The Receiver Operator Characteristic (ROC) test is often used to evaluate classification performance. However, it calls for special consideration when applied to the class-imbalanced data. The Precision-Recall Curve (...
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In this paper, based on the ACS dataset, the original data were firstly preprocessed by excluding abnormal data, classification and interpolation operations to obtain complete, effective, intuitive and concise data. S...
In this paper, based on the ACS dataset, the original data were firstly preprocessed by excluding abnormal data, classification and interpolation operations to obtain complete, effective, intuitive and concise data. Secondly, the correlation relationship model of hybrid genetic BP neural network was proposed, and the training accuracy reached 0.99994. Then, the unit step method was used to discretize each independent variable in the chemical reaction, and the network relationship after training using BP neural network was obtained by the control variable method, and the data of the dependent variable changed with them were derived separately, and the trend analysis of the dependent variable when the independent variable changed was obtained by the different independent variables on the dependent variable. The prediction error percentage of the nine sample data in the test set was 0.06% at maximum, and the error analysis results were good.
This article proposes a sector model early warning method based on ELM theory, with the background of big data processing cluster technology. A fault early warning model is established using naive Bayesian algorithm c...
This article proposes a sector model early warning method based on ELM theory, with the background of big data processing cluster technology. A fault early warning model is established using naive Bayesian algorithm combined with time series similarity fault matching. The model adopts collected data such as relevant electrical quantities, switching values, event sequence information, power grid topology, and data obtained from fault recording devices during line faults. The naive Bayesian algorithm is used to mine the occurrence index of potential fault occurrence factors (i.e. fault factors), and then combined with time series similarity fault matching to perform fault warning on the line.
In recent years, semantic segmentation has been continuously developing, but there are still problems such as incomplete image understanding, incomplete contextual information extraction, imbalanced data samples, and ...
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A Study of time series prediction of enterprise energy consumption using ARIMA model in this paper. The data from a coal washing plants from January 2011 to February 2013. Forecasting the power consumption of coal was...
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With the continuous development of artificial intelligence technology, the application of prediction technology in various fields is becoming increasingly widespread. Based on the methods of Principal Component Analys...
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In order to solve the problem that the effect of traditional neural network in fault data diagnosis of power system is not obvious, inspired by the application of deep learning image recognition, this paper combines i...
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The existing voice assistants, such as Apple Siri, Amazon Alexa, and Google Assistant, rely on complex Artificial Intelligence technology. People now connect with computers in different ways via virtual assistants, co...
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With the growth of the internet and other forms of communication, fake news has become an increasing prevalent problem within society. Due to the ease and speed at which one can spread false information, manual fact c...
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With the development of computer and network technology, it has brought great challenges to the efficient processing of the network. In particular, the number of CPU cores is increasing, which leads to the need for ef...
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