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ESTIMATION OF FORMALDEHYDE EMISSIONS OF PLYWOOD TREATED WITH FIRE RETARDANT CHEMICALS BY ARTIFICIAL NEURAL NETWORK

Year 2021, Volume: 5 Issue: 2, 352 - 365, 31.10.2021
https://doi.org/10.32328/turkjforsci.902897

Abstract

Fire-retardant chemicals cause different effects on the physical, mechanical and some technological properties of materials which they are applied to. These effects may vary depending on retention amounts and concentration of solutions. In this study, it was aimed to determine the effects of solution concentration and retention level on formaldehyde emission release of plywood treated with fire retardant chemicals using ANN modelling. Based on this, firstly, the retention level estimation model with ANN was developed to examine the effects of wood type, fire retardant chemical type and solution concentration on the retention level. Then, the effects of wood type, fire retardant chemical type, solution concentration and retention level on the formaldehyde emission of plywood were investigated with the formaldehyde emission estimation model developed with ANN. In experimental studies, poplar, alder and scots pine were used as wood species while zinc borate, monoammonium phosphate and ammonium sulphate were used as fire-retardant chemicals. The veneer sheets were treated with immersion method and chosen three different concentrations as 5%, 7% and 10% aqueous solutions. Formaldehyde emission contents of plywood panels were determined according to flask method described in DIN EN 717-3 standard. The prediction models with the best performance and acceptable deviations were determined by using statistical and graphical comparisons between the experimental data and the prediction values obtained as a result of ANN analysis. Then, using these prediction models, the retention level and formaldehyde emission values were estimated for intermediate solution concentrations (6%, 8% and 9%), which were not experimentally tested. According to ANN analysis results, while retention levels continued to increase at these intermediate values, formaldehyde emission values increased and decreased similarly in all three wood species.

