Environment Optimization Scheme Based on Edge Computing Using PSO for Efficient Thermal Comfort Control in Resident Space

Xu, Rongxu; Jin, Wenquan; Kim, Do‐Hyeun

doi:10.3390/act10090241

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…e population proportion in a fixed interval is given, and the interpolation method is also used to estimate the income distribution function of the rural residents. F N (x) � 􏽐 m i�1 c 2i x i and the inverse function F −1 N (p) � 􏽐 n i�1 y 2i p i of the income distribution function, are the polynomial form of the number of urban residents in 2018, as shown in Equation ( 4)- (1) and Equation ( 4)-( 2), a more intuitive expression is shown in Figures 8 and 9. As can be seen from Figures 8 and 9, the income distribution function in the polynomial form can estimate the income distribution function well and the estimation accuracy can be guaranteed, and its effect is far better than the type of the selected income distribution function [23].…”

Section: Interpolation Calculation: Urban and Rural Incomementioning

confidence: 98%

“…With the development of the economy, the development of various industries has an increasing demand for electric energy, which also makes the related technologies of the electric power industry develop rapidly. A stable and reliable power system is the key basis for the transmission and use of electrical energy, so the development of a stable power system is crucial to economic and social development [ 1 ]. The components of the power system involve many aspects, but the main ones can be divided into four parts, namely, users, power generation, power transmission, and power distribution.…”

Section: Introductionmentioning

confidence: 99%

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[Retracted] Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment

Zhao

Liu

2022

Journal of Environmental and Public Health

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In order to explore the current income gap, a method based on the PSO algorithm in the edge computing environment is proposed. PSO calculates and simulates bird flock foraging activities, the Frank Heppner biological group model, and the three rules in bird activities. After studying the activities of these natural creatures, abstract problems are quantified and similar models established. The Gini coefficient is calculated by using grouped data, and the grouping basis is also innovative. The quantile grouping method is adopted, which can effectively solve the difference between the concentration index and the Gini coefficient, and the Gini coefficients of each year can be added up to finally get the Gini coefficient of the stock income. Experimental results show that the Gini coefficient of traffic income in 2017 and 2018 had dropped significantly, but the variation of the Gini coefficient of stock income (Delta CG) was still greater than 0. Obviously, the adjustment speed of the Gini coefficient of stock income was lagging behind, as was the Gini coefficient of traffic income. We found that after 1986, the facilitation effect was greater than the dilution effect, and the facilitation effect continued to push up the stock income gap, which indicated more income flow to the high-income group, with the income flow gap showing an upward trend and the upward trend becoming more and more obvious. It has been proved that the PSO algorithm can effectively identify the income gap in the edge computing environment, and the corresponding policy suggestions are given.

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Section: Interpolation Calculation: Urban and Rural Incomementioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

[Retracted] Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment

Zhao

Liu

2022

Journal of Environmental and Public Health

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Cooking emission control with IoT sensors and connected air quality interventions for smart and healthy homes: Evaluation of effectiveness and energy consumption

Pantelic

Son

Staven

et al. 2023

Energy and Buildings

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iScene: An interpretable framework with hierarchical edge services for scene risk identification in 6G internet of vehicles

Zhong,

Wang,

2023

IET Communications

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Scene risk identification is essential for the traffic safety of Internet of Vehicles. However, the performance of existing risk identification approaches is heavily limited by the imbalanced historical data and the poor model interpretability. Meanwhile, the large processing delay and the potential privacy leakage threat also restrict their application. In this paper, a novel risk identification model is proposed that leverages the synthetic minority over‐sampling technique nearest neighbor (SMOTEENN) method to balance between high‐risk and low‐risk data. The risk identification model has fine interpretability by using recursive feature elimination cross validation (RFECV) with the Shapley additive explanation (SHAP) to analyze the importance of different features, and further elaborately design the Focal Loss function to tackle the disparity between the difficult and easy sample learning. The proposed interpretability scene risk identification framework, named iScene, is built on the infrastructure of 6G space‐air‐ground integrated networks (SAGINs) with blockchain assistance. The model updata efficiency and privacy preservation are effectively enhanced. An elastic computing offloading algorithm is applied to minimize the system overhead under the hierarchical edge service architecture. The experimental evaluation is carried out to verify the effectiveness of the proposed risk identification framework. The results indicate that the G‐Mean value is increased by 23.4%, while the task average response delay is reduced by 21.2%, compared to that in the traditional risk identification approaches with local computing services.

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Environment Optimization Scheme Based on Edge Computing Using PSO for Efficient Thermal Comfort Control in Resident Space

Cited by 5 publications

References 30 publications

[Retracted] Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment

[Retracted] Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment

Cooking emission control with IoT sensors and connected air quality interventions for smart and healthy homes: Evaluation of effectiveness and energy consumption

iScene: An interpretable framework with hierarchical edge services for scene risk identification in 6G internet of vehicles

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