A survey of data mining techniques applied to agriculture

Operational Research

Volumn 9, Issue 2, 2009, Pages 121-140

  Mucherino, A ^a   Papajorgji, Petraq ^b   Pardalos, P M ^b  

^a ÉCOLE POLYTECHNIQUE   (France)

^b University of Florida   (United States)

Author keywords

Agriculture; Artificial neural networks; Data mining; K nearest neighbor; K means; Optimization; Support vector machines

Indexed keywords

EID: 67651005448     PISSN: 11092858     EISSN: 18661505     Source Type: Journal    
DOI: 10.1007/s12351-009-0054-6     Document Type: Review

References (72)

1. Abello J, Pardalos PM, Resende M (2002) Handbook of massive data sets. Kluwer, New York
2. J-M Aerts P Jans D Halloy P Gustin D Berckmans 2004 Labeling of cough data from pigs for on-line disease monitoring by sound analysis Am Soc Agric Biol Eng 48 1 351 354
3. Angiulli F, Folino G (2007) Efficient distributed data condensation for nearest neighbor classification. In: Kermarrec A-M, Bouge L, Priol T (eds) Lecture notes on computer science vol 4641, pp 338-347
4. JL Bentley 1975 Multidimensional binary search trees used for associative searching Commun ACM 18 9 509 517
5. Bishop CM (2006) Pattern recognition and machine learning. Springer, New York
6. CJC Burges 1998 A tutorial on support vector machines for pattern recognition Data Min Knowl Discov 2 2 955 974
7. S Busygin OA Prokopyev PM Pardalos 2005 Feature selection for consistent biclustering via fractional 0-1 programming J Comb Optim 10 7 21 (Pubitemid 41205694)
8. RL Brown 1995 Accelerated template matching using template trees grown by condensation IEEE Trans Syst Man Cybernet 25 3 523 528
9. K Brudzewski S Osowski T Markiewicz 2004 Classification of milk by means of an electronic nose and SVM neural network Sens Actuators B98 291 298
10. G Camps-Valls L Gomez-Chova J Calpe-Maravilla E Soria-Olivas JD Martin-Guerrero J Moreno 2003 Support vector machines for crop classification using hyperspectral data Lect Notes Computer Sci 2652 134 141
11. G Castellano AM Fanelli M Pelillo 1997 An iterative pruning algorithm for feedforward neural networks IEEE Trans Neural Netw 8 3 519 531
12. A Chedad D Moshou JM Aerts A Van Hirtum H Ramon D Berckmans 2001 Recognition system for pig cough based on probabilistic neural networks J Agricult Eng Res 79 4 449 457
13. C Cortes V Vapnik 1995 Support vector networks Mach Learning 20 273 297
14. TM Cover PE Hart 1967 Nearest neighbor pattern classification IEEE Trans Inf Theory 13 1 21 27
15. KC Das MD Evans 1992 Detecting fertility of hatching eggs using machine vision II: neural network classifiers Trans ASAE 35 6 2035 2041
16. AP Dempster NM Laird RD Rubin 1977 Maximum likelihood from incomplete data via the EM algorithm J R Stat Soc B39 1 1 38
17. VS Devi MN Murty 2002 An incremental prototype set building technique Pattern Recognit 35 505 513
18. C-J Du D-W Sun 2005 Pizza sauce spread classification using colour vision and support vector machines J Food Eng 66 137 145
19. Fagerlund S (2007) Bird species recognition using support vector machines. EURASIP J Adv Signal Processing, Article ID 38637, p 8
20. Fnaiech N, Abid S, Fnaiech F, Cheriet M (2004) A modified version of a formal pruning algorithm based on local relative variance analysis. First international symposium on control, communications and signal processing, March
21. GW Gates 1972 The reduced nearest neighbor rule IEEE Trans Inf Theory 18 431 433
22. R Gil-Garcia JM Badia-Contelles A Pons-Porrata 2007 Parallel nearest neighbour algorithms for text categorization Lect Notes Comp Sci 4641 328 337
