This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aguilar Ibarra, A., Gevrey, M., Park, Y S., Lim, P., & Lek, S. (2003). Modelling the factors that influence fish guilds composition using a back-propagation network: Assessment of metrics for indices of biotic integrity. Ecological Modelling, 160, 281-290. https://doi.org/10.1016/S0304-3800(02)00259-4Aguilar IbarraA.GevreyM.ParkY S.LimP.LekS. (2003). Modelling the factors that influence fish guilds composition using a back-propagation network: Assessment of metrics for indices of biotic integrity. , 160, 281-290. https://doi.org/10.1016/S0304-3800(02)00259-4Open DOISearch in Google Scholar
Anderson, D., & McNeill, G. (1992). Artificial neural networks technology. Kaman Sciences Corporation, 258(6), 1-83.AndersonD.McNeillG. (1992). . Kaman Sciences Corporation, 258(6), 1-83.Search in Google Scholar
Amoros, C., Roux, A. L., Reygrobellet, J. L., Bravard, J. P., & Pautou, G. (1987). A method for applied ecological studies of fluvial hydrosystems. Regulated Rivers, 1, 17-36. https:// doi.org/10.1002/rrr.3450010104AmorosC.RouxA. L.ReygrobelletJ. L.BravardJ. P.PautouG. (1987). A method for applied ecological studies of fluvial hydrosystems. , 1, 17-36. https://doi.org/10.1002/rrr.3450010104Open DOISearch in Google Scholar
Aoki, I., & Komatsu, T. (1997). Analysis and prediction of the fluctuation of sardine abundance using a neural network. Oceanologica Acta, 20(1), 81-88.AokiI.KomatsuT. (1997). Analysis and prediction of the fluctuation of sardine abundance using a neural network. , 20(1), 81-88.Search in Google Scholar
Attayde, J. L., & Bozelli, R. L. (1998). Assessing the indicator properties of zooplankton as-semblages to disturbance gradients by canonical correspondence analysis. Canadian Journal of Fisheries and Aquatic Sciences, 55, 1789-1797. https://doi.org/10.1139/f98-033AttaydeJ. L.BozelliR. L. (1998). Assessing the indicator properties of zooplankton as-semblages to disturbance gradients by canonical correspondence analysis. , 55, 1789-1797. https://doi.org/10.1139/f98-033Open DOISearch in Google Scholar
Banse, K. (1995). Zooplankton: Pivotal role in the control of ocean production. ICES Journal of Marine Science, 52 (3-4), 265-277. https://doi.org/10.1016/1054-3139(95)80043-3BanseK. (1995). Zooplankton: Pivotal role in the control of ocean production. , 52 (3-4), 265-277. https://doi.org/10.1016/1054-3139(95)80043-3Open DOISearch in Google Scholar
Benzer, S., Benzer, R., & Gunal Caglan, A. (2017). Artificial Neural Networks approach in morphometric analysis of crayfish (Astacus leptodactylus) in Hirfanli Dam Lake. Biologia, 72, 527-535. https://doi.org/10.1515/biolog-2017-0052BenzerS.BenzerR.Gunal CaglanA. (2017). Artificial Neural Networks approach in morphometric analysis of crayfish (Astacus leptodactylus) in Hirfanli Dam Lake. , 72, 527-535. https://doi.org/10.1515/biolog-2017-0052Open DOISearch in Google Scholar
Benzer, S., & Benzer, R. (2018). New perspectives for predicting growth properties of crayfish (Astacus leptodactylus Eschscholtz, 1823) in Uluabat Lake. Pakistan Journal of Zoology, 50(1), 35-45. https://doi.org/10.17582/journal. pjz/2018.50.1.35.45BenzerS.BenzerR. (2018). New perspectives for predicting growth properties of crayfish (Astacus leptodactylus Eschscholtz, 1823) in Uluabat Lake. , 50(1), 35-45. https://doi.org/10.17582/journal.pjz/2018.50.1.35.45Open DOISearch in Google Scholar
Bulut, H., & Saler, S. (2018). Seasonal Variations in Zooplankton Community of an Aquatic Ecosystem at Susurluk Basin (Balikesir-Turkey). Fres. Env. Bul., 27(7), 2530-2535.BulutH.SalerS. (2018). Seasonal Variations in Zooplankton Community of an Aquatic Ecosystem at Susurluk Basin (Balikesir-Turkey). ., 27(7), 2530-2535.Search in Google Scholar