References

  • Antanasijević, D. Z., Pocajt, V. V., Povrenović, D. S., Ristić, M. Đ., & Perić-Grujić, A. A. (2013) PM10 emission forecasting using artificial neural networks and genetic algorithm input variable optimization. Science of the Total Environment, 443, 511-519.
  • Aydin, I., & Colakoglu, G. (2007) Variation in surface roughness, wettability and some plywood properties after preservative treatment with boron compounds. Building and Environment, 42(11), 3837-3840.
  • Bekhta, P., Sedliačik, J., Noshchenko, G., Kačík, F., & Bekhta, N. (2021) Characteristics of beech bark and its effect on properties of UF adhesive and on bonding strength and formaldehyde emission of plywood panels. European Journal of Wood and Wood Products, 1-11.
  • Bryn, O., Bekhta, P., Sedliačik, J., Forosz, V., & Galysh, V. (2016) The effect of diffusive impregnation of birch veneers with fire retardant on plywood properties. BioResources, 11(4), 9112-9125.
  • Cheng, R. X., & Wang, Q. W. (2011) The influence of FRW-1 fire retardant treatment on the bonding of plywood. Journal of Adhesion Science and Technology, 25(14), 1715-1724.
  • Çolak, S., & Colakoglu, G. (2004) Volatile acetic acid and formaldehyde emission from plywood treated with boron compound. Building and Environment, 39(5), 533-536.
  • Costa, N. A., Pereira, J., Ferra, J., Cruz, P., Martins, J., Magalhães, F. D., ... & Carvalho, L. H. (2013) Scavengers for achieving zero formaldehyde emission of wood-based panels. Wood science and technology, 47(6), 1261-1272.
  • Demir, A., Aydin, I., & Colak, S. (2017) Effect of various fire retardant chemicals in different concentrations on formaldehyde emission of plywood. Kastamonu Üniversitesi Orman Fakültesi Dergisi, 17(3), 509-516.
  • Demir, A., Aydin, İ., & Öztürk H. (2014) Effect of fire retardant chemicals on formaldehyde emission of plywood. 25th International Scientific Conference New Materials and Technologies in the Function of Wooden Products (17 October), 63-66, Zagreb, Croatia.
  • Demirkir, C., Özsahin, Ş., Aydin, I., & Colakoglu, G. (2013) Optimization of some panel manufacturing parameters for the best bonding strength of plywood. International Journal of Adhesion and Adhesives, 46, 14-20.
  • DIN EN 717-3, (1996) Wood-based panel products - Determination of formaldehyde release by the flask method.
  • Dunky, M. (2003) Adhesives in the wood industry. In: Pizzi A, Mittal KL (eds) Handbook of adhesive technology, 2nd edn., p 71Marcel Dekker Inc., New York.
  • Esteban, L. G., Fernández, F. G., & de Palacios, P. (2011) Prediction of plywood bonding quality using an artificial neural network. Holzforschung, 65(2), 209-214.
  • Fernández, F. G., Esteban, L. G., Palacios, P. D., Navaro, N., & Conde, M. (2008) Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model. Investigación agraria: Sistemas y recursos forestales, 17(2), 178-187.
  • Gangi, M., Tabarsa, T., Sepahvand, S., & Asghari, J. (2013) Reduction of formaldehyde emission from plywood. Journal of adhesion science and technology, 27(13), 1407-1417.
  • Gui, C., Zhu, J., Zhang, Z., & Liu, X. (2016) Research progress on formaldehyde- free wood adhesive derived from soy flour. In: Rudawska A (ed) Adhesives—applications and properties. IntechOpen.
  • Hodgson, A. T., Beal, D., & McIlvaine, J. E. R. (2002) Sources of formaldehyde, other aldehydes and terpenes in a new manufactured house. Indoor Air, 12(4), 235-242.
  • IARC (2006) Formaldehyde, 2-butoxyethanol and 1-tert-butoxypropan- 2-ol. In: Monographs on the Evaluation of carcinogenic risk to humans; world health organization international agency for research on cancer: Lyon, France, 2006, vol 88, p 478.
  • Junyou, S., & Shengyou, Y. (2010) Effects of addition ammonia modified urea-melamine -formaldehyde resin on the adhesions and formaldehyde emission in plywood. Environment Materials and Environment Management PTS 1-3. Book Series: Advanced Materials Research, 113-116, 1226-1229.
  • Kim, S. (2009) Environment-friendly adhesives for surface bonding of wood-based flooring using natural tannin to reduce formaldehyde and TVOC emission. Bioresource technology, 100(2), 744-748.
  • Küçükönder, H., Boyaci, S., & Akyüz, A. (2016) A modeling study with an artificial neural network: developing estimationmodels for the tomato plant leaf area. Turkish Journal of Agriculture and Forestry, 40(2), 203-212.
  • Łebkowska, M., Załęska-Radziwiłł, M., & Tabernacka, A. (2017) Adhesives based on formaldehyde–environmental problems. BioTechnologia, 98(1), 53-65.
  • Moubarik, A., Allal, A., Pizzi, A., Charrier, F., & Charrier, B. (2010) Characterization of a formaldehyde-free cornstarch-tannin wood adhesive for interior plywood. European Journal of Wood and Wood Products, 68(4), 427-433.
  • Myers, G. E. (1984) How mole ratio of UF resin affects formaldehyde emission and other properties: a literature critique. Forest products journal, 34(5), 35-41.
  • Myers, G. E. (1986) Effects of post-manufacture board treatments on formaldehyde emission: A literature review (1960-1984). Forest products journal, 36(6), 41-51.
  • Özşahin, Ş. (2012) The use of an artificial neural network for modeling the moisture absorption and thickness swelling of oriented strand board. BioResources, 7(1), 1053-1067.
  • Ozsahin, S., & Aydin, I. (2014) Prediction of the optimum veneer drying temperature for good bonding in plywood manufacturing by means of artificial neural network. Wood science and technology, 48(1), 59-70.
  • Ozsahin, S., & Murat, M. (2018) Prediction of equilibrium moisture content and specific gravity of heat treated wood by artificial neural networks. European journal of wood and wood products, 76(2), 563-572.
  • Roffael, E. (1982) Die Formaldehydabgabe von Spanplatten und anderen Werkstoffen [The release of formaldehyde from particleboards and other materials]. DRW, Stuttgart.
  • Rowell, R.M. (2005) Handbook of chemistry and wood composites. CRC Press, Boca Raton, 446 pp.
  • Salca, E. A., Bekhta, P., & Seblii, Y. (2020) The effect of veneer densification temperature and wood species on the plywood properties made from alternate layers of densified and non-densified veneers. Forests, 11(6), 700.
  • Schröder, K., Meyer‐Plath, A., Keller, D., Besch, W., Babucke, G., & Ohl, A. (2001) Plasma‐induced surface functionalization of polymeric biomaterials in ammonia plasma. Contributions to Plasma Physics, 41(6), 562-572.
  • Su, W. Y., Hata, T., Nishimiya, K., Imamura, Y., & Ishihara, S. (1998) Improvement of fire retardancy of plywood by incorporating boron or phosphate compounds in the glue. Journal of wood science, 44(2), 131-136.
  • Taşpınar, F., & Bozkurt, Z. (2014) Application of artificial neural networks and regression models in the prediction of daily maximum PM10 concentration in Düzce, Turkey. Fresenius Environ. Bull, 23, 2450-2459.
  • The Food and Agriculture Organization (FAO), (2021). FAOSTAT-FAO Statics Division - Production Quantity/Plywood. http://faostat3.fao.org/browse/F/FO/E.
  • Tiryaki, S., Bardak, S., & Aydın, A. (2016) Modeling of wood bonding strength based on soaking temperature and soaking time by means of artificial neural networks. International Journal of Intelligent Systems and Applications in Engineering, 153-157.
  • Tiryaki, S., Özşahin, Ş., & Aydın, A. (2017) Employing artificial neural networks for minimizing surface roughness and power consumption in abrasive machining of wood. European Journal of Wood and Wood Products, 75(3), 347-358.
  • Ustaömer, D. (2008) Çeşitli yanmayı geciktirici kimyasal maddelerle muamele edilerek üretilmiş orta yoğunluktaki liflevhaların (MDF) özelliklerindeki değişimlerin belirlenmesi, K.T.Ü., Fen Bilimleri Enstitüsü, Doktora Tezi, Trabzon, 1 s.
  • Varol, T., Canakci, A., & Ozsahin, S. (2018) Prediction of effect of reinforcement content, flake size and flake time on the density and hardness of flake AA2024-SiC nanocomposites using neural networks. Journal of Alloys and Compounds, 739, 1005-1014.
  • Wang, W., Zammarano, M., Shields, J. R., Knowlton, E. D., Kim, I., Gales, J. A., ... & Li, J. (2018) A novel application of silicone-based flame-retardant adhesive in plywood. Construction and Building Materials, 189, 448-459.
  • Wang, Y., & Zhao, J. (2018) Preliminary study on decanoic/palmitic eutectic mixture modified silica fume geopolymer-based coating for flame retardant plywood. Construction and Building Materials, 189, 1-7.
  • Wen, H. C., Yang, K., Ou, K. L., Wu, W. F., Chou, C. P., Luo, R. C., & Chang, Y. M. (2006) Effects of ammonia plasma treatment on the surface characteristics of carbon fibers. Surface and Coatings Technology, 200(10), 3166-3169.
  • Wu, M., Song, W., Wu, Y., & Qu, W. (2020) Preparation and characterization of the flame-retardant decorated plywood based on the intumescent flame retardant adhesive. Materials, 13(3), 676.
  • Yadav, V., & Nath, S. (2017) Forecasting of PM 10 Using Autoregressive Models and Exponential Smoothing Technique. Asian Journal of Water, Environment and Pollution, 14(4), 109-113.
  • Zhang, H., Liu, J., & Lu, X. (2013) Reducing the formaldehyde emission of composite wood products by cold plasma treatment. Wood Research, 58(4), 607-616.

YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ

Year 2021, Volume: 5 Issue: 2, 352 - 365, 31.10.2021
https://doi.org/10.32328/turkjforsci.902897

Abstract

Yangın geciktirici kimyasallar, uygulanmış oldukları malzemelerin fiziksel, mekanik ve diğer bazı teknolojik özellikleri üzerinde farklı etkilere neden olmaktadır. Bu etkiler, çözeltilerin konsantrasyon miktarlarına ve retensiyon miktarlarına bağlı olarak değişim gösterebilmektedir. Bu çalışmada, YSA modellemesi kullanılarak yangın geciktirici kimyasallarla emprenye edilmiş kontrplakların formaldehit emisyon salınımları üzerine çözelti konsantrasyon ve retensiyon miktarlarının etkilerinin belirlenmesi amaçlanmıştır. Bundan yola çıkarak, ilk olarak, ağaç türü, yangın geciktirici kimyasal türü ve çözelti konsantrasyonunun retensiyon miktarı üzerine etkilerini incelemek için YSA ile retensiyon miktarı tahmin modeli geliştirilmiştir. Daha sonra, ağaç türü, yangın geciktirici kimyasal türü, çözelti konsantrasyonu ve retensiyon miktarının kontrplakların formaldehit emisyonu üzerine etkileri YSA ile geliştirilen formaldehit emisyon değerleri tahmin modeliyle araştırılmıştır. Deneysel çalışmalarda, ağaç türü olarak, kavak, kızılağaç ve sarıçam, yangın geciktirici kimyasal olarak da çinko borat, monoamonyum fosfat ve amonyum sülfat kullanılmıştır. Kaplama levhaları daldırma metoduna göre emprenye edilmiş ve %5, %7 ve %10 olmak üzere üç farklı çözelti konsantrasyonları seçilmiştir. Kontrplak levhalarının formaldehit emisyon ölçümleri DIN EN 717-3 standardındaki şişe yöntemine göre belirlenmiştir. Deneysel olarak elde edilen veriler ile YSA analizleri sonucunda elde edilen tahmin değerleri hem istatistiksel hem de grafiksel karşılaştırmalar kullanılarak, en iyi performansa ve kabul edilebilir sapmalara sahip tahmin modelleri belirlenmiştir. Daha sonra, bu tahmin modelleri kullanılarak, retensiyon miktarı ve formaldehit emisyon değerleri deneysel olarak testi yapılmayan ara çözelti konsantrasyon değerleri (%6, %8 ve %9) için tahmin edilmiştir. YSA analiz sonuçlarına göre, belirlenen bu ara değerlerde retensiyon miktarları artmaya devam ederken, formaldehit emisyon değerleri her üç ağaç türünde de benzer şekilde artış ve azalış göstermiştir.

