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Volumn 25, Issue 12, 2010, Pages 1857-1865

Filling gaps in diameter measurements on standing tree boles in the urban forest of Thessaloniki, Greece

Author keywords

Back propagation; Cascade correlation; Diameter measurements; Kalman learning rule; Neural networks; Pine tree

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; CASCADE CORRELATION; DIAMETER MEASUREMENT; DIAMETER MEASUREMENTS; ENVIRONMENTAL APPLICATIONS; FILLING GAPS; FOREST MANAGEMENT; INCOMPLETE DATA; LEARNING RULES; MISSING DATA; MISSING DATA ESTIMATION; MISSING DATA PROBLEM; MISSING VALUES; NEW APPROACHES; PINE TREES; PRIMARY DATA; STANDING TREE; STATISTICAL PROBLEMS; THESSALONIKI , GREECE; URBAN FORESTS;

EID: 84555192942     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2010.04.020     Document Type: Article
Times cited : (24)

References (56)
  • 1
    • 67349276109 scopus 로고    scopus 로고
    • The relative utility of regression and artificial neural networks models for rapidly predicting the capacity of water supply reservoirs
    • Adeloye A. The relative utility of regression and artificial neural networks models for rapidly predicting the capacity of water supply reservoirs. Environ. Modell. Softw. 2009, 24:1233-1240.
    • (2009) Environ. Modell. Softw. , vol.24 , pp. 1233-1240
    • Adeloye, A.1
  • 2
    • 36148953966 scopus 로고    scopus 로고
    • Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone
    • Al-Alawi S.M., Abdul-Wahab S.A., Bakheit C.S. Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone. Environ. Modell. Softw. 2008, 23(4):396-403.
    • (2008) Environ. Modell. Softw. , vol.23 , Issue.4 , pp. 396-403
    • Al-Alawi, S.M.1    Abdul-Wahab, S.A.2    Bakheit, C.S.3
  • 3
    • 33749332287 scopus 로고    scopus 로고
    • Wood dielectric loss factor prediction with artificial neural networks
    • Avramidis S., Iliadis L., Mansfield S.D. Wood dielectric loss factor prediction with artificial neural networks. Wood Sci. Technol. 2006, 40(7):563-574.
    • (2006) Wood Sci. Technol. , vol.40 , Issue.7 , pp. 563-574
    • Avramidis, S.1    Iliadis, L.2    Mansfield, S.D.3
  • 4
    • 34250690403 scopus 로고    scopus 로고
    • Artificial neural network and mathematical modeling comparative analysis of nonisothermal diffusion of moisture in wood
    • Avramidis S., Wu H. Artificial neural network and mathematical modeling comparative analysis of nonisothermal diffusion of moisture in wood. Holz Als Roh-und Werkst 2007, 65:89-93.
    • (2007) Holz Als Roh-und Werkst , vol.65 , pp. 89-93
    • Avramidis, S.1    Wu, H.2
  • 5
    • 0000334686 scopus 로고
    • How to develop neural-networks applications
    • Bailey R.L., Thompson D. How to develop neural-networks applications. AI Expert 1990, S(6):38-47.
    • (1990) AI Expert , vol.S , Issue.6 , pp. 38-47
    • Bailey, R.L.1    Thompson, D.2
  • 6
    • 0034564603 scopus 로고    scopus 로고
    • Artificial neural networks: fundamentals, computing, design, and application
    • Basheer I.A., Hajmeer M. Artificial neural networks: fundamentals, computing, design, and application. J. Microbiol. Methods 2000, 43:3-31.
    • (2000) J. Microbiol. Methods , vol.43 , pp. 3-31
    • Basheer, I.A.1    Hajmeer, M.2
  • 7
    • 0028468293 scopus 로고
    • Using mutual information for selecting features in supervised neural netwopk learning
    • Battiti R. Using mutual information for selecting features in supervised neural netwopk learning. IEEE Trans. Neural Networks 1995, 5:537-550.
    • (1995) IEEE Trans. Neural Networks , vol.5 , pp. 537-550
    • Battiti, R.1
  • 8
    • 57649221780 scopus 로고    scopus 로고
    • Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks
    • Behzadian K., Kapelan Z., Savic D., Ardeshir A. Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks. Environ. Modell. Softw. 2009, 24(4):530-541.
    • (2009) Environ. Modell. Softw. , vol.24 , Issue.4 , pp. 530-541
    • Behzadian, K.1    Kapelan, Z.2    Savic, D.3    Ardeshir, A.4
  • 9
    • 0033400675 scopus 로고    scopus 로고
    • Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables
    • Blackard J., Dean D. Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables. Comput. Electron. Agric. 1999, 24:131-151.
    • (1999) Comput. Electron. Agric. , vol.24 , pp. 131-151
    • Blackard, J.1    Dean, D.2
  • 11
    • 2642576811 scopus 로고    scopus 로고
    • Predicting forest attributes in southeast Alaska using artificial neural networks
    • Corne S.A., Carver S.J., Kunin W.E., Lennon J.J., Van Hees W.W.S. Predicting forest attributes in southeast Alaska using artificial neural networks. For. Sci. 2004, 50:259-276.
    • (2004) For. Sci. , vol.50 , pp. 259-276
    • Corne, S.A.1    Carver, S.J.2    Kunin, W.E.3    Lennon, J.J.4    Van Hees, W.W.S.5
  • 12
    • 77956545822 scopus 로고    scopus 로고
    • Neural network toolbox. For use with Matlab®, User's Guide, V4.
    • Demuth, H., Beale, M., 2001. Neural network toolbox. For use with Matlab®, User's Guide, V4.
    • (2001)
    • Demuth, H.1    Beale, M.2
  • 13
    • 22544487549 scopus 로고    scopus 로고
    • Artificial neural networks as an alternative tool in pine bark volume estimation
    • Diamantopoulou M.J. Artificial neural networks as an alternative tool in pine bark volume estimation. Comput. Electron. Agric. 2005, 48:235-244.
    • (2005) Comput. Electron. Agric. , vol.48 , pp. 235-244
    • Diamantopoulou, M.J.1
  • 14
    • 77956531788 scopus 로고    scopus 로고
    • Tree-bole volume estimation on standing pine trees using cascade correlation artificial neural network models
    • Diamantopoulou M.J. Tree-bole volume estimation on standing pine trees using cascade correlation artificial neural network models. Agric. Eng. Inter. CIGR J. Sci. Res. Develop. 2006, 8:1-14.
    • (2006) Agric. Eng. Inter. CIGR J. Sci. Res. Develop. , vol.8 , pp. 1-14
    • Diamantopoulou, M.J.1
  • 15
    • 38049027371 scopus 로고    scopus 로고
    • Performance of neural network models with Kalman learning rule for flow routing in a river system
    • Diamantopoulou M.J., Georgiou P., Papamichail D.M. Performance of neural network models with Kalman learning rule for flow routing in a river system. Fresen. Environ. Bull. 2007, 16(11b):1474-1484.
    • (2007) Fresen. Environ. Bull. , vol.16 , Issue.11 B , pp. 1474-1484
    • Diamantopoulou, M.J.1    Georgiou, P.2    Papamichail, D.M.3
  • 16
    • 77956544600 scopus 로고
    • Solving problems in environmental engineering and geosciences with artificial neural networks. Massachusetts, USA.
    • Dowla, U.F., Rogers, L., 1995. Solving problems in environmental engineering and geosciences with artificial neural networks. Massachusetts, USA.
    • (1995)
    • Dowla, U.F.1    Rogers, L.2
  • 18
    • 70449375185 scopus 로고    scopus 로고
    • The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases
    • Eskelson B., Temesgen H., Lemay V., Barrett T., Crookston N., Hudak A. The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases. Scand. J. Forest Res. 2009, 24:235-246.
    • (2009) Scand. J. Forest Res. , vol.24 , pp. 235-246
    • Eskelson, B.1    Temesgen, H.2    Lemay, V.3    Barrett, T.4    Crookston, N.5    Hudak, A.6
  • 19
    • 0000155950 scopus 로고
    • The cascade correlation learning architecture
    • Morgan Kaufmann, San Mateo, CA, D.S. Touretsky (Ed.)
    • Fahlman S.E., Lebiere C. The cascade correlation learning architecture. Advances in Neural Information Processing Systems 2 1990, 524-532. Morgan Kaufmann, San Mateo, CA. D.S. Touretsky (Ed.).
    • (1990) Advances in Neural Information Processing Systems 2 , pp. 524-532
    • Fahlman, S.E.1    Lebiere, C.2
  • 24
    • 77956498404 scopus 로고
    • Kolmogorov's mapping neural network existence theorem. In: Proceedings of IEEE international Conference on systems Engineering, Dayton
    • Hecht-Nielsen, R., 1987. Kolmogorov's mapping neural network existence theorem. In: Proceedings of IEEE international Conference on systems Engineering, Dayton, pp. 277-280.
    • (1987) , pp. 277-280
    • Hecht-Nielsen, R.1
  • 25
    • 0004199140 scopus 로고