Bulut, H., & Saler, S. (2019). Effect of physicochemical parameters on zooplankton at a freshwater body of Euphrates Basin (Elazig-Turkey). Cellular and Molecular Biology, 65(1), 8-13. https://doi.org/10.14715/cmb/2019.65.1.2 PMID:30782288BulutH.SalerS. (2019). Effect of physicochemical parameters on zooplankton at a freshwater body of Euphrates Basin (Elazig-Turkey). , 65(1), 8-13. https://doi.org/10.14715/cmb/2019.65.1.2 PMID:30782288Open DOISearch in Google Scholar
Bulut, H., & Saler, S. (2020). Monthly distribution of zooplankton in Kapikaya Reservoir, Turkey. Maejo International Journal of Science and Technology, 14 (1), 1-10.BulutH.SalerS. (2020). Monthly distribution of zooplankton in Kapikaya Reservoir, Turkey. , 14 (1), 1-10.Search in Google Scholar
Burns, C. W., & Galbraith, L. M. (2007). Relating planktonic microbial food web structure in lentic freshwater ecosystems to water quality and land use. Journal of Plankton Research, 29(3), 127-139. https://doi.org/10.1093/ plankt/fbm001BurnsC. W.GalbraithL. M. (2007). Relating planktonic microbial food web structure in lentic freshwater ecosystems to water quality and land use. , 29(3), 127-139. https://doi.org/10.1093/plankt/fbm001Open DOISearch in Google Scholar
Deivanai, K., Arunprasath, S., Rajan, M. K., & Baskaran, S. (2004). Biodiversity of phyto and zooplankton in relation to water quality parameters in a sewage polluted pond at Ellayirampannai, Virudhunagar District. In: The proceedings of National Symposium on biodiversity resources management and sustainable use, organized by the center for biodiversity and Forest studies, Madurai Kamaraj University. Madurai.DeivanaiK.ArunprasathS.RajanM. K.BaskaranS. (2004). Biodiversity of phyto and zooplankton in relation to water quality parameters in a sewage polluted pond at Ellayirampannai, Virudhunagar District. In: , Madurai Kamaraj University. Madurai.Search in Google Scholar
Dini, M. L., & Carpenter, S. R. (1992). Fish predators, food availability and diel vertical migration in Daphnia. Journal of Plankton Research, 14, 359-377. https://doi.org/10.1093/ plankt/14.3.359DiniM. L.CarpenterS. R. (1992). Fish predators, food availability and diel vertical migration in Daphnia. , 14, 359-377. https://doi.org/10.1093/plankt/14.3.359Open DOISearch in Google Scholar
Haykin, S. (1994). Neural Networks, A Comprehensive Foundation. MacMillan College Publishing Comp.HaykinS. (1994). . MacMillan College Publishing Comp.Search in Google Scholar
Hoang, H., Recknagel, F., Marshall, J., & Choy, S. (2001). Predictive modelling of macroinvertebrate assemblages for stream habitat assessments in Queensland (Australia). Ecological Modelling, 195, 195-206. https://doi.org/10.1016/S0304-3800(01)00306-4HoangH.RecknagelF.MarshallJ.ChoyS. (2001). Predictive modelling of macroinvertebrate assemblages for stream habitat assessments in Queensland (Australia). , 195, 195-206. https://doi.org/10.1016/S0304-3800(01)00306-4Open DOISearch in Google Scholar
Horne, A. J., & Goldman, C. R. (1994). Limnology. McGraw-Hill.HorneA. J.GoldmanC. R. (1994). . McGraw-Hill.Search in Google Scholar
Ismail, A. H., & Adnan, A. A. (2016). Zooplankton composition and abundance as indicators of eutrophication in two small man-made lakes. Tropical Life Sciences Research, 27(supp1), 31-38. https://doi.org/10.21315/tlsr2016.27.3.5 PMID:27965738IsmailA. H.AdnanA. A. (2016). Zooplankton composition and abundance as indicators of eutrophication in two small man-made lakes. , 27(supp1), 31-38. https://doi.org/10.21315/tlsr2016.27.3.5 PMID:27965738Open DOISearch in Google Scholar
