TY - GEN
T1 - A fuzzy pattern recognition model for water quality evaluation based on the principle of maximum entropy
AU - Jin, Juliang
AU - Zhang, Youfu
AU - Wei, Yiming
AU - Tang, Lihua
PY - 2008
Y1 - 2008
N2 - A fuzzy pattern recognition model for water quality evaluation was developed on the basis of the least weighted general distance and the objective influence of uncertainty estimated by the principle of maximum information entropy of Jaynes. To balance the least weighted general distance and the maximum entropy, a new methodology was developed to use the model of maximum entropy fuzzy pattern recognition as the practical modelling process, to use the grade judgment standard as the principle of theoretic grade, and to use accelerating genetic algorithms to determine the balanced parameter α between the least weighted general distance and the maximum entropy. The theoretical analysis and applications show that the new method for determining the balance parameter α is highly feasible and reliable. The new model is theoretically sound and widely applicable for fuzzy pattern recognition for handling various problems in comprehensive water resources evaluation.
AB - A fuzzy pattern recognition model for water quality evaluation was developed on the basis of the least weighted general distance and the objective influence of uncertainty estimated by the principle of maximum information entropy of Jaynes. To balance the least weighted general distance and the maximum entropy, a new methodology was developed to use the model of maximum entropy fuzzy pattern recognition as the practical modelling process, to use the grade judgment standard as the principle of theoretic grade, and to use accelerating genetic algorithms to determine the balanced parameter α between the least weighted general distance and the maximum entropy. The theoretical analysis and applications show that the new method for determining the balance parameter α is highly feasible and reliable. The new model is theoretically sound and widely applicable for fuzzy pattern recognition for handling various problems in comprehensive water resources evaluation.
KW - Fuzzy pattern recognition
KW - Genetic algorithms
KW - Principle of maximum entropy
KW - Water quality evaluation
KW - Water resources comprehensive evaluation
UR - http://www.scopus.com/inward/record.url?scp=45749109096&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:45749109096
SN - 9781901502442
T3 - IAHS-AISH Publication
SP - 49
EP - 56
BT - Hydrological Sciences for Managing Water Resources in the Asian Developing World
T2 - Hydrological Sciences for Managing Water Resources in the Asian Developing World
Y2 - 8 June 2006 through 10 June 2006
ER -