AIMC Topic: Wavelet Analysis

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Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network.

Environmental science and pollution research international
Accurate wind speed forecasting (WSF) not only ensures stable power system operation but also contributes to enhancing the competitiveness of wind power companies in the market. In this paper, a hybrid prediction model based on secondary decompositio...

Resting-state electroencephalography based deep-learning for the detection of Parkinson's disease.

PloS one
Parkinson's disease (PD) is one of the most serious and challenging neurodegenerative disorders to diagnose. Clinical diagnosis on observing motor symptoms is the gold standard, yet by this point nerve cells are degenerated resulting in a lower effic...

A Method for Pipeline Leak Detection Based on Acoustic Imaging and Deep Learning.

Sensors (Basel, Switzerland)
This paper proposes a reliable technique for pipeline leak detection using acoustic emission signals. The acoustic emission signal of a pipeline contains leak-related information. However, the noise in the signal often obscures the leak-related infor...

Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...

A Bearing Fault Diagnosis Method Based on Wavelet Packet Transform and Convolutional Neural Network Optimized by Simulated Annealing Algorithm.

Sensors (Basel, Switzerland)
Bearings are widely used in various electrical and mechanical equipment. As their core components, failures often have serious consequences. At present, most parameter adjustment methods are still manual adjustments of parameters. This adjustment met...

Electrocardiogram Signal Classification in the Diagnosis of Heart Disease Based on RBF Neural Network.

Computational and mathematical methods in medicine
Heart disease is a common disease affecting human health. Electrocardiogram (ECG) classification is the most effective and direct method to detect heart disease, which is helpful to the diagnosis of most heart disease symptoms. At present, most ECG d...

Improving the leak detection efficiency in water distribution networks using noise loggers.

The Science of the total environment
Leak detection techniques are effective ways of controlling water leakage in real water distribution networks (WDNs). Nevertheless, developing detection techniques for real WDNs has received little attention compared to the detection models developed...

Application of artificial intelligence based on synchrosqueezed wavelet transform and improved deep extreme learning machine in water quality prediction.

Environmental science and pollution research international
Water quality prediction is the basis for the prevention and control of water pollution. In this paper, to address the problem of low prediction accuracy of existing empirical models due to the non-smoothness and nonlinearity of water quality series,...

Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques.

Journal of healthcare engineering
Radiology is a broad subject that needs more knowledge and understanding of medical science to identify tumors accurately. The need for a tumor detection program, thus, overcomes the lack of qualified radiologists. Using magnetic resonance imaging, b...

Overview on prediction, detection, and classification of atrial fibrillation using wavelets and AI on ECG.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common supraventricular cardiac arrhythmia, resulting in high mortality rates among affected patients. AF occurs as episodes coming from irregular excitations of the ventricles that affect the functionality of the...