23. Guan Y, Ghorbani AA, Belacel N (2003) Y-means: a clustering method for intrusion Detection. In: IEEE Canadian conference on electrical and computer engineering, proceedings, 1083-1086
24. P Hansen N Mladenovic 2002 J-means: a new local search heuristic for minimum sum-of-squares clustering Pattern Recognit 34 2 405 413
25. Hammerstrom D (1993) Neural networks at work. IEEE Spectr:26-32 (June)
26. PE Hart 1968 The condensed nearest neighbor rule IEEE Trans Inf Theory 14 515 516
27. Hartigan J (1975) Clustering algorithms. John Wiles & Sons, New York
28. P Holmgren T Thuresson 1998 Satellite remote sensing for forestry planning: a review Scand J For Res 13 1 90 110
29. Graf HP, Cosatto E, Bottou L, Dourdanovic I, Vapnik V (2005) Parallel support vector machines: the cascade SVM. In: Bernhard S, Leon B (eds) Advances in neural information processing systems. Lawrence Saul, vol 17, MIT Press
30. SS Jagtap U Lall JW Jones AJ Gijsman JT Ritchie 2004 Dynamic nearest-neighbor method for estimating soil water parameters Trans ASAE 47 5 1437 1444
31. T Jinlan Z Lin Z Suqin L Lu 2005 Improvement and parallelism of k-means clustering algorithm Tsinghua Sci Technol 10 3 277 281
32. IT Jolliffe 1972 Discarding variables in a principal component analysis. I: artificial data Appl Stat 21 2 160 173
33. Jones JW, Tsuji GY, Hoogenboom G, Hunt LA, Thornton PK, Wilkens PW, Imamura DT, Bowen WT, Singh U (1998) Decision support system for agrotechnology transfer: DSSAT v3. In: Tsuji GY, Hoogenboom G, Thornton PK (eds) Understanding options for agricultural production. Kluwer Academic Publishers, Dordrecht, pp 157-177
34. Jorquera H, Perez R, Cipriano A, Acuna G (2001) Short term forecasting of air pollution episodes. In: Zannetti P (eds) Environmental modeling 4. WIT Press, UK
35. Y Karimi SO Prasher RM Patel SH Kim 2006 Application of support vector machine technology for weed and nitrogen stress detection in corn Comput Electronics Agric 51 99 109
36. Kernel-Machines web site: http://www.kernel-machines.org/
37. Klosgen W, Zytkow JM (2002) Handbook of data mining and knowledge discovery. Oxford University Press
38. K Krishna M Murty 1999 Genetic k-means algorithm IEEE Trans Syst Man Cybern Part B Cybern 29 3 433 439
39. V Leemans MF Destain 2004 A real time grading method of apples based on features extracted from defects J Food Eng 61 83 89
40. RA Leonard WG Knisel DA Still 1987 GLEAMS: groundwater-loading effects of agricultural management systems Trans Am Soc Agric Eng 30 5 1403 1418
41. SP Lloyd 1982 Least squares quantization in PCM IEEE Trans Inf Theory 28 2 129 137
42. Nahapatyan A, Busygin S, Pardalos P (2008) An improved heuristic for consistent biclustering problems. In: Mondaini RP, Pardalos PM (eds) Mathematical modelling of biosystems. Appl Optim 102. Springer, pp 185-198
43. The MathWorks: http://www.mathworks.com/
44. GE Meyer JC Neto DD Jones TW Hindman 2004 Intensified fuzzy clusters for classifying plant, soil, and residue regions of interest from color images Comput Electronics Agric 42 161 180
45. B Moreaux D Beerens P Gustin 1999 Development of a cough induction test in pigs: effects of SR 48968 and enalapril J Veterinary Pharmacol Ther 22 387 389
46. D Moshou A Chedad A Van Hirtum J De Baerdemaeker D Berckmans H Ramon 2001 An intellingent alarm for early detection of swine epidemics based on neural networks Am Soc Agric Eng 44 1 167 174
47. D Moshou A Chedad A Van Hirtum J De Baerdemaeker D Berckmans H Ramon 2001 Neural recognition system for swine cough Math Comput Simul 56 475 487
48. Mucherino A, Papajorgji P, Pardalos PM (2009) Data mining in agriculture. Springer, New York (in press)