    • Addison-Wesely Publishing Company, Reading, MA
    • Hecht-Nielsen R. Neurocomputing 1990, Addison-Wesely Publishing Company, Reading, MA.
    • (1990) Neurocomputing
    • Hecht-Nielsen, R.1
  • 26
    • 0000528136 scopus 로고    scopus 로고
    • A review of current software for handling missing data
    • Hox J.J. A review of current software for handling missing data. Kwantitatieve Methoden 1999, 62:123-138.
    • (1999) Kwantitatieve Methoden , vol.62 , pp. 123-138
    • Hox, J.J.1
  • 27
    • 33846820421 scopus 로고    scopus 로고
    • An artificial neural network model for mountainous water-resources management: the case of Cyprus mountainous watersheds
    • Iliadis L.S., Maris F. An artificial neural network model for mountainous water-resources management: the case of Cyprus mountainous watersheds. Environ. Modell. Softw. 2007, 22:1066-1072.
    • (2007) Environ. Modell. Softw. , vol.22 , pp. 1066-1072
    • Iliadis, L.S.1    Maris, F.2
  • 28
    • 54049100690 scopus 로고    scopus 로고
    • A neural network approach to simple prediction of soil nitrification potential: a case study in Japanese temperate forests
    • Ito E., Ono K., Ito Y.M., Araki M. A neural network approach to simple prediction of soil nitrification potential: a case study in Japanese temperate forests. Ecol. Model. 2008, 219:200-211.
    • (2008) Ecol. Model. , vol.219 , pp. 200-211
    • Ito, E.1    Ono, K.2    Ito, Y.M.3    Araki, M.4
  • 29
    • 0030169551 scopus 로고    scopus 로고
    • Predicting moment-curvature parameters from experimental data
    • Jadid M.N., Fairbairn D.R. Predicting moment-curvature parameters from experimental data. Eng. Appl. Artif. Intell. 1996, 9:303-319.
    • (1996) Eng. Appl. Artif. Intell. , vol.9 , pp. 303-319
    • Jadid, M.N.1    Fairbairn, D.R.2
  • 30
    • 62349132975 scopus 로고    scopus 로고
    • Increasing the accuracy of neural network classification using refined training data
    • Kavzoglu T. Increasing the accuracy of neural network classification using refined training data. Environ. Modell. Softw. 2009, 24(7):850-858.
    • (2009) Environ. Modell. Softw. , vol.24 , Issue.7 , pp. 850-858
    • Kavzoglu, T.1
  • 31
    • 0002621464 scopus 로고
    • The overfitting problem in perspective
    • Leahy K. The overfitting problem in perspective. AI Expert 1994, 9(IO):35-36.
    • (1994) AI Expert , vol.9 , Issue.IO , pp. 35-36
    • Leahy, K.1
  • 33
    • 0036113977 scopus 로고    scopus 로고
    • Extended Kalman filter training of neural networks on a SIMD parallel machine
    • Li S., Wunsch D.C., O'Hair E., Giesselmann M.G. Extended Kalman filter training of neural networks on a SIMD parallel machine. J. Parallel Distr. Com. 2002, 62:544-562.
    • (2002) J. Parallel Distr. Com. , vol.62 , pp. 544-562
    • Li, S.1    Wunsch, D.C.2    O'Hair, E.3    Giesselmann, M.G.4
  • 35
    • 0042427272 scopus 로고    scopus 로고
    • Comparison of neural networks and statistical methods in classification of ecological habitats using FIA data
    • Liu C.L., Zhang C.J., Davis D.S., Solomon T.B., BrannCaldwell L.E. Comparison of neural networks and statistical methods in classification of ecological habitats using FIA data. Forest Sci. 2003, 49:619-631.
    • (2003) Forest Sci. , vol.49 , pp. 619-631
    • Liu, C.L.1    Zhang, C.J.2    Davis, D.S.3    Solomon, T.B.4    BrannCaldwell, L.E.5
  • 36
    • 0032051569 scopus 로고    scopus 로고
    • The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study
    • Maier H.R., Dandy G.C. The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study. Environ. Modell. Softw. 1998, 13:193-209.
    • (1998) Environ. Modell. Softw. , vol.13 , pp. 193-209
    • Maier, H.R.1    Dandy, G.C.2
  • 37
    • 0033957764 scopus 로고    scopus 로고
    • Neural Networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications
    • Maier H.R., Dandy G.C. Neural Networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications. Environ. Modell. Softw. 2000, 15:101-124.
    • (2000) Environ. Modell. Softw. , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 38
