A Trainsient Voltage Stability Evaluation Model Based on Morphological Similarity Distance Online Calculation

Song, Dafeng; Yang, Xuetao; Zheng, Li; Hanyang, Dai

doi:10.1109/scems48876.2020.9352380

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…e decision tree algorithm is an inductive learning algorithm that can deduce the specific representation of the decision tree and the classification rules from a set of data samples that are not regular [14].…”

Section: Structure Of Decisionmentioning

confidence: 99%

Interactive Teaching System for Remote Vocal Singing Based on Decision Tree Algorithm

Wang

Liu

2022

Mathematical Problems in Engineering

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As the global pandemic rapidly spreads, distance learning is emerging as a new method of instruction. Particularly, traditional courses that must be taught in-person, such as vocal singing instruction, require immediate adaptation to the COVID-19 and the new distance learning model. However, in the process of distance learning, it is frequently impossible to tailor and personalize instruction, particularly for vocal singing courses. Educational researchers are confronted with the pressing issue of how to extract useful and personalized patterns from a large volume of learner data in order to customize and individualize instruction. In this paper, we propose applying the decision tree method from data mining technology to a vocal singing education system by categorizing students according to the model. Once the characteristics of various learners have been stored in the corresponding user database, teachers can access timely information regarding the learners’ most recent learning situation. This can be used as the basis for differentiating instructional strategies for various learners. This allows the instructor to designate individualized teaching and learning strategies for each student.

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Section: Structure Of Decisionmentioning

confidence: 99%

Interactive Teaching System for Remote Vocal Singing Based on Decision Tree Algorithm

Wang

Liu

2022

Mathematical Problems in Engineering

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A Prosumer Power Prediction Method Based on Dynamic Segmented Curve Matching and Trend Feature Perception

Zhao

Guo

et al. 2023

Sustainability

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With the massive installation of distributed renewable energy (DRE) generation, many prosumers with the dual attributes of load and power supply have emerged. Different DRE permeability and the corresponding peak-valley timing characteristics have an impact on the power features of prosumers, so new models and methods are needed to reflect the new features brought about by these factors. This paper proposes a method for predicting the power of prosumers. In this method, dynamic segmented curve matching is applied to reduce the complexity of source–load coupling features and improve the effectiveness of the input features, and trend feature perception based on a temporal convolutional network (TCN) was applied to grasp the power trend of prosumers by predicting the multisegment trend indexes. The LST-Atten prediction model based on a temporal attention mechanism (TAM) and a long short-term memory (LSTM) network was applied to predict “day-ahead” power, which combines the trend indexes and similar curve sets as the input. Simulation results show that the proposed model has higher accuracy than individual models. Furthermore, the proposed model can maintain prediction stability under different renewable energy permeability scenarios.

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A Trainsient Voltage Stability Evaluation Model Based on Morphological Similarity Distance Online Calculation

Cited by 2 publications

References 7 publications

Interactive Teaching System for Remote Vocal Singing Based on Decision Tree Algorithm

Interactive Teaching System for Remote Vocal Singing Based on Decision Tree Algorithm

A Prosumer Power Prediction Method Based on Dynamic Segmented Curve Matching and Trend Feature Perception

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