Recently, the one-class extreme learning machine (OC-ELM) has been developed for learning acceleration and performance enhancement. But existing one-class algorithms are generally less effective in complex and
The Extreme Learning Machine is a single-hidden-layer feedforward learning algorithm, which has been successfully applied in regression and classification
Optical approaches have made great strides towards the goal of high-speed, energy-efficient computing necessary for modern deep learning and AI applications. Read-in and read-out of data, however, limit the overall performance of existing approaches. Thi
Hierarchical extreme learning machine framework In network structure of H-ELM, the original input is decomposed into multiple hidden layers. The output of the previous layer is regarded as the input of the current one. The learning of hidden layer represents more abstract information. By doing so,...
i.e. the one with maximum firing degree, determines the output class. If no rules are fired for a given data instance, then FURIA applies the so-called rule-stretching mechanism, which looks for slight modifications in the rule base with the aim of finding a new rule on-the-fly that is...
Financial applications of machine learning: A literature review 2023, Expert Systems with Applications Forecasting movements of stock time series based on hidden state guided deep learning approach 2023, Information Processing and Management Soft computing in business: exploring current research and outlining...
[5], this framework, which is the latest and one of the most popular techniques of deep learning, is proposed for STLF for individual residential households, • stacked denoising autoencoders—in [6] this model, a class of deep neural networks and its extended version are utilized to ...
The first type is long-term load forecasting (LTLF)[5], which is used to predict the load during a year or over more than one year, which is very important in economic operations involving the power system. The second type is mid-term load forecasting (MTLF)[6], which is used to ...
i.e., two layers with hidden units and one layer with output units. Keyword: universal approximator [Kolmogorov Theorem, 1957] K Multilayer perceptrons are also called multilayer networks or (artificial) neural networks, ANN for short. ...
Comparison between epileptic seizure prediction and forecasting based on machine learning Article Open access 07 March 2024 EEG epilepsy seizure prediction: the post-processing stage as a chronology Article Open access 03 January 2024 Engineering nonlinear epileptic biomarkers using deep learning and ...