References

  • Antanasijević, D. Z., Pocajt, V. V., Povrenović, D. S., Ristić, M. Đ., & Perić-Grujić, A. A. (2013) PM10 emission forecasting using artificial neural networks and genetic algorithm input variable optimization. Science of the Total Environment, 443, 511-519.
  • Aydin, I., & Colakoglu, G. (2007) Variation in surface roughness, wettability and some plywood properties after preservative treatment with boron compounds. Building and Environment, 42(11), 3837-3840.
  • Bekhta, P., Sedliačik, J., Noshchenko, G., Kačík, F., & Bekhta, N. (2021) Characteristics of beech bark and its effect on properties of UF adhesive and on bonding strength and formaldehyde emission of plywood panels. European Journal of Wood and Wood Products, 1-11.
  • Bryn, O., Bekhta, P., Sedliačik, J., Forosz, V., & Galysh, V. (2016) The effect of diffusive impregnation of birch veneers with fire retardant on plywood properties. BioResources, 11(4), 9112-9125.
  • Cheng, R. X., & Wang, Q. W. (2011) The influence of FRW-1 fire retardant treatment on the bonding of plywood. Journal of Adhesion Science and Technology, 25(14), 1715-1724.
  • Çolak, S., & Colakoglu, G. (2004) Volatile acetic acid and formaldehyde emission from plywood treated with boron compound. Building and Environment, 39(5), 533-536.
  • Costa, N. A., Pereira, J., Ferra, J., Cruz, P., Martins, J., Magalhães, F. D., ... & Carvalho, L. H. (2013) Scavengers for achieving zero formaldehyde emission of wood-based panels. Wood science and technology, 47(6), 1261-1272.
  • Demir, A., Aydin, I., & Colak, S. (2017) Effect of various fire retardant chemicals in different concentrations on formaldehyde emission of plywood. Kastamonu Üniversitesi Orman Fakültesi Dergisi, 17(3), 509-516.
  • Demir, A., Aydin, İ., & Öztürk H. (2014) Effect of fire retardant chemicals on formaldehyde emission of plywood. 25th International Scientific Conference New Materials and Technologies in the Function of Wooden Products (17 October), 63-66, Zagreb, Croatia.
  • Demirkir, C., Özsahin, Ş., Aydin, I., & Colakoglu, G. (2013) Optimization of some panel manufacturing parameters for the best bonding strength of plywood. International Journal of Adhesion and Adhesives, 46, 14-20.
  • DIN EN 717-3, (1996) Wood-based panel products - Determination of formaldehyde release by the flask method.
  • Dunky, M. (2003) Adhesives in the wood industry. In: Pizzi A, Mittal KL (eds) Handbook of adhesive technology, 2nd edn., p 71Marcel Dekker Inc., New York.
  • Esteban, L. G., Fernández, F. G., & de Palacios, P. (2011) Prediction of plywood bonding quality using an artificial neural network. Holzforschung, 65(2), 209-214.
  • Fernández, F. G., Esteban, L. G., Palacios, P. D., Navaro, N., & Conde, M. (2008) Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model. Investigación agraria: Sistemas y recursos forestales, 17(2), 178-187.
  • Gangi, M., Tabarsa, T., Sepahvand, S., & Asghari, J. (2013) Reduction of formaldehyde emission from plywood. Journal of adhesion science and technology, 27(13), 1407-1417.
  • Gui, C., Zhu, J., Zhang, Z., & Liu, X. (2016) Research progress on formaldehyde- free wood adhesive derived from soy flour. In: Rudawska A (ed) Adhesives—applications and properties. IntechOpen.
  • Hodgson, A. T., Beal, D., & McIlvaine, J. E. R. (2002) Sources of formaldehyde, other aldehydes and terpenes in a new manufactured house. Indoor Air, 12(4), 235-242.
  • IARC (2006) Formaldehyde, 2-butoxyethanol and 1-tert-butoxypropan- 2-ol. In: Monographs on the Evaluation of carcinogenic risk to humans; world health organization international agency for research on cancer: Lyon, France, 2006, vol 88, p 478.
  • Junyou, S., & Shengyou, Y. (2010) Effects of addition ammonia modified urea-melamine -formaldehyde resin on the adhesions and formaldehyde emission in plywood. Environment Materials and Environment Management PTS 1-3. Book Series: Advanced Materials Research, 113-116, 1226-1229.
  • Kim, S. (2009) Environment-friendly adhesives for surface bonding of wood-based flooring using natural tannin to reduce formaldehyde and TVOC emission. Bioresource technology, 100(2), 744-748.
  • Küçükönder, H., Boyaci, S., & Akyüz, A. (2016) A modeling study with an artificial neural network: developing estimationmodels for the tomato plant leaf area. Turkish Journal of Agriculture and Forestry, 40(2), 203-212.
  • Łebkowska, M., Załęska-Radziwiłł, M., & Tabernacka, A. (2017) Adhesives based on formaldehyde–environmental problems. BioTechnologia, 98(1), 53-65.
