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In this paper, a new prediction approach is proposed for ocean vessel heave compensation based on echo state network (ESN). To improve the prediction accuracy and enhance the robustness against noise and outliers, a generalized similarity measure called correntropy is introduced into ESN training, which is referred as corr-ESN. An iterative method based on half-quadratic minimization is derived to train corr-ESN. The proposed corr-ESN is used for the heave motion prediction. The experimental results verify its effectiveness.
This article was published in the following journal.
Name: PloS one
In this paper, a new prediction and identification method based on adaptive echo state network (AESN) is proposed to identify a class of discrete-time dynamic nonlinear systems (DDNS). Firstly, accord...
Cortical neural connectivity has been shown to exhibit a small-world (SW) network topology. However, the role of the topology in neural information processing remains unclear. In this study, we invest...
Like most machine learning algorithms, Echo State Networks possess several hyperparameters that have to be carefully tuned for achieving best performance. For minimizing the error on a specific task, ...
Computational drug target prediction has become an important process in drug discovery. Network-based approaches are commonly used in computational drug-target interactions (DTIs) predictions. Existin...
Echo state networks (ESNs) are randomly connected recurrent neural networks (RNNs) that can be used as a temporal kernel for modeling time series data, and have been successfully applied on time serie...
Workplace wellness programs have become a $6 billion industry and are widely touted as a way to improve employee well-being, reduce health care costs by promoting prevention, and increase ...
Resting state functional MRI is widely used for studying brain functional networks. However, in-scanner head movement and other non-neuronal noise can disproportionately bias connectivity ...
The purpose of this study is to compare C&P examination reports performed using a Compensation and Pension Examination Program (CPEP) computerized, templated documentation tool to a custom...
Computer-aided diagnostic software has been used to assist physicians in various ways. Text-based prediction algorithms have been trained on past medical records through data mining and fe...
The effect of cardiac pacing leads on tricuspid regurgitation is unclear. This study will determine whether using a smaller diameter leads and an alternate position in the ventricle, the p...
A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations.
The prediction or projection of the nature of future problems or existing conditions based upon the extrapolation or interpretation of existing scientific data or by the application of scientific methodology.
Predicting the time of OVULATION can be achieved by measuring the preovulatory elevation of ESTRADIOL; LUTEINIZING HORMONE or other hormones in BLOOD or URINE. Accuracy of ovulation prediction depends on the completeness of the hormone profiles, and the ability to determine the preovulatory LH peak.
Usually refers to the use of mathematical models in the prediction of learning to perform tasks based on the theory of probability applied to responses; it may also refer to the frequency of occurrence of the responses observed in the particular study.
A quantitative prediction of the biological, ecotoxicological or pharmaceutical activity of a molecule. It is based upon structure and activity information gathered from a series of similar compounds.