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[求助]
求高人指點 已有1人參與
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已知數(shù)據(jù) T(a) t(min) 5 10 15 20 30 45 60 90 120 150 180 i(mm/min) 2 1.89 1.55 1.28 1.09 0.89 0.7 0.58 0.45 0.36 0.31 0.27 3 2.17 1.78 1.49 1.28 1.06 0.84 0.7 0.55 0.45 0.38 0.33 5 2.48 2.04 1.76 1.54 1.28 1.01 0.86 0.68 0.55 0.48 0.42 10 2.87 2.38 2.13 1.91 1.59 1.25 1.07 0.85 0.7 0.61 0.55 20 3.23 2.69 2.5 2.28 1.9 1.49 1.29 1.03 0.85 0.75 0.69 50 3.68 3.09 2.98 2.79 2.32 1.81 1.57 1.27 1.05 0.94 0.87 100 4.01 3.38 3.35 3.18 2.63 2.06 1.79 1.46 1.21 1.08 1.00 滿足數(shù)據(jù)模型 i=A1*(1+C*LOG(T))/(t+b)^n,如何解決次非線性已知關(guān)系式的參數(shù)估計呢?MATLAB或者spss或者lingo有會的嗎? |
木蟲 (正式寫手)

木蟲 (正式寫手)
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LINGO程序: MODEL: SETS: ROW:TA; COL:T; LINKS(ROW,COL):II,I_EST; ENDSETS DATA: TA=2,3,5,10,20,50,100; T=5,10,15,20,30,45,60,90,120,150,180; II=1.89,1.55,1.28,1.09,0.89,0.7,0.58,0.45,0.36,0.31,0.27, 2.17,1.78,1.49,1.28,1.06,0.84,0.7,0.55,0.45,0.38,0.33, 2.48,2.04,1.76,1.54,1.28,1.01,0.86,0.68,0.55,0.48,0.42, 2.87,2.38,2.13,1.91,1.59,1.25,1.07,0.85,0.7,0.61,0.55, 3.23,2.69,2.5,2.28,1.9,1.49,1.29,1.03,0.85,0.75,0.69, 3.68,3.09,2.98,2.79,2.32,1.81,1.57,1.27,1.05,0.94,0.87, 4.01,3.38,3.35,3.18,2.63,2.06,1.79,1.46,1.21,1.08,1.00; ENDDATA MIN=@SUM(LINKS(I,J) II-I_EST)^2);@FOR(LINKS(I,J):I_EST(I,J)=A*(1+C*@LOG(TA(I)))/((T(J)+B)^D)); END 結(jié)果: Local optimal solution found. Objective value: 0.7190258 Infeasibilities: 0.000000 Total solver iterations: 76 Elapsed runtime seconds: 0.08 Model Class: NLP Total variables: 81 Nonlinear variables: 81 Integer variables: 0 Total constraints: 78 Nonlinear constraints: 78 Total nonzeros: 462 Nonlinear nonzeros: 385 Variable Value Reduced Cost A 13.90490 0.000000 C 0.5246665 0.000000 B 19.67398 0.000000 D 0.7547631 0.000000 TA( 1) 2.000000 0.000000 TA( 2) 3.000000 0.000000 TA( 3) 5.000000 0.000000 TA( 4) 10.00000 0.000000 TA( 5) 20.00000 0.000000 TA( 6) 50.00000 0.000000 TA( 7) 100.0000 0.000000 T( 1) 5.000000 0.000000 T( 2) 10.00000 0.000000 T( 3) 15.00000 0.000000 T( 4) 20.00000 0.000000 T( 5) 30.00000 0.000000 T( 6) 45.00000 0.000000 T( 7) 60.00000 0.000000 T( 8) 90.00000 0.000000 T( 9) 120.0000 0.000000 T( 10) 150.0000 0.000000 T( 11) 180.0000 0.000000 II( 1, 1) 1.890000 0.000000 II( 1, 2) 1.550000 0.000000 II( 1, 3) 1.280000 0.000000 II( 1, 4) 1.090000 0.000000 II( 1, 5) 0.8900000 0.000000 II( 1, 6) 0.7000000 0.000000 II( 1, 7) 0.5800000 0.000000 II( 1, 8) 0.4500000 0.000000 II( 1, 9) 0.3600000 0.000000 II( 1, 10) 0.3100000 0.000000 II( 1, 11) 0.2700000 0.000000 II( 2, 1) 2.170000 0.000000 II( 2, 2) 1.780000 0.000000 II( 2, 3) 1.490000 0.000000 II( 2, 4) 1.280000 0.000000 II( 2, 5) 1.060000 0.000000 II( 2, 6) 0.8400000 0.000000 II( 2, 7) 0.7000000 0.000000 II( 2, 8) 0.5500000 0.000000 II( 2, 9) 0.4500000 0.000000 II( 2, 10) 0.3800000 0.000000 II( 2, 11) 0.3300000 0.000000 II( 3, 1) 2.480000 0.000000 II( 3, 2) 