  • Moubarik, A., Allal, A., Pizzi, A., Charrier, F., & Charrier, B. (2010) Characterization of a formaldehyde-free cornstarch-tannin wood adhesive for interior plywood. European Journal of Wood and Wood Products, 68(4), 427-433.
  • Myers, G. E. (1984) How mole ratio of UF resin affects formaldehyde emission and other properties: a literature critique. Forest products journal, 34(5), 35-41.
  • Myers, G. E. (1986) Effects of post-manufacture board treatments on formaldehyde emission: A literature review (1960-1984). Forest products journal, 36(6), 41-51.
  • Özşahin, Ş. (2012) The use of an artificial neural network for modeling the moisture absorption and thickness swelling of oriented strand board. BioResources, 7(1), 1053-1067.
  • Ozsahin, S., & Aydin, I. (2014) Prediction of the optimum veneer drying temperature for good bonding in plywood manufacturing by means of artificial neural network. Wood science and technology, 48(1), 59-70.
  • Ozsahin, S., & Murat, M. (2018) Prediction of equilibrium moisture content and specific gravity of heat treated wood by artificial neural networks. European journal of wood and wood products, 76(2), 563-572.
  • Roffael, E. (1982) Die Formaldehydabgabe von Spanplatten und anderen Werkstoffen [The release of formaldehyde from particleboards and other materials]. DRW, Stuttgart.
  • Rowell, R.M. (2005) Handbook of chemistry and wood composites. CRC Press, Boca Raton, 446 pp.
  • Salca, E. A., Bekhta, P., & Seblii, Y. (2020) The effect of veneer densification temperature and wood species on the plywood properties made from alternate layers of densified and non-densified veneers. Forests, 11(6), 700.
  • Schröder, K., Meyer‐Plath, A., Keller, D., Besch, W., Babucke, G., & Ohl, A. (2001) Plasma‐induced surface functionalization of polymeric biomaterials in ammonia plasma. Contributions to Plasma Physics, 41(6), 562-572.
  • Su, W. Y., Hata, T., Nishimiya, K., Imamura, Y., & Ishihara, S. (1998) Improvement of fire retardancy of plywood by incorporating boron or phosphate compounds in the glue. Journal of wood science, 44(2), 131-136.
  • Taşpınar, F., & Bozkurt, Z. (2014) Application of artificial neural networks and regression models in the prediction of daily maximum PM10 concentration in Düzce, Turkey. Fresenius Environ. Bull, 23, 2450-2459.
  • The Food and Agriculture Organization (FAO), (2021). FAOSTAT-FAO Statics Division - Production Quantity/Plywood. http://faostat3.fao.org/browse/F/FO/E.
  • Tiryaki, S., Bardak, S., & Aydın, A. (2016) Modeling of wood bonding strength based on soaking temperature and soaking time by means of artificial neural networks. International Journal of Intelligent Systems and Applications in Engineering, 153-157.
  • Tiryaki, S., Özşahin, Ş., & Aydın, A. (2017) Employing artificial neural networks for minimizing surface roughness and power consumption in abrasive machining of wood. European Journal of Wood and Wood Products, 75(3), 347-358.
  • Ustaömer, D. (2008) Çeşitli yanmayı geciktirici kimyasal maddelerle muamele edilerek üretilmiş orta yoğunluktaki liflevhaların (MDF) özelliklerindeki değişimlerin belirlenmesi, K.T.Ü., Fen Bilimleri Enstitüsü, Doktora Tezi, Trabzon, 1 s.
  • Varol, T., Canakci, A., & Ozsahin, S. (2018) Prediction of effect of reinforcement content, flake size and flake time on the density and hardness of flake AA2024-SiC nanocomposites using neural networks. Journal of Alloys and Compounds, 739, 1005-1014.
  • Wang, W., Zammarano, M., Shields, J. R., Knowlton, E. D., Kim, I., Gales, J. A., ... & Li, J. (2018) A novel application of silicone-based flame-retardant adhesive in plywood. Construction and Building Materials, 189, 448-459.
  • Wang, Y., & Zhao, J. (2018) Preliminary study on decanoic/palmitic eutectic mixture modified silica fume geopolymer-based coating for flame retardant plywood. Construction and Building Materials, 189, 1-7.
  • Wen, H. C., Yang, K., Ou, K. L., Wu, W. F., Chou, C. P., Luo, R. C., & Chang, Y. M. (2006) Effects of ammonia plasma treatment on the surface characteristics of carbon fibers. Surface and Coatings Technology, 200(10), 3166-3169.
  • Wu, M., Song, W., Wu, Y., & Qu, W. (2020) Preparation and characterization of the flame-retardant decorated plywood based on the intumescent flame retardant adhesive. Materials, 13(3), 676.
  • Yadav, V., & Nath, S. (2017) Forecasting of PM 10 Using Autoregressive Models and Exponential Smoothing Technique. Asian Journal of Water, Environment and Pollution, 14(4), 109-113.
  • Zhang, H., Liu, J., & Lu, X. (2013) Reducing the formaldehyde emission of composite wood products by cold plasma treatment. Wood Research, 58(4), 607-616.
There are 45 citations in total.

