Today the persistence of plant and plant diseases is a substantial problem for cultivators, disease diagnosis is important in the farm. To preserve the production of crops, adequate consideration is a must. To isolate...
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The Integrated Internet MANET (IIM) by means of the aid of the hub the mobile ad hoc network's operating system produces, allowing communication between mobile and fixed nodes. Because of the wireless channel and ...
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In order to ensure the safety and manufacturing efficiency of pharmaceuticals, rigorous quality control measures are necessary. However, existing quality control systems often struggle with industrial process complexi...
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Alzheimer's disease (AD), is the most common form of dementia that affects the nervous system. In the past few years, non-invasive early AD diagnosis has become more popular as a way to improve patient care and tr...
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The Infant Mortality Rate (IMR) is a significant measure used to evaluate the health and socioeconomic status of developing nations, particularly Bangladesh. It is important to carefully examine the various risk facto...
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Feature selection is a major pre-processing stage in machine learning to identify the optimal features through diminishing the redundant features to enhance the classification accuracy. The swarm intelligence algorith...
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Lung cancer is generally caused by an abnormal expansion of cells in the lungs of people due to mutation. In the lungs, the smallest unit of cell growth is named lung nodules that vary from 5 to 25 mm in diameter...
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The concept of smart grids was released a long time ago, and since then the development in clever grids have changed our conventional energy machine with new advanced features like real-time monitoring power distribut...
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Sharing students’ credentials is an essential process for any educational ecosystem that includes diverse stakeholders such as students, teachers, various committees of institutes, administrations, government agencie...
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Modern power systems are incorporated with distributed energy sources to be environmental-friendly and ***,due to the uncertainties of the system integrated with renewable energy sources,effective strategies need to b...
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Modern power systems are incorporated with distributed energy sources to be environmental-friendly and ***,due to the uncertainties of the system integrated with renewable energy sources,effective strategies need to be adopted to stabilize the entire power ***,the system operators need accurate prediction tools to forecast the dynamic system states *** this paper,we propose a Bayesian deep learning approach to predict the dynamic system state in a general power ***,the input system dataset with multiple system features requires the data pre-processing ***,we obtain the dynamic state matrix of a general power system through the Newton-Raphson power flow ***,by incorporating the state matrix with the system features,we propose a Bayesian long short-term memory(BLSTM)network to predict the dynamic system state variables *** results show that the accurate prediction can be achieved at different scales of power systems through the proposed Bayesian deep learning approach.
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