prediction ta...
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In this paper, a missing wind speed data temporal interpolation and extrapolation method in the wind energy industry was investigated. Given that traditional methods have previously ignored part of mixed uncertainty of wind speed, a concrete granular computing method is constructed and a new Measure–Correlate–Predict (MCP) method of wind speed data temporal interpolation and extrapolation consi...
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Feature extraction and feature selection are two important tasks in pattern recognition. Classiication algorithms like k-nearest neighbors, which are based on the assumption that patterns in the same class are close to each other and those in diierent classes are far apart (locality property), rely heavily on the quality of the features extracted from the input data. In this work, an objective ...
متن کاملFeature Selection Extraction and Construction
Feature selection is a process that chooses a subset of features from the original features so that the fea ture space is optimally reduced according to a certain criterion Feature extraction construction is a process through which a set of new features is created They are used either in isolation or in combination All attempt to improve performance such as estimated ac curacy visualization and...
متن کاملMinimum Bayes error feature selection
We consider the problem of designing a linear transformation 2 IR , of rank p n, which projects the features of a classi er x 2 IR onto y = x 2 IR such as to achieve minimum Bayes error (or probability of misclassi cation). Two avenues will be explored: the rst is to maximize the -average divergence between the class densities and the second is to minimize the union Bhattacharyya bound in the r...
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ژورنال
عنوان ژورنال: Wind Energy Science
سال: 2020
ISSN: 2366-7451
DOI: 10.5194/wes-5-959-2020