    • 0003486924 scopus 로고
    • Academic Press, San Diego, CA
    • ++ 1993, Academic Press, San Diego, CA.
    • (1993) ++
    • Masters, T.1
  • 40
    • 44749087176 scopus 로고    scopus 로고
    • Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems
    • May R.J., Dandy G.C., Maier H.R., Nixon J.B. Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems. Environ. Modell. Softw. 2008, 23(10, 11):1289-1299.
    • (2008) Environ. Modell. Softw. , vol.23 , Issue.10-11 , pp. 1289-1299
    • May, R.J.1    Dandy, G.C.2    Maier, H.R.3    Nixon, J.B.4
  • 41
    • 44749087316 scopus 로고    scopus 로고
    • Non-linear variable selection for artificial neural networks using partial mutual information
    • May R.J., Maier H.R., Dandy G.C., Gayani Fernando T.M.K. Non-linear variable selection for artificial neural networks using partial mutual information. Environ. Modell. Softw. 2008, 23(10, 11):1312-1326.
    • (2008) Environ. Modell. Softw. , vol.23 , Issue.10-11 , pp. 1312-1326
    • May, R.J.1    Maier, H.R.2    Dandy, G.C.3    Gayani Fernando, T.M.K.4
  • 42
    • 53149113747 scopus 로고    scopus 로고
    • Prediction of urban stormwater quality using artificial neural networks
    • May D.B., Sivakumar M. Prediction of urban stormwater quality using artificial neural networks. Environ. Modell. Softw. 2009, 24:296-302.
    • (2009) Environ. Modell. Softw. , vol.24 , pp. 296-302
    • May, D.B.1    Sivakumar, M.2
  • 45
    • 47649097460 scopus 로고    scopus 로고
    • Comparative study of standard and modern methods for estimating tree bole volume of three species in Turkey
    • Özcelik R., Diamantopoulou M.J., Wiant H.V., Brooks J.R. Comparative study of standard and modern methods for estimating tree bole volume of three species in Turkey. For. Prod. J. 2008, 58(6):73-81.
    • (2008) For. Prod. J. , vol.58 , Issue.6 , pp. 73-81
    • Özcelik, R.1    Diamantopoulou, M.J.2    Wiant, H.V.3    Brooks, J.R.4
  • 49
    • 0032584921 scopus 로고    scopus 로고
    • A recursive algorithm based on the extended Kalman filter for the training of feed forward neural models
    • Rivals I., Personnaz L. A recursive algorithm based on the extended Kalman filter for the training of feed forward neural models. Neurocomputing 1998, 20(1-3):279-294.
    • (1998) Neurocomputing , vol.20 , Issue.1-3 , pp. 279-294
    • Rivals, I.1    Personnaz, L.2
  • 50
    • 0028174533 scopus 로고
    • Optimization of groundwater remediation using artificial neural networks with parallel solute transport modeling
    • Rogers L.L., Dowla F.U. Optimization of groundwater remediation using artificial neural networks with parallel solute transport modeling. Water Resour. Res. 1994, 30:457-481.
    • (1994) Water Resour. Res. , vol.30 , pp. 457-481
    • Rogers, L.L.1    Dowla, F.U.2
  • 52
    • 0031071044 scopus 로고    scopus 로고
    • Machine vision using artificial neural networks with local 3D neighbourhoods
    • Schmoldt D.L., Pei Li, Lynn Abbott A. Machine vision using artificial neural networks with local 3D neighbourhoods. Comput. Electron. Agric. 1997, 16:255-271.
    • (1997) Comput. Electron. Agric. , vol.16 , pp. 255-271
    • Schmoldt, D.L.1    Pei, L.2    Lynn Abbott, A.3
  • 54
    • 36148981764 scopus 로고    scopus 로고
    • Forest measurement and biometrics in pacific Northwest USA: status and future needs of the Pacific Northwest USA
    • Temesgen H., Goerndt M., Johnson G., Adams D., Monseurd R. Forest measurement and biometrics in pacific Northwest USA: status and future needs of the Pacific Northwest USA. J. For. 2007, 105:233-238.
    • (2007) J. For. , vol.105 , pp. 233-238
    • Temesgen, H.1    Goerndt, M.2    Johnson, G.3    Adams, D.4    Monseurd, R.5
  • 56
    • 33845428996 scopus 로고    scopus 로고
    • Prediction of timber kiln drying rates by neural networks
    • Wu H., Avramidis S. Prediction of timber kiln drying rates by neural networks. Dry Technol. 2006, 24:1541-1545.
    • (2006) Dry Technol. , vol.24 , pp. 1541-1545
    • Wu, H.1    Avramidis, S.2


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