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Expert Systems with Applications
Scopus
ISSN 0957-4174 · Elsevier BV · 42 articles in the index
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Physics-informed machine learning: A comprehensive review on applications in anomaly detection and condition monitoring
Condition monitoring plays a vital role in ensuring the reliability and optimal performance of various engineering systems. Traditional methods for condition monitoring rely on physics-based models and statistical analysis techniques. However, these approaches often face challenges in dealing with…
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A comparison review of transfer learning and self-supervised learning: Definitions, applications, advantages and limitations
Deep learning has emerged as a powerful tool in various domains, revolutionising machine learning research. However, one persistent challenge is the scarcity of labelled training data, which hampers the performance and generalisation of deep learning models. To address this limitation, researchers…
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Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm
The stock market is a financial market where shares of publicly listed corporations are purchased and sold. It is an indicator of a country's economic health, reflecting the performance of companies and the overall business environment. The prices of stocks are determined by supply and demand…
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A review on sentiment analysis from social media platforms
Sentiment analysis has proven to be a valuable tool to gauge public opinion in different disciplines. It has been successfully employed in financial market prediction, health issues, customer analytics, commercial valuation assessment, brand marketing, politics, crime prediction, and emergency…
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Condition Monitoring using Machine Learning: A Review of Theory, Applications, and Recent Advances
In modern industry, the quality of maintenance directly influences equipment’s operational uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive maintenance can minimize machine downtime and potential losses. Throughout the field, machine learning (ML) methods…
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Path planning techniques for mobile robots: Review and prospect
Mobile robot path planning refers to the design of the safely collision-free path with shortest distance and least time-consuming from the starting point to the end point by a mobile robot autonomously. In this paper, a systematic review of mobile robot path planning techniques is presented…
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A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations belonging to one class is lower than the other. Ensemble learning combines multiple models to obtain a robust model and has been prominently used with data augmentation methods to address class imbalance…
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Robust clinical applicable CNN and U-Net based algorithm for MRI classification and segmentation for brain tumor
Early diagnosis of brain tumors is critical for enhancing patient prognosis and treatment options, while accurate classification and segmentation of brain tumors are vital for developing personalized treatment strategies. Despite the widespread use of Magnetic Resonance Imaging (MRI) for brain…
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Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach
The Internet of Things (IoT) is currently seeing tremendous growth due to new technologies and big data . Research in the field of IoT security is an emerging topic. IoT networks are becoming more vulnerable to new assaults as a result of the growth in devices and the production of massive data. In…
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Generalized MAML for few-shot cross-domain fault diagnosis of bearing driven by heterogeneous signals
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A survey of state-of-the-art on visual SLAM
This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We discuss the basic definitions in the SLAM and vision system fields and provide a review of the state-of-the-art methods utilized for mobile robot’s vision and SLAM. This paper covers topics from the basic SLAM…
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A multi-head attention-based transformer model for traffic flow forecasting with a comparative analysis to recurrent neural networks
Traffic flow forecasting is an essential component of an intelligent transportation system to mitigate congestion. Recurrent neural networks, particularly gated recurrent units and long short-term memory, have been the state-of-the-art traffic flow forecasting models for the last few years…
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Machine learning techniques and data for stock market forecasting: A literature review
In this literature review, we investigate machine learning techniques that are applied for stock market prediction. A focus area in this literature review is the stock markets investigated in the literature as well as the types of variables used as input in the machine learning techniques used for…
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Remote sensing image super-resolution and object detection: Benchmark and state of the art
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Covid-19 vaccine hesitancy: Text mining, sentiment analysis and machine learning on COVID-19 vaccination Twitter dataset
In 2019 there was an outbreak of coronavirus pandemic also known as COVID-19. Many scientists believe that the pandemic originated from Wuhan, China, before spreading to other parts of the globe. To reduce the spread of the disease, decision makers encouraged measures such as hand washing, face…