Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems...
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This article integrates the widely recognised ensemble filters that are employed for power system state estimation and their ensemble scenarios to controls for power systems linearised on manifolds. The approach has t...
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ISBN:
(数字)9798350354508
ISBN:
(纸本)9798350354515
This article integrates the widely recognised ensemble filters that are employed for power system state estimation and their ensemble scenarios to controls for power systems linearised on manifolds. The approach has the effect of directly providing constraint scenarios for any optimal real-time fast power system management for any ensemble-based state estimator used in the power system, thereby reducing the computational task for both radial and meshed power systems and addressing the computational needs of stochastic external state parameter that is not controlled by the grid operator. New and unparalleled obstacles have surfaced in the recent past for power systems. Tighter guidelines for grid reliability and service quality, the growing spread of electric mobility that has given rise to a new class of intermittent loads with distinct spatiotemporal patterns, and the growing use of distributed microgenerators from renewable power sources-which are frequently characterised by unpredictable behavior-are some of these challenges. For proof of concept, the method is shown on a simple example.
Droplet formation happens in finite time due to the surface tension force. The linear stability analysis is useful to estimate droplet size but fails to approximate droplet shape. This is due to a highly non-linear fl...
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The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable e...
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The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable energy such as wind *** this study,a mesoscale approach is adopted whereby the wind farm location is investigated in comparison with a microscale approach where the location of each individual turbine is *** study focuses on the placement of a wind farm by economical optimization constrained by the power system,wind resources,and *** optimization is introduced in this context at the power system which is constrained by wind farm planning.
Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems...
Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems of identification of patterns can be solved with ease and accuracy when proper machine learning model is implemented. This paper uses EHR data to build an end-to-end machine learning pipeline for predicting the outcome of emergency care patients. As a machine learning process, the pipeline includes data preprocessing, feature engineering, model selection, data set training and testing, evaluation, and deployment. By using EHR data in this pipeline, the model has been trained and tested on a large dataset of many patients information with different types of machine learning algorithms to improve and get the best prediction accuracy. This pipeline can aid in managing primary care patients efficiently and effectively with the implementation of best suitable machine learning algorithm at the time of urgency. By implementing the model on the EHR dataset, an accuracy of more than $75 \%$ is obtained which indicates the efficiency of the machine learning process in the process of identifying patients who need the emergency care more than the general patients when taken to the primary care or emergency.
The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering f...
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The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering for reliable, resilient and robust power systems. The power system is a global sensitivity problem since each input uncertainty varies the output and all the variables simultaneously that have higher order interactions between inputs, unlike local sensitivity. The article assesses and compares the global sensitivity methods of Sobol’ sensitivity indices, the activity scores of the active subspace method, and Shapley values, to assess the importance of input parameters in the IEEE 14-bus modified test system. The limitations and advantages of each approach are illustrated to reduce the complexity of the model by performing uncertainty quantification for the output by global sensitivity indices in the IEEE 14-bus modified test system.
Population structure has been known to substantially affect evolutionary dynamics. Networks that promote the spreading of fitter mutants are called amplifiers of selection, and those that suppress the spreading of fit...
Trusting others and reciprocating the received trust with trustworthy actions are fundaments of economic and social interactions. The trust game (TG) is widely used for studying trust and trustworthiness and entails a...
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Understanding the dynamics of financial transactions among people is critically important for various applications such as fraud detection. One important aspect of financial transaction networks is temporality. The or...
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Manga, Japanese comics, has been popular on a global scale. Social networks among characters, which are often called character networks, may be a significant contributor to their popularity. We collected data from 162...
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