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A Teaching Framework Based on Big Data of Students’ Learning Behaviors: A Case Study of Academic Performance Prediction Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Biological Fermentation Process Control on Account of Swarm Intelligence Algorithm

Authors : Shixiong Liu, Hui Chen, Zixuan Xu, Dacheng Liu

Published in: Frontier Computing

Publisher: Springer Nature Singapore

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Abstract

Biological fermentation industry is one of the modern industrial units in industrial economy. This technology has been applied in many aspects such as medical equipment and food on a large scale, and has been found to have excellent development potential and development dynamics. However, biological fermentation is a technology with various processes and complicated procedures, among which there are many influencing factors and the correlation between them is very huge. It is very difficult to fully grasp and conform to process objectives. This paper studies the control of biological fermentation process based on swarm intelligence algorithm, and describes the related content of biological fermentation process control. The test shows that the control research of biological fermentation process based on swarm intelligence algorithm improves the scientific and accuracy of biological fermentation process control simulation.

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Literature
1.
El-Shafeiy, E., Sallam, K.M., Chakrabortty, R.K., et al.: A clustering based swarm intelligence optimization technique for the internet of medical things. Expert Syst. Appl. 173(12), 114648 (2021) CrossRef
2.
3.
Castro, E., Salles, E., Ciarelli, P.M.: A new approach to enhanced swarm intelligence applied to video target tracking. Sensors 21(5), 1903 (2021)CrossRef
4.
Pasumpon, P.A.: Novel distance estimation based localization scheme for wireless sensor networks using modified swarm intelligence algorithm. IRO J. Sustain. Wirel. Syst. 2(4), 171–176 (2021)CrossRef
5.
Mashwani, W.K., Hamdi, A., Jan, M.A., et al.: Large-scale global optimization based on hybrid swarm intelligence algorithm. J. Intell. Fuzzy Syst. 39(1), 1257–1275 (2020)CrossRef
6.
7.
El-Saleh, A.A., Shami, T.M., Nordin, R., et al.: Multi-objective optimization of joint power and admission control in cognitive radio networks using enhanced swarm intelligence. Electronics 10(2), 189 (2021)CrossRef
8.
Awad, A., Salem, R., Abdelkader, H., et al.: A swarm intelligence-based approach for dynamic data replication in a cloud environment. Int. J. Intell. Eng. Syst. 14(2), 271–284 (2021)
9.
Yadav, R.K., Sivakkumarm, M., Kshirsagar, P.: Design framework of stock price forecasting using cascaded machine learning and swarm intelligence. Solid State Technol. 64(1), 724–738 (2021)
10.
11.
Arulanantham, D., Palanisamy, C., Pradeepkumar, G., et al.: An energy efficient path selection using swarm intelligence in IoT SN. In: Journal of Physics Conference Series, vol. 1916, no. 1, p. 012102 (2021)
12.
Cogun, S., Kara, B., Kunt, B., et al.: Biological recovery of phosphorus from waste activated sludge via alkaline fermentation and struvite biomineralization by Brevibacterium antiquum. Biodegradation 33(2), 195–206 (2022)CrossRef
13.
Zlateva, P.: A modified sliding mode control of a nonlinear methane fermentation process. In: E3S Web of Conferences, vol. 167, no. 3, p. 05007 (2020)
14.
Nitiema-Yefanova, S., Dossa, C., Gbohada, V., et al.: Fermented Parkia biglobosa seeds as a nitrogen source supplementation for bioethanol production from cashew apple juice. Int. J. Biol. Chem. Sci. 14(9), 3441–3454 (2021)CrossRef
15.
Winiewska, M., Kulig, A., Lelicińska-Serafin, K.: The impact of technological processes on odorant emissions at municipal waste biogas plants. Sustainability 12(13), 5457 (2020)CrossRef
Metadata
Title
Biological Fermentation Process Control on Account of Swarm Intelligence Algorithm
Authors
Shixiong Liu
Hui Chen
Zixuan Xu
Dacheng Liu
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Frontier Computing

Print ISBN: 978-981-9914-27-2

Electronic ISBN: 978-981-9914-28-9

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-99-1428-9_80