End-Effector Position Estimation and Control of a Flexible Interconnected Industrial Manipulator Using Machine Learning

Adel, M.; Ahmed, Sabah M.; Fanni, Mohamed

doi:10.1109/access.2022.3157817

Cited by 5 publications

(2 citation statements)

References 37 publications

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“…On the other hand, the introduction of EGR eliminates the over injection area and reduces the particulate matter produced in the anoxic combustion environment. A large amount of carbon dioxide in EGR gas can also reduce the generation of soot [13][14].…”

Section: Exhaust Gas Recirculation Technologymentioning

confidence: 99%

Diesel Engine Exhaust Gas Recirculation Technology Based on Machine Learning

2021

KME

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Recycling technology has the characteristics of high efficiency, recyclability and reuse. At the same time, it can be widely used in industrial production as an environment-friendly technology. At present, the waste gas treatment methods adopted in China mainly include mechanical (heat treatment) or chemical methods. These methods do great harm to the environment. In order to improve the environmental protection of diesel engines, this paper intends to study the application of machine learning in exhaust gas recirculation technology, and propose the method of exhaust gas recirculation technology. This paper mainly uses the experimental method of EGR scheme design and changes the variables to compare the data difference to realize the research on the influence of internal EGR on emission performance and combustion characteristics. The experimental results show that the NOx emissions of the internal EGR scheme are lower than 10/g•h-1 at 2200r/min and 10% load conditions. The internal exhaust gas recirculation technology has great potential to improve the harmful exhaust gas and total fuel emissions of diesel engines.

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Section: Exhaust Gas Recirculation Technologymentioning

confidence: 99%

Diesel Engine Exhaust Gas Recirculation Technology Based on Machine Learning

2021

KME

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“…In this stage, the most common one is the artificial neural network, which is also used in the artificial neural network model. Because it can be applied to other disciplines and multiple fields in a very large range, it is widely used in the diagnosis and treatment of many diseases [13][14]. Figure 1 In this study, machine learning is a very important method, which can help children to carry out correct, efficient and rapid treatment.…”

Section: Machine Learningmentioning

confidence: 99%

Machine Learning in the Recognition and Prognosis Prediction of Children's Post-traumatic Stress Disorder

2020

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With the development of society, diseases have also become a topic of concern, and children's post-traumatic stress disorder has attracted more attention. This paper mainly analyzes the current situation of research on nerve protection and human brain injury at home and abroad, and designs a protection system based on machine learning model in combination with the algorithm used in this topic. First, it introduces some related concepts and theoretical foundations of this model, and studies its application in the recognition of children's post-traumatic stress disorder and prognosis prediction. Secondly, the characteristics and advantages of recognition of children's post-traumatic stress defects, problems in use; evaluation difficulties and other aspects are obtained through experimental analysis. Finally, a sample test based on training classification diagram is proposed to solve these problems with Bayesian algorithm, and the results are compared to verify its accuracy. The verification results show that the recognition rate of children's post-traumatic stress disorder in this model is very high. The prediction time and recognition time of stress disorder are very fast, which meets the recognition needs of users.

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