Energy, exergy analysis and optimization by a genetic algorithm of a system based on a solar absorption chiller with a cylindrical PCM and nano-fluid

Keshtkar, Mohammad Mehdi

doi:10.18280/ijht.35226

Cited by 10 publications

(8 citation statements)

References 11 publications

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“…As shown in Figure 6 , when using the genetic algorithm to deal with multi-objective problems, how to deal with multiple objective functions is the primary problem to solve the model. Many scholars have proposed the method of weight coefficient, which assigns the corresponding weight to each sub-objective, and then combines the weighted calculation of each objective into a single objective function ( 31 ). The weight coefficient indicates the importance of an index item in the index item system.…”

Section: Multi-objective Model Based On Genetic Algorithm and Improve...mentioning

confidence: 99%

Networked Organizational Structure of Enterprise Information Security Management Based on Digital Transformation and Genetic Algorithm

Liu

2022

Front. Public Health

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With the rapid development of society and economy, enterprises have also started digital transformation in order to follow the pace. Now-a-days, the development of enterprises is also faced with the risk of improper management of enterprise information security, so it is very necessary to study the networked organizational structure of enterprise information security management. The purpose of this paper is to study how to analyze the network organization structure of enterprise information security management based on genetic algorithm. This paper puts forward the difficult problems faced by enterprise information security, and how to prevent and solve the risks encountered in information security. In the experimental part of this paper, it can be seen that with the increase of the number of experiments, the work efficiency of the traditional network organization structure has increased from about 4.6 to about 17%. The work efficiency of the network organization structure based on genetic algorithm has risen from about 10 to about 50%. It shows that the work efficiency of the network organization structure based on genetic algorithm is much higher than that of the traditional network organization structure. It can be seen that the advantage percentage of enterprise information security management networked organizational structure with strong room for growth is 79–84%, and the percentage of cost savings is 75–82%. It can be seen that there are still many advantages of the networked organizational structure of enterprise information security management. The network organization structure based on genetic algorithm can not only improve the work efficiency of enterprises, but also improve the information security. Therefore, the network organization structure based on genetic algorithm is of great significance to the enterprise information security.

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Section: Multi-objective Model Based On Genetic Algorithm and Improve...mentioning

confidence: 99%

Networked Organizational Structure of Enterprise Information Security Management Based on Digital Transformation and Genetic Algorithm

Liu

2022

Front. Public Health

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“…This is similar to the biological evolution process, where the individuals that can adapt to the changes in the environment survive and those who do not are eliminated. Through continuous iterations, the genetic algorithm obtains the solution with the highest fitness function value, which is the optimal solution to the problem (Li, 2017;Mohanty et al, 2016;Dhabal et al, 2017;İnkaya et al, 2015;Keshtkar, 2017;Huang et al, 2016;Yuan et al, 2017). The main implementation process of the genetic algorithm is shown in Fig.2:…”

Section: Genetic Algorithmmentioning

confidence: 99%

Slope Stability Analysis Based on the Radial Basis Function Neural Network of the Cerebral Cortex

Qin¹,

Chen²,

Fu³

et al. 2018

Neuroquantology

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The artificial neural network technology simulates the neural network structure of the cerebral cortex by establishing artificial neurons and sensors to solve nonlinear engineering problems, and establishes the prediction model for solving such problems. Rock slope stability is a hot research topic in the field of geotechnical engineering, especially for those slopes affected by the cyclic changes of water level. This paper establishes a slope stability prediction model based on the radial basis function neural network (RBFNN) of the cerebral cortex and introduces the genetic algorithm to eliminate the drawbacks of the cerebral cortex RBFNN, that is, slow convergence and local optimisation. The cerebral cortex RBFNN prediction model can predict the slope safety factor, with the relative error controlled between-5.16% and 6.02%. According to the cerebral cortex RBFNN prediction results, as the water level in the tailing pond changes cyclically, the rock mechanics parameters of the slope gradually weaken, which leads to the continuous decrease of the slope safety factor. The results can provide reference for the extension and application of the cerebral cortex RBFNN in the engineering field, and serve as guidance for the specific project safety maintenance.

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“…Various classical deep neural network structures suitable for different data processing tasks are generated [6]. Target detection algorithms in deep learning are generally divided into the candidate region-based algorithm and regression-based algorithm [7]. e candidate region-based algorithm divides the target detection process into two stages: one is to create candidate regions, and the other is to use classifiers to classify candidate regions [8].…”

Section: Introductionmentioning

confidence: 99%

Technical Research on Optimization of Irrigation Canal System Considering Genetic Algorithm

Wang

2022

Mobile Information Systems

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In order to solve the lack of optimization and comparison of the previous schemes in the irrigation and water conservancy project reconstruction, the engineering design and planning are difficult to reach the best state, resulting in water resource waste and other problems. In this paper, genetic algorithm optimization technology of the irrigation canal system is studied, in-depth learning technology of image processing is elaborated, the rectangular optimization model is established, and the optimal nonlinear design of trapezoidal and U-shaped sections of irrigation channel is verified by engineering examples. According to the geographical location, water source, irrigation area, irrigation area, and designer’s experience, two possible irrigation scheme layouts have been determined, and the trapezoidal section has been optimized. The results show that the value of the objective function decreases rapidly with the increase of iteration time. Scheme 1 has stabilized for about 19 generations. Scheme 2 tends to be stable for about 25 generations. The optimization results of the U-shaped section show that scheme 1 is stable for about 43 generations, while scheme 2 tends to be stable for about 60 generations. By comparing the optimal schemes of the trapezoidal section and the U-section, it can be found that the water supply cost of the U-section is low. Therefore, under the condition of layout scheme 2, the U-shaped section is the best scheme. The calculation shows that under the same conditions, the trapezoidal section area is about 45% larger than the U-shaped section area. Although the trapezoidal section is adopted in the original project, the U-shaped section is recommended when construction conditions permit. The optimization method can quickly determine the overall optimization scheme of irrigation channels. The water supply cost depends on the final optimized objective function value, which is used as the reference basis for formulating the water supply price. The optimal design scheme should not only meet the provisions of engineering practice but also meet the requirements of the lowest water supply cost.

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Energy, exergy analysis and optimization by a genetic algorithm of a system based on a solar absorption chiller with a cylindrical PCM and nano-fluid

Cited by 10 publications

References 11 publications

Networked Organizational Structure of Enterprise Information Security Management Based on Digital Transformation and Genetic Algorithm

Networked Organizational Structure of Enterprise Information Security Management Based on Digital Transformation and Genetic Algorithm

Slope Stability Analysis Based on the Radial Basis Function Neural Network of the Cerebral Cortex

Technical Research on Optimization of Irrigation Canal System Considering Genetic Algorithm

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