2.040000 0.000000 II( 3, 3) 1.760000 0.000000 II( 3, 4) 1.540000 0.000000 II( 3, 5) 1.280000 0.000000 II( 3, 6) 1.010000 0.000000 II( 3, 7) 0.8600000 0.000000 II( 3, 8) 0.6800000 0.000000 II( 3, 9) 0.5500000 0.000000 II( 3, 10) 0.4800000 0.000000 II( 3, 11) 0.4200000 0.000000 II( 4, 1) 2.870000 0.000000 II( 4, 2) 2.380000 0.000000 II( 4, 3) 2.130000 0.000000 II( 4, 4) 1.910000 0.000000 II( 4, 5) 1.590000 0.000000 II( 4, 6) 1.250000 0.000000 II( 4, 7) 1.070000 0.000000 II( 4, 8) 0.8500000 0.000000 II( 4, 9) 0.7000000 0.000000 II( 4, 10) 0.6100000 0.000000 II( 4, 11) 0.5500000 0.000000 II( 5, 1) 3.230000 0.000000 II( 5, 2) 2.690000 0.000000 II( 5, 3) 2.500000 0.000000 II( 5, 4) 2.280000 0.000000 II( 5, 5) 1.900000 0.000000 II( 5, 6) 1.490000 0.000000 II( 5, 7) 1.290000 0.000000 II( 5, 8) 1.030000 0.000000 II( 5, 9) 0.8500000 0.000000 II( 5, 10) 0.7500000 0.000000 II( 5, 11) 0.6900000 0.000000 II( 6, 1) 3.680000 0.000000 II( 6, 2) 3.090000 0.000000 II( 6, 3) 2.980000 0.000000 II( 6, 4) 2.790000 0.000000 II( 6, 5) 2.320000 0.000000 II( 6, 6) 1.810000 0.000000 II( 6, 7) 1.570000 0.000000 II( 6, 8) 1.270000 0.000000 II( 6, 9) 1.050000 0.000000 II( 6, 10) 0.9400000 0.000000 II( 6, 11) 0.8700000 0.000000 II( 7, 1) 4.010000 0.000000 II( 7, 2) 3.380000 0.000000 II( 7, 3) 3.350000 0.000000 II( 7, 4) 3.180000 0.000000 II( 7, 5) 2.630000 0.000000 II( 7, 6) 2.060000 0.000000 II( 7, 7) 1.790000 0.000000 II( 7, 8) 1.460000 0.000000 II( 7, 9) 1.210000 0.000000 II( 7, 10) 1.080000 0.000000 II( 7, 11) 1.000000 0.000000 I_EST( 1, 1) 1.686812 0.000000 I_EST( 1, 2) 1.467515 0.000000 I_EST( 1, 3) 1.304787 0.000000 I_EST( 1, 4) 1.178648 0.000000 I_EST( 1, 5) 0.9947225 0.000000 I_EST( 1, 6) 0.8150901 0.000000 I_EST( 1, 7) 0.6963602 0.000000 I_EST( 1, 8) 0.5471199 0.000000 I_EST( 1, 9) 0.4558515 0.000000 I_EST( 1, 10) 0.3935919 0.000000 I_EST( 1, 11) 0.3480805 0.000000 I_EST( 2, 1) 1.949956 0.000000 I_EST( 2, 2) 1.696449 0.000000 I_EST( 2, 3) 1.508335 0.000000 I_EST( 2, 4) 1.362519 0.000000 I_EST( 2, 5) 1.149900 0.000000 I_EST( 2, 6) 0.9422449 0.000000 I_EST( 2, 7) 0.8049930 0.000000 I_EST( 2, 8) 0.6324712 0.000000 I_EST( 2, 9) 0.5269648 0.000000 I_EST( 2, 10) 0.4549926 0.000000 I_EST( 2, 11) 0.4023814 0.000000 I_EST( 3, 1) 2.281479 0.000000 I_EST( 3, 2) 1.984871 0.000000 I_EST( 3, 3) 1.764775 0.000000 I_EST( 3, 4) 1.594168 0.000000 I_EST( 3, 5) 1.345401 0.000000 I_EST( 3, 6) 1.102441 0.000000 I_EST( 3, 7) 0.9418542 0.000000 I_EST( 3, 8) 0.7400010 0.000000 I_EST( 3, 9) 0.6165569 0.000000 I_EST( 3, 10) 0.5323483 0.000000 I_EST( 3, 11) 0.4707924 0.000000 I_EST( 4, 1) 2.731327 0.000000 I_EST( 4, 2) 2.376236 0.000000 I_EST( 4, 3) 2.112742 0.000000 I_EST( 4, 4) 1.908496 0.000000 I_EST( 4, 5) 1.610679 0.000000 I_EST( 4, 6) 1.319814 0.000000 I_EST( 4, 7) 1.127563 0.000000 I_EST( 4, 8) 0.8859099 0.000000 I_EST( 4, 9) 0.7381259 0.000000 I_EST( 4, 10) 0.6373135 0.000000 I_EST( 4, 11) 0.5636204 0.000000 I_EST( 5, 1) 3.181175 0.000000 I_EST( 