Kaastra, I., & Boyd, M. (1996). Designing a neural network for forecasting fnancial and economic time series. Neurocomputing, 10(3), 215-236. https://doi.org/10.1016/0925-2312(95)00039-9KaastraI.BoydM. (1996). Designing a neural network for forecasting fnancial and economic time series. , 10(3), 215-236. https://doi.org/10.1016/0925-2312(95)00039-9Open DOISearch in Google Scholar
Karjalainen, J., Holopainen, A. L., & Huttunen, P. (1996). Spatial patterns and relationships between phytoplankton, zooplankton and water quality in the Saimaa Lake system. Hydrobiologia. https://doi.org/10.1007/978-94-009-1655-5_42KarjalainenJ.HolopainenA. L.HuttunenP. (1996). Spatial patterns and relationships between phytoplankton, zooplankton and water quality in the Saimaa Lake system. . https://doi.org/10.1007/978-94-009-1655-5_42Open DOISearch in Google Scholar
Karul, C., Soyupak, S., Cilesiz, A. F., Akbay, N., & Germen, E. (2000). Case studies on the use of neural networks in eutrophication modeling. Ecological Modelling, 134, 145-152. https://doi.org/10.1016/S0304-3800(00)00360-4KarulC.SoyupakS.CilesizA. F.AkbayN.GermenE. (2000). Case studies on the use of neural networks in eutrophication modeling. , 134, 145-152. https://doi.org/10.1016/S0304-3800(00)00360-4Open DOISearch in Google Scholar
Krenker, A., Bester, J., & Kos, A. (2011). Artificial Neural Networks-Methodological Advances and Biomedical Applications. InTech, 5, 3-18.KrenkerA.BesterJ.KosA. (2011). Artificial Neural Networks-Methodological Advances and Biomedical Applications. , 5, 3-18.Search in Google Scholar
Legendre, L., & Demers, S. (1984). Towards dynamic biological oceanography and limnology. Canadian Journal of Fisheries and Aquatic Sciences, 41,2-19. https://doi.org/10.1139/f84-001LegendreL.DemersS. (1984). Towards dynamic biological oceanography and limnology. , 41,2-19. https://doi.org/10.1139/f84-001Open DOISearch in Google Scholar
Lewis, C. D. (1982). Industrial and business forecasting methods. Butterworths.LewisC. D. (1982). . Butterworths.Search in Google Scholar
Loverde Oliveira, S. M., Huszar, V. L. M., Mazzeo, N., & Scheffer, M. (2009). Hydrology-driven regime shifts in a shallow tropical lake. Ecosystems (New York, N.Y.), 12, 807-819. https://doi.org/10.1007/s10021-009-9258-0Loverde OliveiraS. M.HuszarV. L. M.MazzeoN.SchefferM. (2009). Hydrology-driven regime shifts in a shallow tropical lake. , 12, 807-819. https://doi.org/10.1007/s10021-009-9258-0Open DOISearch in Google Scholar
Maravelias, C. D., & Reid, D. G. (1997). Identifying the effects of oceanographic features and zooplankton on prespawning herring abundance using generalized additive models. Marine Ecology Progress Series, 147, 1-9. https://doi.org/10.3354/meps147001MaraveliasC. D.ReidD. G. (1997). Identifying the effects of oceanographic features and zooplankton on prespawning herring abundance using generalized additive models. , 147, 1-9. https://doi.org/10.3354/meps147001Open DOISearch in Google Scholar
Mastrorillo, S., Lek, S., Dauba, F., & Belaud, A. (1997). The use of artificial neural networks to predict the presence of small-bodied fish in river. Freshwater Biology, 38, 237-246. https://doi.org/10.1046/j.1365-2427.1997.00209.xMastrorilloS.LekS.DaubaF.BelaudA. (1997). The use of artificial neural networks to predict the presence of small-bodied fish in river. , 38, 237-246. https://doi.org/10.1046/j.1365-2427.1997.00209.xOpen DOISearch in Google Scholar
