Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data

References

• Abbass , H. A. , Sarker , R. A. and Newton , C. S. 2002 . Data mining: a heuristic approach (Idea Group Publishing)
   Google Scholar
• Bagheri Shouraki , S. and Honda , N. 1997a . “ A new method for establishing and saving fuzzy membership functions. ” . In 13^th Fuzzy Symposium 91 – 94 . 4–6 June 1997, Toyama, Japan
   Google Scholar
• Bagheri Shouraki , S. and Honda , N. 1997b . “ Outlines of a living structure based on biological neurons for simulating the active learning method. ” . In 7^th Intelligent Systems Symposium 183 – 188 . November 1997, Sapporo, Japan
   Google Scholar
• Bagheri Shouraki , S. and Honda , N. 1998 . “ Fuzzy controller design by an active learning method. ” . In 31^st Symposium of Intelligent Control 1 – 10 . 26 August 1998, Japan, Tokyo
   Google Scholar
• Bagheri Shouraki , S. and Honda , N. 1999 . Recursive fuzzy modelling based on fuzzy interpolation. . Journal of Advanced Computational Intelligence , 3 : 114 – 125 .
   Google Scholar
• Bagheri Shouraki , S. , Yuasa , G. and Honda , N. 1998 . “ Fuzzy interpretation of human intelligence. ” . In Vietnam–Japan Bilateral Symposium of Fuzzy Systems and Applications 441 – 448 . October 1998, Halong Bay, Vietnam
   Google Scholar
• Darecki , M. , Kaczmarek , S. and Olszewski , J. 2005 . SeaWiFS ocean colour chlorophyll algorithms for the southern Baltic Sea. . International Journal of Remote Sensing , 26 : 247 – 260 .
   Web of Science ®Google Scholar
• Fell , F. and Fischer , J. 2001 . Numerical simulation of the light field in the atmosphere–ocean system using the matrix–operator method. . Journal of Quantitative Spectroscopy and Radiative Transfer , 69 : 351 – 388 .
   Web of Science ®Google Scholar
• Fischer , J. and Kronfeld , U. 1990 . Sun‐stimulated chlorophyll fluorescence, 1: Influence of oceanic properties. . International Journal of Remote Sensing , 11 : 2125 – 2147 .
   Web of Science ®Google Scholar
• Heim , B. , Oberhaensli , H. , Fietz , S. and Kaufmann , H. 2005 . Variation in Lake Baikal's phytoplankton distribution and fluvial input assessed by SeaWiFS satellite data. . Global and Planetary Change , 46 : 9 – 27 .
   Web of Science ®Google Scholar
• Iluz , D. , Yacobi , Y. Z. and Gitelson , A. 2003 . Adaption of an algorithm for chlorophyll‐a estimation by optical data in oligotrophic Gulf of Eliat. . International Journal of Remote Sensing , 24 : 1157 – 1163 .
   Web of Science ®Google Scholar
• Lotfi , T. and Bagheri Shouraki , S. 2004 . “ Active learning method to solve Bin Packing problem. ” . In Proceedings of Neural Networks and Computational Intelligence (NCI 2004) 23–25 February 2004, Grindelwald, Switzerland, Paper no. 413‐009
   Google Scholar
• Mamdani , E. A. 1976 . Advances in the linguistic synthesis of fuzzy controllers. . International Journal of Man–Machine Studies , 8 : 669 – 678 .
   Google Scholar
• Maritorena , S. , O'Reilly , J. and Schieber , B. D. 2002 . “ SeaBAM Evaluation Dataset. ” . Available online at: http://seabass.gsfc.nasa.gov/seabam/pub/maritorena_oreilly_schieber/
   Google Scholar
• Mitchel , B. G. and Kuhra , M. 1998 . Algorithms for SeaWiFS developed with the CalCOFI dataset CalCOFI Report 39, California Cooperative Oceanic Fisheries Investigations Report, Lajolla, California
   Google Scholar
• Murakami , M. and Honda , N. 2004 . “ Toward the development of a high fault tolerant learning system based on the ALM architecture. ” . In Joint 2^nd International Conference on Soft Computing and Intelligent Systems and 5^th International Symposium on Advanced Intelligent Systems 21–24 September 2004, Yokohama, Japan
   Google Scholar
• Murakami , M. , Honda , N. and Nishino , J. 2003 . A hardware design for a new learning system based on fuzzy concepts. . 12^th IEEE International Conference on Fuzzy Systems , 2 : 1002 – 1007 . 25–28 May 2003
   Google Scholar
• O'Reilly , J. and Maritorena , S. 2002 . “ SeaBAM algorithm evaluation. ” . Available online at: http://seabass.gsfc.nasa.gov/seabam/pub/oreilly_maritorena/
   Google Scholar
• O'Reilly , J. , Maritorena , S. , Mitchell , B. , Siegel , D. , Carder , K. , Garver , S. , Kahru , M. and McClain , C. 1998 . Ocean colour chlorophyll algorithms for SeaWiFS. . Journal of Geophysical Research , 103 : 24 937 – 24 953 .
   Web of Science ®Google Scholar
• Schmidt , R. F. 1985 . Fundamentals of Neurophysiology (Springer‐Verlag)
   Google Scholar
• Shahdi , S. A. and Bagheri Shouraki , S. 2003 . “ Use of active learning method to develop an intelligent stop and go cruise control. ” . In Proceedings of Intelligent Control and Systems (ISC 2003) 25–27 June 2003, Salzburg, Austria, paper no. 388‐157
   Google Scholar
• Su , F. C. , Ho , C. R. , Zheng , Q. , Kuo , N. J. and Chen , C. T. 2006 . Satellite chlorophyll retrievals with a bipartite artificial neural network model. . International Journal of Remote Sensing , 27 : 1563 – 1579 .
   Web of Science ®Google Scholar
• Sugeno , M. and Yasukawa , T. 1993 . A fuzzy‐logic based approach to qualitative modelling. . IEEE Transactions on Fuzzy Systems , 1 : 7 – 31 .
   Google Scholar
• Takagi , T. and Sugeno , M. 1985 . Fuzzy identification of systems and its applications to modelling and control. . IEEE Transactions on Systems, Man, and Cybernetics , SMC‐15 : 116 – 132 .
   Web of Science ®Google Scholar
• Werdell , P. J. and Bailey , S. W. 2005 . An improved in situ bio‐optical dataset for ocean colour algorithm development and satellite data product validation. . Remote Sensing of Environment , 98 : 122 – 140 .
   Web of Science ®Google Scholar
• Zadeh , L. A. 1965 . Fuzzy sets. . Information and Control , 8 : 338 – 353 .
   Web of Science ®Google Scholar
• Zhan , H. , Shi , P. and Chen , C. 2003 . Retrieval of oceanic chlorophyll concentration using support vector machines. . IEEE Transactions on Geoscience and Remote Sensing , 41 : 2947 – 2951 .
   Web of Science ®Google Scholar
• Zhang , T. 2003 . “ Retrieval of oceanic constituents with artificial neural network based on radiative transfer simulation techniques. ” . PhD thesis, Freie Universität Berlin
   Google Scholar
• Zhang , T. , Fell , F. , Liu , Z. S. , Preusker , R. , Fischer , J. and He , M. X. 2003 . Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean colour in case I waters. . Journal of Geophysical Research , 108 : 3286 – 3297 .
   Web of Science ®Google Scholar