Fuzzy-Based Energy Management System With Decision Tree Algorithm for Power Security System

Ramya, K.; Teekaraman, Yuvaraja; Kumar, K. Yogesh

doi:10.2991/ijcis.d.191016.001

Cited by 89 publications

(12 citation statements)

References 6 publications

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“…Energy performance refers to the operating efficiency and economy of the energy system. In energy management, common methods for evaluating energy performance include energy efficiency index, energy cost index, energy use density index and energy renewable utilization index (Ramya et al, 2019). Among them, the energy efficiency indicator is an indicator to measure the operational efficiency of the energy system.…”

Section: Evaluation Of Energy Performancementioning

confidence: 99%

Path analysis of energy economic management standardization in the context of carbon neutralization and carbon peak

Liu

2023

Front. Ecol. Evol.

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Carbon neutrality and carbon peak are two important measures to control climate change. They have a huge impact on many companies in the fields of energy, industry, construction, transportation, etc. They can change the development pattern of related industries and increase many new investment and development opportunities. This paper proposes a path analysis of the standardization of energy economic management under the background of carbon neutrality and carbon peak, aiming to study the development forecast of energy economic management under low-carbon conditions. The algorithm proposed in this paper is an energy consumption analysis algorithm based on the IPAT model, which can be combined with the IPAT model to analyze and process energy consumption data. In addition, by analyzing and evaluating the contribution of various factors, people can better understand the impact of energy consumption on the environment and formulate corresponding solutions. The experimental analysis results of energy economic management based on carbon neutrality and carbon peak show that, from 2013 to 2017, under the baseline scenario, carbon emissions increased year by year, from 9.25 billion tons to 10.48 billion tons. Under the carbon neutral scenario, its carbon emissions are 9.22 billion tons, 9.24 billion tons, 9.22 billion tons, 9.19 billion tons and 9.21 billion tons respectively. Obviously, under the carbon neutral scenario, carbon emissions can be better controlled through carbon neutral and carbon peak strategies. Through these experimental prediction results, it can be proved that carbon neutrality and carbon peaking have excellent effects on promoting energy economic management. At the same time, this study also provides valuable reference information for further research on carbon neutrality and carbon peaks.

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Section: Evaluation Of Energy Performancementioning

confidence: 99%

Path analysis of energy economic management standardization in the context of carbon neutralization and carbon peak

Liu

2023

Front. Ecol. Evol.

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“…Carneiro et al [6] used touch screen interactions to identify stress. The J48 decision tree classifier [7] can distinguish between the touches (i.e. stressed and non-stressed) with 78% accuracy via touch patterns.…”

Section: Related Workmentioning

confidence: 99%

Multimodal Machine Learning Framework to Detect the Bipolar Disorder

Sivagnanam¹,

Visalakshi²

2022

Advances in Parallel Computing Algorithms, Tools and Paradigms

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The current approaches for diagnosing mental disorders rely heavily on self-reported and clinical interview ratings. The development of an automatic recognition system assists in the early detection and discovery of biological markers for diagnostic purposes. In this paper, develops a multimodal machine learning model, where it processes multiple modalities like visual, acoustic and textual features using a cross-modality correlation. The study uses a Denoising Autoencoder that finds the multimodal representations and then it adopts Fisher Vector encoding to form session-level descriptors. Paragraph Vector (PV) are used for textual modality that embeds the interview sessions transcripts into document representations that tends to capture the mental disorder cues. Finally, the textual and audio-visual features are fused before training the 3-layered denoising autoencoder (DAE) with Residual Neural Network classifier. The proposed model is validated using two bipolar disorders that includes depression and bipolar disorder. The study uses two different datasets including Extended Distress Analysis Interview Corpus (E-DAIC) and Bipolar Disorder Corpus (BDC) to analyse the depression and bipolar disorders. The experimental evaluation is conducted to show the performance improvement using the proposed multimodal model than other state-of-the art methods in detecting the depression and bipolar disorders. The results of simulation show that the proposed method obtains an improved detection rate than existing models.

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“…Decision tree is one of the commonly used algorithms in the field of data mining research. It has the advantages of high precision, high efficiency, fast calculation speed, and ability to process multiple types of data [1][2][3]. At present, the research on online education using decision tree mining algorithm mainly focuses on the evaluation of learning effect and the research of learning influencing factors.…”

Section: Related Workmentioning

confidence: 99%

“…In actual work, the relevant personnel can determine which method to use according to the situation. (5) Function of the achievement analysis system: (1) management function of the system. e management module of the system needs to be able to record the information of users.…”

Section: Features and Stages Of Decisionmentioning

confidence: 99%

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

Yang

2021

Complexity

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With the continuous development of “Internet + Education”, online learning has become a hot topic of concern. Decision tree is an important technique for solving classification problems from a set of random and unordered data sets. Decision tree is not only an effective method to generate classifier from data set, but also an active research field in data mining technology. The decision tree mining algorithm can classify the data, grasp the teaching process of the teacher, and analyze the overall performance of the students, so as to realize the dynamic management of the educational administration and help the educational administration personnel to make the right decision, with more reasonable allocation of resources. This paper evaluates students’ academic performance based on the learning behavior data of online learning, so as to intervene in students’ learning in advance, which is the key problem that needs to be solved at present. Taking students’ learning attitude, completion of homework, and attendance as factors, the paper uses decision tree technology to analyze the factors affecting students’ performance, and evaluates students’ performance. Firstly, this paper collects the high-dimensional behavioral characteristic data of students’ online learning and conducts correlation analysis after preprocessing the behavioral characteristic data. Then, the decision tree C4.5 algorithm is used to construct a performance evaluation model. Students’ performance is evaluated by the model, and the evaluation accuracy is about 88% compared with actual performance. Finally, through the model analysis, it is concluded that the video task point completion is the most influential in students’ achievement, followed by chapter test completion and chapter test average score, and the course interaction amount and homework average score are the least influential in students’ achievement, which has a practical reference value for effectively serving online learning and teachers’ teaching.

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Fuzzy-Based Energy Management System With Decision Tree Algorithm for Power Security System

Cited by 89 publications

References 6 publications

Path analysis of energy economic management standardization in the context of carbon neutralization and carbon peak

Path analysis of energy economic management standardization in the context of carbon neutralization and carbon peak

Multimodal Machine Learning Framework to Detect the Bipolar Disorder

The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm

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