5, 2) 2.767601 0.000000 I_EST( 5, 3) 2.460710 0.000000 I_EST( 5, 4) 2.222824 0.000000 I_EST( 5, 5) 1.875957 0.000000 I_EST( 5, 6) 1.537186 0.000000 I_EST( 5, 7) 1.313272 0.000000 I_EST( 5, 8) 1.031819 0.000000 I_EST( 5, 9) 0.8596948 0.000000 I_EST( 5, 10) 0.7422787 0.000000 I_EST( 5, 11) 0.6564483 0.000000 I_EST( 6, 1) 3.775842 0.000000 I_EST( 6, 2) 3.284957 0.000000 I_EST( 6, 3) 2.920698 0.000000 I_EST( 6, 4) 2.638344 0.000000 I_EST( 6, 5) 2.226635 0.000000 I_EST( 6, 6) 1.824537 0.000000 I_EST( 6, 7) 1.558766 0.000000 I_EST( 6, 8) 1.224700 0.000000 I_EST( 6, 9) 1.020400 0.000000 I_EST( 6, 10) 0.8810352 0.000000 I_EST( 6, 11) 0.7791602 0.000000 I_EST( 7, 1) 4.225690 0.000000 I_EST( 7, 2) 3.676321 -0.3350793E-08 I_EST( 7, 3) 3.268665 0.000000 I_EST( 7, 4) 2.952672 0.000000 I_EST( 7, 5) 2.491913 0.000000 I_EST( 7, 6) 2.041910 0.000000 I_EST( 7, 7) 1.744475 0.000000 I_EST( 7, 8) 1.370609 0.000000 I_EST( 7, 9) 1.141969 0.000000 I_EST( 7, 10) 0.9860003 0.000000 I_EST( 7, 11) 0.8719882 0.000000 Row Slack or Surplus Dual Price 1 0.7190258 -1.000000 2 0.000000 0.4063759 3 0.000000 0.1649700 4 0.000000 -0.4957336E-01 5 0.000000 -0.1772970 6 0.000000 -0.2094449 7 0.000000 -0.2301801 8 0.000000 -0.2327203 9 0.000000 -0.1942399 10 0.000000 -0.1917031 11 0.000000 -0.1671838 12 0.000000 -0.1561610 13 0.000000 0.4400874 14 0.000000 0.1671025 15 0.000000 -0.3666924E-01 16 0.000000 -0.1650375 17 0.000000 -0.1798002 18 0.000000 -0.2044897 19 0.000000 -0.2099860 20 0.000000 -0.1649423 21 0.000000 -0.1539296 22 0.000000 -0.1499852 23 0.000000 -0.1447627 24 0.000000 0.3970423 25 0.000000 0.1102578 26 0.000000 -0.9549395E-02 27 0.000000 -0.1083358 28 0.000000 -0.1308016 29 0.000000 -0.1848820 30 0.000000 -0.1637084 31 0.000000 -0.1200020 32 0.000000 -0.1331139 33 0.000000 -0.1046967 34 0.000000 -0.1015848 35 0.000000 0.2773461 36 0.000000 0.7528256E-02 37 0.000000 0.3451560E-01 38 0.000000 0.3007612E-02 39 0.000000 -0.4135740E-01 40 0.000000 -0.1396271 41 0.000000 -0.1151265 42 0.000000 -0.7181971E-01 43 0.000000 -0.7625171E-01 44 0.000000 -0.5462704E-01 45 0.000000 -0.2724073E-01 46 0.000000 0.9764993E-01 47 0.000000 -0.1552013 48 0.000000 0.7858059E-01 49 0.000000 0.1143510 50 0.000000 0.4808677E-01 51 0.000000 -0.9437228E-01 52 0.000000 -0.4654463E-01 53 0.000000 -0.3637468E-02 54 0.000000 -0.1938958E-01 55 0.000000 0.1544258E-01 56 0.000000 0.6710333E-01 57 0.000000 -0.1916837 58 0.000000 -0.3899135 59 0.000000 0.1186045 60 0.000000 0.3033122 61 0.000000 0.1867301 62 0.000000 -0.2907413E-01 63 0.000000 0.2246731E-01 64 0.000000 0.9060044E-01 65 0.000000 0.5919965E-01 66 0.000000 0.1179297 67 0.000000 0.1816795 68 0.000000 -0.4313799 69 0.000000 -0.5926430 70 0.000000 0.1626695 71 0.000000 0.4546556 72 0.000000 0.2761743 73 0.000000 0.3618070E-01 74 0.000000 0.9104919E-01 75 0.000000 0.1787827 76 0.000000 0.1360618 77 0.000000 0.1879993 78 0.000000 0.2560236 |

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