11 hasil
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IEEE/CAA Journal of Automatica Sinica
Scopus
ISSN 2329-9266 · Institute of Electrical and Electronics Engineers · 11 artikel di indeks
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Artikel Jurnal Teks lengkap
Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical applications span from computational fluid dynamics (CFD) to geoscience and climate systems. Recently, much effort has…
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Unmanned Aerial Vehicles: Control Methods and Future Challenges
With the rapid development of computer technology, automatic control technology and communication technology, research on unmanned aerial vehicles (UAVs) has attracted extensive attention from all over the world during the last decades. Particularly due to the demand of various civil applications…
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A Survey on Negative Transfer
Transfer learning (TL) utilizes data or knowledge from one or more source domains to facilitate learning in a target domain. It is particularly useful when the target domain has very few or no labeled data, due to annotation expense, privacy concerns, etc. Unfortunately, the effectiveness of TL is…
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Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey
With the booming of cyber attacks and cyber criminals against cyber-physical systems (CPSs), detecting these attacks remains challenging. It might be the worst of times, but it might be the best of times because of opportunities brought by machine learning (ML), in particular deep learning (DL). In…
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Artikel Jurnal
Deep Learning for EMG-based Human-Machine Interaction: A Review
Electromyography (EMG) has already been broadly used in human-machine interaction (HMI) applications. Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution. Recently, many EMG pattern recognition tasks have been…
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A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trends
Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is increasing popularity in resolving different optimization problems and has been widely utilized in various applications. In the past decades, numerous swarm intelligence algorithms have been developed…
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Deep learning and time series-to-image encoding for financial forecasting
In the last decade, market financial forecasting has attracted high interests amongst the researchers in pattern recognition. Usually, the data used for analysing the market, and then gamble on its future trend, are provided as time series; this aspect, along with the high fluctuation of this kind…
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A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges
With the deep combination of both modern information technology and traditional agriculture, the era of agriculture 4.0, which takes the form of smart agriculture, has come. Smart agriculture provides solutions for agricultural intelligence and automation. However, information security issues…
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AI-based modeling and data-driven evaluation for smart manufacturing processes
Smart manufacturing refers to optimization techniques that are implemented in production operations by utilizing advanced analytics approaches. With the widespread increase in deploying industrial internet of things ( IIOT ) sensors in manufacturing processes, there is a progressive need for…
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Automatic detection of COVID-19 infection using chest X-ray images through transfer learning
The new coronavirus ( COVID-19 ) , declared by the World Health Organization as a pandemic, has infected more than 1 million people and killed more than 50 thousand. An infection caused by COVID-19 can develop into pneumonia, which can be detected by a chest X-ray exam and should be treated…
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Artikel Jurnal Teks lengkap
BAS-ADAM: an ADAM based approach to improve the performance of beetle antennae search optimizer
In this paper, we propose enhancements to Beetle Antennae search ( BAS ) algorithm, called BAS-ADAM, to smoothen the convergence behavior and avoid trapping in local-minima for a highly non-convex objective function. We achieve this by adaptively adjusting the step-size in each iteration using the…