Moss, B., Beklioglu, M., Carvalho, L., Kilinc, S., McGowan, S., & Stephen, D. (1997). Vertically-challenged limnology; contrasts between deep and shallow lakes. Springer. https://doi.org/10.1007/978-94-011-5648-6_27MossB.BekliogluM.CarvalhoL.KilincS.McGowanS.StephenD. (1997). . Springer. https://doi.org/10.1007/978-94-011-5648-6_27Open DOISearch in Google Scholar
Muylaert, K., Declerck, S., Van Wichelen, J., De Meester, L., & Vyverman, W. (2006). An evaluation of the role of daphnids in controlling phytoplankton biomass in clear water versus turbid shallow lakes. Limnologica, 36(2), 69-78. https://doi.org/10.1016/j.limno.2005.12.003MuylaertK.DeclerckS.Van WichelenJ.De MeesterL.VyvermanW. (2006). An evaluation of the role of daphnids in controlling phytoplankton biomass in clear water versus turbid shallow lakes. , 36(2), 69-78. https://doi.org/10.1016/j.limno.2005.12.003Open DOISearch in Google Scholar
Olden, J. D., & Jackson, D. A. (2002). Illuminating the “Black Box”: A Randomization Approach for Understanding Variable Contributions in Artifical Neural Networks. Ecological Modelling, 154, 135-150. https://doi.org/10.1016/S0304-3800(02)00064-9OldenJ. D.JacksonD. A. (2002). Illuminating the “Black Box”: A Randomization Approach for Understanding Variable Contributions in Artifical Neural Networks. , 154, 135-150. https://doi.org/10.1016/S0304-3800(02)00064-9Open DOISearch in Google Scholar
Ozcan, E. I., & Serdar, O. (2018). Artifical neural networks as new alternative method to estimating some population parameters of tigris loach (Oxynoemacheilus tigris (Heckel, 1843)) in the Karasu River, Turkey. Fres. Env. Bul., 27(12B), 9840-9850.OzcanE. I.SerdarO. (2018). Artifical neural networks as new alternative method to estimating some population parameters of tigris loach (Oxynoemacheilus tigris (Heckel, 1843)) in the Karasu River, Turkey. ., 27(12B), 9840-9850.Search in Google Scholar
Ozcan, E. I., & Serdar, O. (2019). Evaluation of a New Computer Method ANNs and Traditional Methods LWRs and VBGF in the Calculation of Some Growth Parameters of Two Cyprinid Species. Fres. Env. Bul., 28(10), 7644-7654.OzcanE. I.SerdarO. (2019). Evaluation of a New Computer Method ANNs and Traditional Methods LWRs and VBGF in the Calculation of Some Growth Parameters of Two Cyprinid Species. ., 28(10), 7644-7654.Search in Google Scholar
Ozcan, E. I. (2019). Artificial Neural Networks A New Statistical Approach Method in Length-Weight Relationships of Alburnus mossulensis in Murat River Palu-Elazig Turkey. Applied Ecology and Environmental Research, 17, 10253-10266. https://doi.org/10.15666/aeer/1705_1025310266OzcanE. I. (2019). Artificial Neural Networks A New Statistical Approach Method in Length-Weight Relationships of Alburnus mossulensis in Murat River Palu-Elazig Turkey. , 17, 10253-10266. https://doi.org/10.15666/aeer/1705_1025310266Open DOISearch in Google Scholar
Pinto-Coelho, R. (1998). Effects of eutrophication on seasonal patterns of mesozooplankton in a tropical reservoir: A 4-year study in Pampulha Lake, Brazil. Freshwater Biology, 40, 159-173. https://doi.org/10.1046/j.1365-2427.1998.00327.xPinto-CoelhoR. (1998). Effects of eutrophication on seasonal patterns of mesozooplankton in a tropical reservoir: A 4-year study in Pampulha Lake, Brazil. , 40, 159-173. https://doi.org/10.1046/j.1365-2427.1998.00327.xOpen DOISearch in Google Scholar
Pinel-Alloul, B., Mathot, G., Verreault, G., & Vigneault, Y. (1990). Zooplankton species associations in Quebec Lakes: Variation with abiotic factors, including natural and anthropogenic acidification. Canadian Journal of Fisheries and Aquatic Sciences, 47, 110-121. https://doi.org/10.1139/ f90-011Pinel-AlloulB.MathotG.VerreaultG.VigneaultY. (1990). Zooplankton species associations in Quebec Lakes: Variation with abiotic factors, including natural and anthropogenic acidification. , 47, 110-121. https://doi.org/10.1139/f90-011Open DOISearch in Google Scholar
