Physical habitat simulation for a fish community using the ANFIS method

Im, Donggu; Choi, Sung Uk; Choi, Byeong-Dae

doi:10.1016/j.ecoinf.2017.09.001

Cited by 21 publications

(13 citation statements)

References 49 publications

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“…Hence, developed model was able to consider effect of unknown factors to predict habitat suitability. Based on review on previous researches, they were not as robust as developed IWO-ANFIS model [26,27]. In other words, application of evolutionary algorithm could improve results of habitat model or enhance proximity between results by model and observations.…”

Section: Resultsmentioning

confidence: 99%

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Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams

Sedighkia

Abdoli²

2021

SN Appl. Sci.

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This study presents a coupled invasive weed optimization-adaptive neuro fuzzy inference system method to simulate physical habitat in streams. We implement proposed method in Lar national park in Iran as one of the habitats of Brown trout in southern Caspian Sea basin. Five indices consisting of root mean square error (RMSE), mean absolute error (MAE), reliability index, vulnerability index and Nash–Sutcliffe model efficiency coefficient (NSE) are utilized to compare observed fish habitats and simulated fish habitats. Based on results, measurement indices demonstrate model is robust to assess physical habitats in rivers. RMSE and MAE are 0.09 and 0.08 respectively. Besides, NSE is 0.78 that indicates robustness of model. Moreover, it is necessary to apply developed habitat model in a practical habitat simulation. We utilize two-dimensional hydraulic model in steady state to simulate depth and velocity distribution. Based on qualitative comparison between results of model and observation, coupled invasive weed optimization-adaptive neuro fuzzy inference system method is robust and reliable to simulate physical habitats. We recommend utilizing proposed model for physical habitat simulation in streams for future studies.

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Section: Resultsmentioning

confidence: 99%

“…Therefore, using simple mathematical relationship would not be precise method to assess habitats. ANFIS has been utilized to develop physical habitat data-driven models [26][27][28]. However, effectiveness of improving training methods is ambiguous.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams

Sedighkia

Abdoli²

2021

SN Appl. Sci.

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“…Statistically learning the inflow time-series using a probabilistic forecast method (Liu et al, 2018) or using a reinforcement learning method (Castelletti et al, 2010) is an option to customize the presented model. The presented model can work as an upstream boundary condition of the eco-hydraulic model (Im et al, 2018). We must pay attention to multiple local optima (Wu et al, 2018) in these cases.…”

Section: Discussionmentioning

confidence: 99%

Regime-switching constrained viscosity solutions approach for controlling dam–reservoir systems

Yoshioka

2020

Computers & Mathematics with Applications

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“…The total number of monitoring points were 4,409. In the present study, the Mahalanobis distance method was used to identify outliers in the monitoring data (Im, Choi, & Choi, ). The data quality assessment identified 238 outliers, resulting in a total of 4,171 datasets for training of the ANFIS model.…”

Section: Methodsmentioning

confidence: 99%

Change in fish community composition following weir removal, field observations, and physical habitat simulations

Choi

2019

River Research & Apps

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The number of untended weirs has increased in Korea in recent years due to land use changes. The removal of abandoned weirs in streams has been attempted following an agreement between local government and residents. The Gongneung Weir-2 was built for irrigation in the 1970s and was removed in 2006. The objective of this study was to investigate the impact of the removal of Gongneung Weir-2 on the composition of the fish community. The study area was a 900-m-long reach in the Gongneung-cheon River in Korea, and Gongneung Weir-2 was located in the middle of the reach. Before weir removal, field monitoring revealed that five fish species were dominant and accounted for more than 80% of the entire fish community. The composition of the fish community changed significantly after weir removal.Lotic fish became dominant after weir removal, whereas lentic fish were dominant prior to weir removal. Physical habitat simulations (PHSs) for individual dominant fish species were carried out. For the PHS, the River2D model and the adaptive neurofuzzy inference system method were used for hydraulic and habitat simulations, respectively. The distributions of the highly suitable portion for each fish species were identified before and after weir removal. The PHS successfully predicted changes in the composition of the fish community after weir removal. The PHSs for the entire fish community and for the lotic and lentic guilds were undertaken and the simulated results were compared with each other. The PHSs for the entire fish community could not account for the less dominant fish species in the fish community. KEYWORDSANFIS, fish community, highly suitable portion, lotic and lentic guild, physical habitat simulation, weir removal

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Physical habitat simulation for a fish community using the ANFIS method

Cited by 21 publications

References 49 publications

Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams

Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams

Regime-switching constrained viscosity solutions approach for controlling dam–reservoir systems

Change in fish community composition following weir removal, field observations, and physical habitat simulations

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