49. Nurnberger A, Pedrycz W, Kruse R (2002) Neural network approaches. In: Klosgen W, Zytkow JM (eds) Handbook of data mining and knowledge discovery. Oxford University Press
50. Papajorgji P, Pardalos PM (2006) Software engineering techniques applied to agricultural systems an object-oriented and UML Approach. Springer, New York
51. Pardalos PM, Boginski LV, Vazacopoulos A (2007) Data mining in biomedicine. Springer, New York
52. Pardalos PM, Hansen P (2008) Data mining and mathematical programming. American Mathematical Society, USA
53. VC Patel RW McClendon JW Goodrum 1994 Crack detection in eggs using computer vision and neural networks Artif Intell Appl 8 2 21 31
54. JA Fernandez Pierna V Baeten A Michotte Renier RP Cogdill P Dardenne 2004 Combination of support vector machines (SVM) and near-infrared (NIR) imaging spectroscopy for the detection of meat and bone meal (MBM) in compound feeds J Chemom 18 341 349
55. Platt JC (1999) Fast training of support vector machines using sequential minimal optimization. In: Schilkopf B, Burges C, Smola A (eds) Advances in kernel methods-support vector learning. MIT Press, MA, USA, pp 185-208
56. B Rajagopalan U Lall 1999 A k-nearest-neighbor simulator for daily precipitation and other weather variables Water Res Res 35 10 3089 3101
57. R Reed 1993 Pruning algorithms-A survey IEEE Trans Neural Netw 4 5 740 747
58. A Riul Jr HC de Sousa RR Malmegrim DS dosSantos Jr ACPLF Carvalho FJ Fonseca ON Oliveira Jr LHC Mattoso 2004 Wine classification by taste sensors made from ultra-thin films and using neural networks Sens Actuators B98 77 82
59. Schwenker F (2000) Hierarchical support vector machines for multi-class pattern recognition. In: Proceedings of the 4th international conference on knowledge-based intellingent engineering systems and allied technologies (KES 2000), vol 2, pp 561-565, Brighton, UK
60. MA Shahin EW Tollner RW McClendon 2001 Artificial intelligence classifiers for sorting apples based on watercore J Agric Eng Res 79 3 265 274
61. Seiffert U (2002) Artificial neural networks on massively parallel computer hardware. European symposium on artificial networks proceedings, Bruges (Belgium), 319-330
62. Spath H (1980) Cluster analysis algorithms for data reduction and classification of objects. Ellis Horwood, Chichester
63. CO Stockle SA Martin GS Campbell 1994 CropSyst, a cropping systems model: water/nitrogen budgets and crop yield Agric Syst 46 3 335 359
64. Sung KK, Poggio T (2009) Example-based learning for view-based human face detection. A.I. Memo 1521, MIT
65. S Tripathi VV Srinivas RS Nanjundiah 2006 Downscaling of precipitation for climate change scenarios: a support vector machine approach J Hydrol 330 621 640
66. A Urtubia JR Perez-Correa M Meurens E Agosin 2004 Monitoring large scale wine fermentations with infrared spectroscopy Talanta 64 778 784
67. A Urtubia JR Perez-Correa A Soto P Pszczolkowski 2007 Using data mining techniques to predict industrial wine problem fermentations Food Control 18 1512 1517
68. Vapnik VN (1998) Statistical learning theory. Wiley, New York
69. K Verheyen D Adriaens M Hermy S Deckers 2001 High-resolution continuous soil classification using morphological soil profile descriptions Geoderma 101 31 48
70. Y Wu K Ianakiev V Govindaraju 2002 Inproved k-nearest neighbor classification Pattern Recognit 35 2311 2318
71. X Wu V Kumar JR Quinlan J Ghosh Q Yang H Motoda GJ McLachlan A Ng B Liu PS Yu Z-H Zhou M Steinbach DJ Hand D Steinberg 2008 Top 10 algorithms in data mining Knowl Inf Syst 14 1 37
72. Zhang Y, Xiong Z, Mao J, Ou L (2006) The study of parallel k-means Algorithm. In: Proceedings of the 6th world congress on intelligent control and automation 2:5868-5871