Improving performance of classification on severity of ill effects (SEV) index on fish using K-Means clustering algorithm with various distance metrics

Khakzad, Hamid

doi:10.2166/wpt.2018.112

Cited by 3 publications

(4 citation statements)

References 23 publications

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“…Before modeling, exploratory data analysis (Xiao et al 2012) is carried out to find the potential law of this dataset. In this study, KCA (Kim & Parnichkun 2017;Hamid 2019) is carried out for data of different time spans, and the results show that there is obvious law in the clustering results of annual data. The data normalization is carried out to present clustering results clearly.…”

Section: Exploratory Data Analysismentioning

confidence: 92%

Rainfall prediction optimization model in ten-day time step based on sliding window mechanism and zero sum game

Liu

Sang

Chang

et al. 2021

Journal of Water Supply: Research and Technology-Aqua

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Rainfall is a precious water resource, especially for Shenzhen with scarce local water resources. Therefore, an effective rainfall prediction model is essential for improvement of water supply efficiency and water resources planning in Shenzhen. In this study, a deep learning model based on zero sum game (ZSG) was proposed to predict ten-day rainfall, the regular models were constructed for comparison, and the cross-validation was performed to further compare the generalization ability of the models. Meanwhile, the sliding window mechanism, differential evolution genetic algorithm, and discrete wavelet transform were developed to solve the problem of data non-stationarity, local optimal solutions, and noise filtration, respectively. The k-means clustering algorithm was used to discover the potential laws of the dataset to provide reference for sliding window. Mean square error (MSE), Nash–Sutcliffe efficiency coefficient (NSE) and mean absolute error (MAE) were applied for model evaluation. The results indicated that ZSG could better optimize the parameter adjustment process of models, and improved generalization ability of models. The generalization ability of the bidirectional model was superior to that of the unidirectional model. The ZSG-based models showed stronger superiority compared with regular models, and provided the lowest MSE (1.29%), NSE (21.75%), and MAE (7.5%) in the ten-day rainfall prediction.

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Section: Exploratory Data Analysismentioning

confidence: 92%

Rainfall prediction optimization model in ten-day time step based on sliding window mechanism and zero sum game

Liu

Sang

Chang

et al. 2021

Journal of Water Supply: Research and Technology-Aqua

View full text Add to dashboard Cite

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“…R‐type cluster analysis was carried out for the seven variables (Hamid, 2019; Jia, Ma, & Kang, 2020). Based on the standardized variable values of MOR, ASR, SSC, DO, DOS, ED, and T, the similarity between variables was measured by Pearson correlation coefficient.…”

Section: Materials and Methodologymentioning

confidence: 99%

“…It can also provide operational parameters for fish protection (Paolo Espa et al, 2019; Moridi & Yazdi, 2017). Through evaluation under complex environmental conditions for different fish species, the model had been continuously modified to improve accuracy (Hamid, 2019; Xu et al, 2018). In this paper, the degree of acute effect on Gymnocypris eckloni was calculated based on the SEV model (ED ≤9 h).…”

Section: Materials and Methodologymentioning

confidence: 99%

Experimental study on acute impacts of hyper‐concentrated flow on Gymnocypris Eckloni and implication for sediment management

Baoligao

et al. 2023

River Research & Apps

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Significant increases in suspended sediment concentration (SSC) always occur during dam removal or sediment flushing processes, which could result in acute impacts on aquatic organisms. An analysis of the potential impact of the Huangheyuan hydropower dam removal on the upper reaches of the Yellow River is required for adaptive management. But the reports on the impact of high SSC on fishes living in rivers in the plateau areas are limited. Further studies on impact factors, fish behavior, and assessment methods were performed in this paper. The acute response of a typical fish, Gymnocypris eckloni, was tested by experiments with sediment concentrations ranging from 3.3 × 103 to 80.78 × 103 mg·L−1. The changes in fish aquatic surface respiration (ASR) behavior were analyzed under different SSCs. The cluster analysis of the environmental factors was conducted to analyze the relationship between the factors and fish mortality. The severity of ill effects (SEV) model was improved to assess the acute impact on fish. The results indicated that the SSC was the most related factor. The ASR could be induced by the SSC higher than 21 × 103 mg·L−1, and fish mortality was caused by SSC higher than 55 × 103 mg·L−1. The thresholds of SSC and exposure duration for fish protection were proposed to be less than 55 × 103 mg·L−1 and 6 hr, respectively. The findings could support the planning and regulation of dam sediment management on plateau areas.

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“…e cycle life takes into account the deterioration caused by the charge-discharge cycle of the power battery in the electric vehicle, and the calendar life refers to the battery deterioration caused by the storage of the battery without going through the charge-discharge cycle. In practical applications, the power battery will be in a state of charge, discharge, and static, so the cycle aging and calendar aging of the battery need to be considered [13,14].…”

Section: Characteristics Of Lithium Batteriesmentioning

confidence: 99%

Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

Qin

2022

Mathematical Problems in Engineering

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Lithium-ion batteries, the core components of electric vehicles, have received unprecedented attention and undergone development in the era of huge energy demand. The traditional clustering algorithm cannot meet the requirement of the consistency of lithium battery distribution. In this study, we provide an improved K-means algorithm to meet the battery distribution needs of enterprises and combine it with reality. This model includes an early data processing model and a battery comparison method based on the new K-means algorithm. In the battery data processing model, the preprocessing process approach and actual production standards preclude problematic batteries. In the battery comparison algorithm, the number of batteries in each cluster becomes equal after the battery comparison. The algorithm can ensure the internal characteristics of lithium-ion power batteries, and, at the same time, after the matching is completed, the number of lithium batteries in each cluster is equal.

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Improving performance of classification on severity of ill effects (SEV) index on fish using K-Means clustering algorithm with various distance metrics

Cited by 3 publications

References 23 publications

Rainfall prediction optimization model in ten-day time step based on sliding window mechanism and zero sum game

Rainfall prediction optimization model in ten-day time step based on sliding window mechanism and zero sum game

Experimental study on acute impacts of hyper‐concentrated flow on Gymnocypris Eckloni and implication for sediment management

Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

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