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Development of a System for Market Identification Based on Stepwise Regression

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A module for market system identification was developed, which is based on a stepwise regression procedure. This module automatically generates a set of multivariate dynamic models. Each model represents a given product category.

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Development of a System for Market Identification Based on Stepwise Regression

  1. 1. Development of a System for Market Identification Based on Stepwise Regression Project Scientific Research Sector of UCTM The developed system generates demand models, which provide important information to the retailers and contributes to the stability of the retail sector of industry. Stepwise Regression for MIMO structure determination x = x0 U xe ERS — set of all factors v J e i 0 : Q X0 5 RH“ v set of factors out of l K the model E E Forwa rd xe ER" — set of factors in the model U, '3 step .6 T: *5 E X '8 / y ER’ — system output Q E Backward g E M O E L y peg’ — model output 2: 3: step 1-; E 3 O :9 C SLE — significant level to enter E‘ "3’ Estimator '- SLL — significant level to leave System Description — MIMO-ARX model (example): A(q‘1)yk = B(q'1)ui + e (1) — Matrix representation of (1): M = ‘D149 + es (2) _ T 17 9 —[a1171 alum“ anal alzmn arm amnarr] ER p = Z, -(Z1-nalj + Z]-nb, -J-) _ - T T T - T T T r><p CDk — [d1ag((oy, ,k, rpyzak, .. ., goyhk) d1ag((pu1’k, gouzsk, .. ., (ou, ’k)]ER T (P)/ i,k = l‘)/1,/ c—1 ‘ )’1,k—na, ., ‘ )’2,k—1 ‘ Y2,/ c—na, ., ‘ )’1,k—1 ‘ )’1,k—na, ,l _ T €0m', k — [“1,k—1 ---”1,k—no, .1 “2,k—1---“2,k—na, ., 7/’1,k—1 ”1,k—na, .,, ,l Least Squares Estimate y: [y; yjf/ _1]T ERr(N—n> — C1‘1teI‘1OI1Z rn0inJ, , = main ll y—cI>6 ii; 6 2 [65 e]TV_1]T ERr<N~n> — Solution: é : (q3Tq))‘1c1)Ty (3) (1) = [cpn q)N_1]T eR’(N'")XP A. Efremov D. Mihaylova A. Atanasov aefremov@gmai| .com darya. mihay| ova@gmai| .com ftomova@uctm. edu naso@uctm. edu University of Chemical Technology and Metallurgy - Sofia

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