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Multi-moth flame optimization for solving the link prediction problem in complex networks
(
Springer Verlag
, 2019 , Article)
Providing a solution for the link prediction problem attracts several computer science fields and becomes a popular challenge in researches. This challenge is presented by introducing several approaches keen to provide the ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...
Arrhythmia classification using DWT-coefficient energy ratios
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Certain features present in electrocardiogram (ECG) signals are used to detect different heart conditions. Hence, by developing a system to extract these features, useful information related to the heart conditions could ...
Robust detection of acoustic partial discharge signals in noisy environments
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Partial discharge (PD) can be used to predict insulation failures in power transformers. Accurate detection of particular PD types has a significant role in anticipating forthcoming outages. However, the noise encountered ...
Robust Feature Extraction and Classification of Acoustic Partial Discharge Signals Corrupted With Noise
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Article)
Partial discharge (PD) can be used as an indicator of impending failure in electrical plant insulation making the accurate classification of particular occurrence patterns useful for anticipating forthcoming outages. In ...
Handcrafted features with convolutional neural networks for detection of tumor cells in histology images
(
IEEE Computer Society
, 2016 , Conference Paper)
Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional ...
Short-term probabilistic building load forecasting based on feature integrated artificial intelligent approach
(
Elsevier Ltd
, 2022 , Article)
Due to various influential factors that lead to instability and volatility of the building load, short-term building load forecasting is a gruelling task. This paper proposes a hybrid short-term building load probability ...
Application of data-driven attack detection framework for secure operation in smart buildings
(
Elsevier Ltd
, 2021 , Article)
With the rapid advancement in the industrial control technologies and the increased deployment of the industrial Internet of Things (IoT) in the buildings sector, this work presents an analysis of the security of the ...
Hybrid attack detection framework for industrial control systems using 1D-convolutional neural network and isolation forest
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Industrial control systems (ICSs) are used in various infrastructures and industrial plants for realizing their control operation and ensuring their safety. Concerns about the cybersecurity of industrial control systems ...
Design and analysis of an adaptive compressive sensing architecture for epileptic seizure detection
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as a representative signal carrying valuable information pertaining to the current brain state. In this work, we investigate the stability of ...