d ( V x , V y ) = ( f y 1 − f x 1 ) 2 + ( f y 2 − f x 2 ) 2 + ( f y 3 − f x 3 ) 2 {\displaystyle \mathrm {d} (\mathbf {V_{x}} ,\mathbf {V_{y}} )={\sqrt {(f_{y1}-f_{x1})^{2}+(f_{y2}-f_{x2})^{2}+(f_{y3}-f_{x3})^{2}}}}
d σ ( V x , V y ) = ( f y 1 − f x 1 σ 1 ) 2 + ( f y 2 − f x 2 σ 2 ) 2 + ( f y 3 − f x 3 σ 3 ) 2 {\displaystyle \mathrm {d_{\sigma }} (\mathbf {V_{x}} ,\mathbf {V_{y}} )={\sqrt {\left({\frac {f_{y1}-f_{x1}}{\sigma _{1}}}\right)^{2}+\left({\frac {f_{y2}-f_{x2}}{\sigma _{2}}}\right)^{2}+\left({\frac {f_{y3}-f_{x3}}{\sigma _{3}}}\right)^{2}}}}
σ f c 1 = ( f c 1 1 − E ( V c 1 ) ) 2 + ( f c 1 2 − E ( V c 1 ) ) 2 + ⋯ + ( f c 1 20 − E ( V c 1 ) ) 2 n {\displaystyle \sigma _{f_{c1}}={\sqrt {\frac {(f_{c1_{1}}-E(V_{c1}))^{2}+(f_{c1_{2}}-E(V_{c1}))^{2}+\dots +(f_{c1_{20}}-E(V_{c1}))^{2}}{n}}}}
σ f c 1 = ( 2 − 2.15 ) 2 + ( 2 − 2.15 ) 2 + ( 2 − 2.15 ) 2 + ( 2 − 2.15 ) 2 + ( 3 − 2.15 ) 2 + ( 2 − 2.15 ) 2 + ( 2 − 2.15 ) 2 + ⋯ + ( 2 − 2.15 ) 2 20 {\displaystyle \sigma _{f_{c1}}={\sqrt {\frac {(2-2.15)^{2}+(2-2.15)^{2}+(2-2.15)^{2}+(2-2.15)^{2}+(3-2.15)^{2}+(2-2.15)^{2}+(2-2.15)^{2}+\dots +(2-2.15)^{2}}{20}}}}
σ f c 1 = ( − 0.15 ) 2 + ( − 0.15 ) 2 + ( − 0.15 ) 2 + ( − 0.15 ) 2 + ( 0.85 ) 2 + ( − 0.15 ) 2 + ( − 0.15 ) 2 + ⋯ + ( − 0.15 ) 2 20 {\displaystyle \sigma _{f_{c1}}={\sqrt {\frac {(-0.15)^{2}+(-0.15)^{2}+(-0.15)^{2}+(-0.15)^{2}+(0.85)^{2}+(-0.15)^{2}+(-0.15)^{2}+\dots +(-0.15)^{2}}{20}}}}
σ f c 2 = ( f c 2 1 − E ( V c 2 ) ) 2 + ( f c 2 2 − E ( V c 2 ) ) 2 + ⋯ + ( f c 2 20 − E ( V c 2 ) ) 2 n {\displaystyle \sigma _{f_{c2}}={\sqrt {\frac {(f_{c2_{1}}-E(V_{c2}))^{2}+(f_{c2_{2}}-E(V_{c2}))^{2}+\dots +(f_{c2_{20}}-E(V_{c2}))^{2}}{n}}}}
σ f c 2 = ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ( 1 − 1.15 ) 2 + ⋯ + ( 1 − 1.15 ) 2 20 {\displaystyle \sigma _{f_{c2}}={\sqrt {\frac {(1-1.15)^{2}+(1-1.15)^{2}+(1-1.15)^{2}+(1-1.15)^{2}+(1-1.15)^{2}+(1-1.15)^{2}+(1-1.15)^{2}+\dots +(1-1.15)^{2}}{20}}}}
σ f c 3 = ( f c 3 1 − E ( V c 3 ) ) 2 + ( f c 3 2 − E ( V c 3 ) ) 2 + ⋯ + ( f 3 20 − E ( V c 3 ) ) 2 n {\displaystyle \sigma _{f_{c3}}={\sqrt {\frac {(f_{c3_{1}}-E(V_{c3}))^{2}+(f_{c3_{2}}-E(V_{c3}))^{2}+\dots +(f_{3_{20}}-E(V_{c3}))^{2}}{n}}}}
d σ ( E ( V c ) , V n e w ) = ( f n e w 1 − E ( V c 1 ) σ f c 1 ) 2 + ( f n e w 2 − E ( V c 2 ) σ f c 2 ) 2 + ( f n e w 3 − E ( V c 3 ) σ f c 3 ) 2 {\displaystyle \mathrm {d_{\sigma }} (\mathbf {E(V_{c})} ,\mathbf {V_{new}} )={\sqrt {\left({\frac {f_{new1}-E(V_{c1})}{\sigma _{f_{c1}}}}\right)^{2}+\left({\frac {f_{new2}-E(V_{c2})}{\sigma _{f_{c2}}}}\right)^{2}+\left({\frac {f_{new3}-E(V_{c3})}{\sigma _{f_{c3}}}}\right)^{2}}}}
