Design and Implementation of Environmental Protection Publicity Based on Green Energy Effect

doi:10.38007/nep.2022.030307

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…It can consider optimization in terms of open and closed mechanisms, personnel evacuation and transfer mechanisms, etc. By searching and collaborating with individual bees, the optimal response strategy can be found to improve the efficiency and accuracy of emergency response (Guo, 2022;Wang, 2022). The application of artificial bee colony algorithm in the shelter planning in oil and gas energy resource-based cities can provide faster, more accurate and comprehensive solutions, help decisionmakers make more reasonable decisions and improve the resilience and adaptability of shelters.…”

Section: Application Of Artificial Bee Colony Algorithm In the Planni...mentioning

confidence: 99%

Algorithm for planning shelters in oil and gas energy resource-based cities based on artificial intelligence resilient city model

Liang,

2023

Front. Energy Res.

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Cities based on oil and gas energy resources are crucial to energy production and economic development, but they also face various disasters and security risks. To ensure the safety and well-being of urban residents during disaster events, the planning of urban shelters is crucial. In this paper, comprehensively considering multiple factors such as disaster risk, population distribution, and convenient transportation, the artificial bee colony algorithm is used to optimize the site selection and capacity planning of shelters. By comprehensively evaluating the disaster resistance capacity of urban refuges, the response speed of residents and other related indicators, the planning algorithm of refuges is continuously optimized to better meet the needs of oil and gas energy resource-based cities. The results of the study showed that the average overall disaster resilience of AI-based urban shelters reached 0.64. When the distance to the shelter was 4 km, the average response speed of residents reached 10.22 min, and other indicators also improved. The research shows that the oil and gas energy urban refuge planning algorithm based on the artificial intelligence elastic city model provides an innovative approach for urban planners and disaster managers. Further research and practice will help promote the application of this algorithm in real cities, improving the resilience and disaster resistance of cities and the safety and security level of residents.

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Section: Application Of Artificial Bee Colony Algorithm In the Planni...mentioning

confidence: 99%

Algorithm for planning shelters in oil and gas energy resource-based cities based on artificial intelligence resilient city model

Liang,

2023

Front. Energy Res.

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“…Fourthly, repeat the above steps three times to ensure that the interval time and torque value are the same. Therefore, the comparison of stator current of induction motors in vehicles with and without energy-saving controllers is shown in Figure 4 [20].…”

Section: Case Numbermentioning

confidence: 99%

Innovative Application of Energy-Saving Control Technology in Mechanical and Electronic Engineering

2023

AJETS

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In the context of modern society, economic and technological progress, energy consumption is increasingly intensifying. It is in this context that people's understanding of energy conservation has gradually deepened, and control technologies for energy conservation have also rapidly developed. The energy-saving control system is a control system established based on energy-saving control technology. It utilizes programmable automation control technology to achieve automatic control of the system, and has obvious advantages in energy-saving control in electronic and mechanical engineering. This article takes the energy-saving controller of asynchronous motors for vehicles as the research object, with the aim of reducing motor energy consumption and improving motor efficiency, to study extending the range of electric vehicles. In the energy-saving comparison experiment, this article proposes a scheme for energy-saving control experiment of automotive asynchronous motors. The experimental results show that under energy-saving conditions, the power factor improvement in condition 2 is the largest, with a value of 67%. Under the condition of not using any energy, the power factor of condition 6 increases by a maximum of 65%. This proves the correctness and effectiveness of this control method. It is very important to adopt energy-saving control technology for the application research of asynchronous motors.

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Design and Implementation of Environmental Protection Publicity Based on Green Energy Effect

Cited by 2 publications

References 3 publications

Algorithm for planning shelters in oil and gas energy resource-based cities based on artificial intelligence resilient city model

Algorithm for planning shelters in oil and gas energy resource-based cities based on artificial intelligence resilient city model

Innovative Application of Energy-Saving Control Technology in Mechanical and Electronic Engineering

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