Reyjol, Y., Lim, P., Belaud, A., & Lek, S. (2001). Modelling of microhabitat used by fish in natural and regulated flows in the river Garonne (France). Ecological Modelling, 146, 131-142. https://doi.org/10.1016/S0304-3800(01)00301-5ReyjolY.LimP.BelaudA.LekS. (2001). Modelling of microhabitat used by fish in natural and regulated flows in the river Garonne (France). , 146, 131-142. https://doi.org/10.1016/S0304-3800(01)00301-5Open DOISearch in Google Scholar
Ryding, S. O., & Rast, W. (1989). The Control of Eutrophicayion of Lakes and Reservoirs. Man and Biosphere Series, Parthenon Publication Group.RydingS. O.RastW. (1989). The Control of Eutrophicayion of Lakes and Reservoirs., Parthenon Publication Group.Search in Google Scholar
Saler, S. (2017). Diversity and abundance of zooplankton in Medik Reservoir of Turkey. Maejo International Journal of Science and Technology, 11 (2), 126-132.SalerS. (2017). Diversity and abundance of zooplankton in Medik Reservoir of Turkey. , 11 (2), 126-132.Search in Google Scholar
Saler, S. (1995). Cip Baraj Golu (Elazig) Rotifera Faunasinin Taksonomik Yonden Incelenmesi [In Turkish]. Firat UniversitesiFen ve Muhendislik Bilimleri Dergisi, 12, 329-337.SalerS. (1995). Cip Baraj Golu (Elazig) Rotifera Faunasinin Taksonomik Yonden Incelenmesi [In Turkish]. , 12, 329-337.Search in Google Scholar
Schleiter, I. M., Borchardt, D., Wagner, R., Dapper, T., Schmidt, K. D., Schmidt, H. H., & Werne, R. H. (1999). Modelling water quality, bioindication and population dynamics in lotic ecosystems using neural network. Ecological Modelling, 120, 271-286. https://doi.org/10.1016/S0304-3800(99)00108-8SchleiterI. M.BorchardtD.WagnerR.DapperT.SchmidtK. D.SchmidtH. H.WerneR. H. (1999). Modelling water quality, bioindication and population dynamics in lotic ecosystems using neural network. , 120, 271-286. https://doi.org/10.1016/S0304-3800(99)00108-8Open DOISearch in Google Scholar
Sharda, R., & Patil, R. B. (1992). Connectionist approach to time series prediction: An empirical test. Journal of Intelligent Manufacturing, 3, 317-323. https://doi.org/10.1007/ BF01577272ShardaR.PatilR. B. (1992). Connectionist approach to time series prediction: An empirical test. , 3, 317-323. https://doi.org/10.1007/BF01577272Open DOISearch in Google Scholar
Sousa, W., Attayde, J. L., Rocha, E. D. S., & Eskinazi-Sant Anna, E. M. (2008). The response of zooplankton assemblages to variations in the water quality of four man-made lakes in semi-arid northeastern. Brazil. Journal of Plankton Research, 30(6), 699-708. https://doi.org/10.1093/plankt/ fbn032SousaW.AttaydeJ. L.RochaE. D. S.Eskinazi-Sant AnnaE. M. (2008). The response of zooplankton assemblages to variations in the water quality of four man-made lakes in semi-arid northeastern. , 30(6), 699-708. https://doi.org/10.1093/plankt/fbn032Open DOISearch in Google Scholar
Sagiroglu, S., Besdok, E., & Erler, M. (2003). Muhendislikte yapay zeka uygulamalari I, Yapay Sinir Aglari, Ufuk Kitap Kirtasiye-Yayincilik Tic. Ltd.Sti. (In Turkish)SagirogluS.BesdokE.ErlerM. (2003). , Ufuk Kitap Kirtasiye-Yayincilik Tic. Ltd.Sti. (In Turkish)Search in Google Scholar
Tanyolac, J. (2009). Limnoloji. Hatiboglu Basimevi. (In Turkish) URL. 2023 https://tr.wikipedia.org/wiki/Cip_Baraj%C4%B1 [Accessed 20 May 2023]TanyolacJ. (2009). . (In Turkish) URL. 2023 https://tr.wikipedia.org/wiki/Cip_Baraj%C4%B1 [Accessed 20 May 2023]Search in Google Scholar