d σ ( E ( V z ) , V n e w ) = ( f n e w 1 − E ( V z 1 ) σ f z 1 ) 2 + ( f n e w 2 − E ( V z 2 ) σ f z 2 ) 2 + ( f n e w 3 − E ( V z 3 ) σ f z 3 ) 2 {\displaystyle \mathrm {d_{\sigma }} (\mathbf {E(V_{z})} ,\mathbf {V_{new}} )={\sqrt {\left({\frac {f_{new1}-E(V_{z1})}{\sigma _{f_{z1}}}}\right)^{2}+\left({\frac {f_{new2}-E(V_{z2})}{\sigma _{f_{z2}}}}\right)^{2}+\left({\frac {f_{new3}-E(V_{z3})}{\sigma _{f_{z3}}}}\right)^{2}}}}
s u m = 1.0 0.5 + 1.1 1.5 + 1.2 2.5 + 1.3 3.5 + 1.4 4.5 + ⋯ + 2.0 10.5 {\displaystyle sum={\frac {1.0}{0.5}}+{\frac {1.1}{1.5}}+{\frac {1.2}{2.5}}+{\frac {1.3}{3.5}}+{\frac {1.4}{4.5}}+\dots +{\frac {2.0}{10.5}}}
C l a s s ( f 1 , f 2 , f 3 , f 4 , f 5 , f 6 ) = { C 1 if 0 ≤ P r o g i ( f 1 , f 2 , f 3 , f 4 , f 5 , f 6 ) < 10000 C 2 if 10000 ≤ P r o g i ( f 1 , f 2 , f 3 , f 4 , f 5 , f 6 ) < 20000 C 3 if 30000 ≤ P r o g i ( f 1 , f 2 , f 3 , f 4 , f 5 , f 6 ) < 40000 C 4 if 40000 ≤ P r o g i ( f 1 , f 2 , f 3 , f 4 , f 5 , f 6 ) < 50000 {\displaystyle Class(f_{1},f_{2},f_{3},f_{4},f_{5},f_{6})={\begin{cases}C_{1}&{\text{if }}0\leq Prog_{i}(f_{1},f_{2},f_{3},f_{4},f_{5},f_{6})<10000\\C_{2}&{\text{if }}10000\leq Prog_{i}(f_{1},f_{2},f_{3},f_{4},f_{5},f_{6})<20000\\C_{3}&{\text{if }}30000\leq Prog_{i}(f_{1},f_{2},f_{3},f_{4},f_{5},f_{6})<40000\\C_{4}&{\text{if }}40000\leq Prog_{i}(f_{1},f_{2},f_{3},f_{4},f_{5},f_{6})<50000\end{cases}}}
y = { 3 x − 7 if x = − 3 5 x 2 if x = 2 or x = 5 x − 4 x 3 if x = − 4 or x = 4 {\displaystyle y={\begin{cases}3x-7&{\text{if }}x=-3\\5x^{2}&{\text{if }}x=2{\text{ or }}x=5\\x-4x^{3}&{\text{if }}x=-4{\text{ or }}x=4\end{cases}}}
A = [ a 11 a 12 a 13 a 21 a 22 a 13 a 31 a 32 a 33 ] {\displaystyle \mathbf {A} ={\begin{bmatrix}a_{11}&a_{12}&a_{13}\\a_{21}&a_{22}&a_{13}\\a_{31}&a_{32}&a_{33}\\\end{bmatrix}}}
y = 1 1 ! + 2 2 ! + 3 3 ! + ⋯ + n n ! {\displaystyle y={\frac {1}{1!}}+{\frac {2}{2!}}+{\frac {3}{3!}}+\cdots +{\frac {n}{n!}}}
f ( n ) = ∑ i = 1 n n 1 i {\displaystyle f(n)=\sum _{i\mathop {=} 1}^{n}n^{\frac {1}{i}}}
f ( N ) = ∏ i = 1 N 7 1 i = 7 × 7 1 2 × 7 1 3 × 7 1 4 × ⋯ × 7 1 N {\displaystyle f(N)=\prod _{i\mathop {=} 1}^{N}7^{\frac {1}{i}}=7\times 7^{\frac {1}{2}}\times 7^{\frac {1}{3}}\times 7^{\frac {1}{4}}\times \cdots \times 7^{\frac {1}{N}}}