Comparison semantic similarity approach using biomedical domain dataset
Power Plant Heat exchanger is widely used in chemical and petroleum plants because it can sustain wide range of temperature and pressure. Heat exchanger is a high nonlinearity and poor dynamics plant; therefore it is complex to model and difficult to control its dynamics. In this paper two types of...
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my.uthm.eprints.36412021-11-21T04:29:06Z http://eprints.uthm.edu.my/3641/ Comparison semantic similarity approach using biomedical domain dataset Kasim, Shahreen Omar, Nurul Aswa Mohammad Akbar, Nurul Suhaida Hassan, Rohayanti A. Jabar, Marzanah QA76 Computer software Power Plant Heat exchanger is widely used in chemical and petroleum plants because it can sustain wide range of temperature and pressure. Heat exchanger is a high nonlinearity and poor dynamics plant; therefore it is complex to model and difficult to control its dynamics. In this paper two types of heat exchanger model and controller are applied for selecting suitable model and controller. First model is called (Physical model) and derived using real parameter of heat exchanger plant. Second, a Second Order Plus Dead Time (SOPDT model) that is derived from the response of heat exchanger. While the controllers are consisted of fuzzy proportional derivative (FPD) controller and proportional integral derivative (PID) controller and applied to the model and their responses are compared with the existing PID controller. The PID controller response based on Physical model gives similar response of existing PID controller based real heat exchanger plant in comparison with SOPDT model. That means the Physical model is able to represent the heat exchanger plant dynamics more accurately than SOPDT model. For the controller, the FPD control gives a slight enhancement based on SOPDT model. Therefore, FPD controller is more suitable than PID controller. Razi Publishing 2017 Article PeerReviewed text en http://eprints.uthm.edu.my/3641/1/AJ%202017%20%28510%29.pdf Kasim, Shahreen and Omar, Nurul Aswa and Mohammad Akbar, Nurul Suhaida and Hassan, Rohayanti and A. Jabar, Marzanah (2017) Comparison semantic similarity approach using biomedical domain dataset. Acta Electronica Malaysia (AEM), 1 (2). pp. 1-4. ISSN 25904043 https://dx.doi.org/10.26480/aem.02.2017.01.04 |
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QA76 Computer software Kasim, Shahreen Omar, Nurul Aswa Mohammad Akbar, Nurul Suhaida Hassan, Rohayanti A. Jabar, Marzanah Comparison semantic similarity approach using biomedical domain dataset |
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Power Plant Heat exchanger is widely used in chemical and petroleum plants because it can sustain wide range of temperature and pressure. Heat exchanger is a high nonlinearity and poor dynamics plant; therefore it is complex to model and difficult to control its dynamics. In this paper two types of heat exchanger model and controller are applied for selecting suitable model and controller. First model is called (Physical model) and derived using real parameter of heat exchanger plant. Second, a Second Order Plus Dead Time (SOPDT model) that is derived from the response of heat exchanger. While the controllers are consisted of fuzzy proportional derivative (FPD) controller and proportional integral derivative (PID) controller and applied to the model and their responses are compared with the existing PID controller. The PID controller response based on Physical model gives similar response of existing PID controller based real heat exchanger plant in comparison with SOPDT model. That means the Physical model is able to represent the heat exchanger plant dynamics more accurately than SOPDT model. For the controller, the FPD control gives a slight enhancement based on SOPDT model. Therefore, FPD controller is more suitable than PID controller. |
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Article |
author |
Kasim, Shahreen Omar, Nurul Aswa Mohammad Akbar, Nurul Suhaida Hassan, Rohayanti A. Jabar, Marzanah |
author_facet |
Kasim, Shahreen Omar, Nurul Aswa Mohammad Akbar, Nurul Suhaida Hassan, Rohayanti A. Jabar, Marzanah |
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Kasim, Shahreen |
title |
Comparison semantic similarity approach using biomedical domain dataset |
title_short |
Comparison semantic similarity approach using biomedical domain dataset |
title_full |
Comparison semantic similarity approach using biomedical domain dataset |
title_fullStr |
Comparison semantic similarity approach using biomedical domain dataset |
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Comparison semantic similarity approach using biomedical domain dataset |
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comparison semantic similarity approach using biomedical domain dataset |
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Razi Publishing |
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2017 |
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http://eprints.uthm.edu.my/3641/1/AJ%202017%20%28510%29.pdf http://eprints.uthm.edu.my/3641/ https://dx.doi.org/10.26480/aem.02.2017.01.04 |
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