Details

Primary Language Turkish
Subjects Timber, Pulp and Paper
Journal Section Research Article
Authors

Aydın Demir 0000-0003-4060-2578

İsmail Aydın 0000-0003-0152-7501

Publication Date October 31, 2021
Published in Issue Year 2021 Volume: 5 Issue: 2

Cite

APA Demir, A., & Aydın, İ. (2021). YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ. Turkish Journal of Forest Science, 5(2), 352-365. https://doi.org/10.32328/turkjforsci.902897
AMA Demir A, Aydın İ. YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ. Turk J For Sci. October 2021;5(2):352-365. doi:10.32328/turkjforsci.902897
Chicago Demir, Aydın, and İsmail Aydın. “YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ”. Turkish Journal of Forest Science 5, no. 2 (October 2021): 352-65. https://doi.org/10.32328/turkjforsci.902897.
EndNote Demir A, Aydın İ (October 1, 2021) YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ. Turkish Journal of Forest Science 5 2 352–365.
IEEE A. Demir and İ. Aydın, “YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ”, Turk J For Sci, vol. 5, no. 2, pp. 352–365, 2021, doi: 10.32328/turkjforsci.902897.
ISNAD Demir, Aydın - Aydın, İsmail. “YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ”. Turkish Journal of Forest Science 5/2 (October 2021), 352-365. https://doi.org/10.32328/turkjforsci.902897.
JAMA Demir A, Aydın İ. YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ. Turk J For Sci. 2021;5:352–365.
MLA Demir, Aydın and İsmail Aydın. “YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ”. Turkish Journal of Forest Science, vol. 5, no. 2, 2021, pp. 352-65, doi:10.32328/turkjforsci.902897.
Vancouver Demir A, Aydın İ. YANGIN GECİKTİRİCİ KİMYASALLARLA EMPRENYE EDİLMİŞ KONTRPLAKLARIN FORMALDEHİT EMİSYONLARININ YAPAY SİNİR AĞLARI İLE TAHMİNİ. Turk J For Sci. 2021;5(2):352-65.