An Oxygen Forecasting Strategy for Waterless Live Fish Transportation Based on IPSO-GRU Method

Zhang, Yongjun; Ning, Yufu; Zhang, Huan

doi:10.1007/978-3-030-81007-8_15

Cited by 2 publications

(4 citation statements)

References 12 publications

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“…The Western region grapples with transportation time and vehicle vibration, likely influenced by poor roads and infrastructure. A similar finding was noted by Zhang et al (2022), where they addressed the oxygen concern in waterless live fish transportation by creating a model using the IPSO-GRU method. This model offers effective prediction and early-warning functions for oxygen consumption during fish waterless keepalive transportation.…”

Section: Discussionsupporting

confidence: 70%

“…Notably, public transport is a noteworthy aspect in Central and Nairobi, showcasing the adaptability within the industry, a trend similarly observed by Asiedu et al (2023) in Ghana. In West-ern and Nyanza regions, purpose-built vehicles are commonly used, as also observed Peer Mohamed and Devaraj (1997) and Zhang et al (2022). This highlights its importance in enhancing fish survival and reducing stress during transportation.…”

Section: Discussionmentioning

confidence: 70%

“…The use of salt during transportation is recommended, especially for air-breathing pirarucu fingerlings, to reduce stressors during long-distance transportation (Iversen et al 1998;Gomes et al 2006). Common stressors include improper handling, air exposure, inadequate food utilisation, poor conditioning, stomach evacuation before transportation, poor water quality, and inappropriate packaging densities concerning oxygen availability in the bags (Harmon 2009;Saeed et al 2022;Zhang et al 2022). Sudden changes in water temperature and rapid water movement have also been identified as emerging stressors for fish during transportation (Pakhira et al 2015).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aqua perspectives: stakeholder attitudes and perceptions in live fish transportation practices within the Kenyan fisheries sector

Syanya,

Mathia,

Mumina

et al. 2024

Mar Fish Sci

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Live fish are in high demand all over the world, especially in China, where quality standards align with consumer preferences. In Kenya, discussions on live fish, particularly in aquaculture-rich regions, are focal points. However, the lack of a systematic approach to transporting live fish poses challenges for stakeholders. This research explores attitudes and perceptions of stakeholders in Kenya regarding the adoption and transportation of live fish, shedding light on transportation procedures and sector challenges. Using a descriptive research design, primary data were collected from diverse aquaculture stakeholders through a questionnaire, addressing their knowledge, perceptions, and attitudes toward live fish transportation in the country. The study unveils varied patterns of live fish transportation in Kenya, influenced by the purpose and distance. Private cars are prominent at 26.3%, with Nyanza and Mombasa leading at 35%. Modified vans are prevalent in Central-Nairobi and Western regions (25% and 22.5%, respectively), while public transport is widespread, especially in Central and Nairobi (25%). Purpose-built live fish vehicles dominate in Western and Nyanza (20% and 17.5%, respectively). Crustaceans like lobsters and crabs are primarily exported from the Coastal region (27.5%). Participants generally assessed their knowledge of live fish transportation as moderate, with a basic understanding of fish welfare. Feedback indicates common practices in live fish transport in Kenya as sealed tanks, plastic bags, and purpose-built vehicles. Temperature and oxygen fluctuations poses a significant challenge during transportation across all regions, particularly in Mombasa and Kisumu. The use of anaesthetics, especially for food fish, is infrequently reported. The study revealed favourable perceptions of stakeholders to live fish transportation and welfare, indicating early adoption. Further research is recommended on fish welfare, best management practices, technological advancements, and interdisciplinary studies to enhance the sustainability of live fish transportation sector and fish welfare in Kenya.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Aqua perspectives: stakeholder attitudes and perceptions in live fish transportation practices within the Kenyan fisheries sector

Syanya,

Mathia,

Mumina

et al. 2024

Mar Fish Sci

View full text Add to dashboard Cite

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“…To overcome the constraints inherent in the traditional Particle Swarm Optimization (PSO) algorithm, this study incorporates elements from immunological algorithms-speci cally, the notions of "immune memory" and "antibody concentration inhibition" (Zhang et al, 2022). The synergistic effects of these two mechanisms signi cantly reduce the likelihood of premature convergence, while still enabling the algorithm to converge rapidly.…”

Section: Ipso Algorithmmentioning

confidence: 99%

Research on Water Quality Prediction of Mine Surroundings Based on Improved Machine Learning Algorithm

Liu,

Gao

2024

Preprint

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Acid Mine Drainage (AMD) poses a significant environmental challenge, frequently occurring at mining, smelting, and closed mine locations. This phenomenon arises when sulfide ores come into contact with oxygen and water, forming sulfuric acid. This acid subsequently dissolves in mine water, increasing its acidity. Sulfate (SO4) serves as a crucial indicator of acid mine water quality. Precise prediction of SO4 concentrations post-treatment is essential for achieving compliant and stable wastewater discharge, thereby mitigating environmental risks. In this paper, we introduce IPSO-GRU, a novel artificial intelligence algorithm designed to predict water quality accurately. Our IPSO-GRU model employs particle swarm optimization to enhance support vector regression for SO4 prediction. The performance indices of the model show a Root Mean Square Error (RMSE) of 0.104, a Mean Absolute Error (MAE) of 0.061, and a Coefficient of Determination (R²) of 0.79. Comparative evaluations with IPSO-RNN and IPSO-LSTM models reveal that IPSO-GRU outperforms these alternatives across RMSE, MAE, and R² metrics, confirming its efficacy as the most suitable model for predicting SO4 concentrations in mine wastewater.

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An Oxygen Forecasting Strategy for Waterless Live Fish Transportation Based on IPSO-GRU Method

Cited by 2 publications

References 12 publications

Aqua perspectives: stakeholder attitudes and perceptions in live fish transportation practices within the Kenyan fisheries sector

Aqua perspectives: stakeholder attitudes and perceptions in live fish transportation practices within the Kenyan fisheries sector

Research on Water Quality Prediction of Mine Surroundings Based on Improved Machine Learning Algorithm

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