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Estimation of zooplankton density with artificial neural networks (a new statistical approach) method, Elazığ-Türkiye Cover

Estimation of zooplankton density with artificial neural networks (a new statistical approach) method, Elazığ-Türkiye

By: Hilal Bulut  
Open Access
|Dec 2023

Figures & Tables

Figure 1

Coordinates of Cip Reservoir
Coordinates of Cip Reservoir

Figure 2

Model Structure of ANNs
Model Structure of ANNs

Figure 3

Some water quality parameters of study field
Some water quality parameters of study field

Figure 4

Monthly changes of total zooplankton in Cip Reservoir at the 1st, 2nd, and 3rd station
Monthly changes of total zooplankton in Cip Reservoir at the 1st, 2nd, and 3rd station

Figure 5

Training, validation, testing and all data results of artificial neural networks for the 1st station
Training, validation, testing and all data results of artificial neural networks for the 1st station

Figure 6

Training, validation, testing and all data results of artificial neural networks for the 2nd station
Training, validation, testing and all data results of artificial neural networks for the 2nd station

Figure 7

Training, validation, testing and all data results of artificial neural networks for the 3rd station
Training, validation, testing and all data results of artificial neural networks for the 3rd station

Figure 8

Artificial neural networks training state at the 1st station
Artificial neural networks training state at the 1st station

Figure 9

Artificial neural networks training state at the 2nd station
Artificial neural networks training state at the 2nd station

Figure 10

Artificial neural networks training state at the 3rd station
Artificial neural networks training state at the 3rd station

Comparison with artificial neural networks of real values of zooplankton density for the 2nd station

Monthrotifercladoceracopepeda
Real DataANNsMAPE (%)Real DataANNsMAPE (%)Real DataANNsMAPE (%)
September33113329920.3655095060.58900.0000.000
October27510274360.269458545261.287305730570.000
November15285155501.733101910190.000305730570.000
December968196220.609023.0120.0004104100.000
January326032981.166017.7850.0005095090.000
February560555960.161062.3180.000917191960.273
March560455211.4815095070.393122412240.000
April305730560.033305730570.00000.0010.000
May815183642.613713270471.19200.0000.000
June14776147730.02012942129170.1932052091.951
July407641762.45312738126270.871023.510.000
August101910150.3930125880.0005095090.000
Average MAPE (%)0.941 0.377 0.185

Comparison with artificial neural networks of real values of zooplankton density for the 3rd station

Monthrotifercladoceracopepeda
Real DataANNsMAPE (%)Real DataANNsMAPE (%)Real DataANNsMAPE (%)
September28532285800.1682032082.46300.0430.000
October31080310810.003356735960.813101910180.098
November15489155360.3035095090.000407640251.251
December13247132180.2192032061.4785095080.196
January377037740.10600.9580.0005095090.000
February16814168390.1495095011.5722032040.493
March27543271691.3585095080.1965095090.000
April23438234390.004101910180.0982032010.985
May36175361320.119866286610.011101910180.098
June37705376650.106713471330.0142032030.000
July12738126081.02011210112090.00900.2280.000
August968196310.516356735660.0282032020.493
Average MAPE (%)0.342 0.557 0.301

Comparison with artificial neural networks of real values of zooplankton density for the 1st station

Monthrotifercladoceracopepeda
Real DataANNsMAPE (%)Real DataANNsMAPE (%)Real DataANNsMAPE (%)
September68273682720.0015095090.00000.0020.000
October50950498862.088458545850.000203820380.000
November35667347302.627101910190.000560556040.018
December10190101880.01902.2620.00000.0020.000
January397339730.00000.0610.0005095080.196
February17323173160.04000.0370.000152815280.000
March30061300560.01600.6880.00001.8370.000
April27515283152.907101910180.09800.0000.000
May43817438170.000968196800.0102032061.478
June58533585120.03617833178320.00600.0000.000
July17324183595.97423948239470.00401.9390.000
August866286630.012254825811.29500.1820.000
Average MAPE (%)1.143 0.118 0.141
DOI: https://doi.org/10.26881/oahs-2023.4.11 | Journal eISSN: 1897-3191 | Journal ISSN: 1730-413X
Language: English
Page range: 502 - 515
Submitted on: Oct 8, 2023
Accepted on: Nov 27, 2023
Published on: Dec 31, 2023
Published by: University of Gdańsk
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Hilal Bulut, published by University of Gdańsk
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.