1、 :cEE ZE !$ = (Z + S 2 210016) K 1 E VE MV U“54B:cEE ZEbs:cE $ E MM1lE 8 M“TV U !9E M V Lsf YVE M LCE M“b LTV ZE ?r“aV U“E Mb 1oM :cE E E M“ sf Expert Evaluation Method Based on Delphi Method LIU Wei-tao, GU Hong, LI Chun-hong (Scientific Research Department, Naval Command College, Nanjing 210016, C
2、hina) AbstractWhen all the problems are evaluated by the experts, expert knowledge expression and integration is very important and difficult as well. Aiming at the problem, expert evaluation method based on Delphi method is applied to collect expert knowledge and evaluate by expert, based on the an
3、alysis of the basic theory of Delphi method, the related definition of expert knowledge and the expression of expert knowledge integration result is proposed, the reliability function of expert knowledge is given, the method of expert knowledge integration is proposed. Experimental results show that
4、 the method can collect, express and integrate expert knowledge effectively. Key wordsDelphi method; expert evaluation; expert knowledge integration; distribution function 9 Computer Engineering 37 9 ! (1982 ) 3 =a VZ_ M $ a = qap V l 2011-08-01 E- 190 9 2011 M 12 (3)?5 ?1E 5s+ r l rTb (4)E5 E G o L
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12、vb9 ZE / !E f / 100NHM M E N B uWE b !E f / 100PHQ Q E 9 P B uWE 9bE MsZm m 1 Ub aE s 020a a20 40a a40 60a a60 80a a80 100ab m 1 E MsZm 5 L s $ h 10 E5us1 ps 0100WYV |E Mis ZEM) d9 V 1 Ub V 1 E M E pis ai(ai&E)2piai E 1 0.15 80 5.29 12.00 E 2 0.05 90 59.29 4.50 E 3 0.20 86 13.69 17.20 E 4 0.03 70 15
13、1.29 2.10 E 5 0.16 92 94.09 14.72 E 6 0.02 65 299.29 1.30 E 7 0.10 85 7.29 8.50 E 8 0.08 95 161.29 7.60 E 9 0.09 82 0.09 7.38 E 10 0.12 78 18.49 9.36 (/ 204 : ) 204 9 2011 M 12 m 6 L 2 FCSS “S6 Et m 7 2 E HWM ( wLb m 7 L 2 E HWM ( wL Vm 7 V A E “S? 3 H69 FCM “S6 E V7 Erb 5 FCM “S6 Evs “S6 E BQ9 “S -
14、 H1 Xy z“St 9 “S - S FCM E) “S “S Mt (g s ) -t1 V7 “S6b7 El s FCSS E+1 “S -919 “SM B H YM i “S B H YF O 7FCSS E) “S 7 “St “S6i O6b 6 FCSS E7 “ f / VYVBZE “9V7 bN?Vt StZ V7 P FCSS E “S6VF b ID 1 , , C , . “S 6+ J. p , 2007, 27(2): 328-331. 2 f . , a . 0 ro EdL “S6 J. 0 S/v : 1 S , 2010, 37(4): 636-64
15、1. 3 j , , k , . RBPF 1 “S6 J. 9 , 2010, 36(6): 186-188. 4 L , , 6j , . “S qL ! 6 J. e , 2011, 28(8): 1087- 1092. 5 Krishnapuram R, Nasraoui O, Frigui H. The Fuzzy C Spherical Shells Algorithm: A New ApproachJ. IEEE Transactions on Neural Networks, 1992, 3(5): 663-671. ( 191 : ) I nE f / ( E =82.3Z2
16、 = 90.01 9 D =81.84bZ lV UEinM“s lb I nE f /F (E =84.66b YV L s V A“E Ms 65 s 95 s uW :cE Vr) 1 10E Mi“ E5 V V 80s7 OinM“byN TE M“E M Bt1 , EV10 E M4 |N ?5r N7:cEE ZE ?E M“ H98C E M) b 6 :cEE ZE B ZE %dL5 Esr7E MV U“ V 1 b:cE $ 4E MM1lE 8 M“TV U4E M V Lsf YVE M 4E M“ZEVs L ZE Vb Ll :cEE ZE 4 5 1C Li
17、lb/B| E M“ZE4E M l rT) r qE MBax V b ID 1 S . “d S M. Z : Z S/, 2000. 2 f . S$ M. : Zv, 1992. 3 . SZE $ M. Z : Z S/ D, 1995. 4 . s TE“d J. 9 , 2009, 35(23): 278-280. 5 Bordly R F. A Multiplicative Formula for Aggregation Probability EstimatesJ. Management Science, 1982, 28(10): 1137-1149. 6 , U , . 8 M5 “d J. 9 , 2009, 35(16): 256-258. 7 , f , , . %“d M. : 0, 2009.
