latex 文件积累

\usepackage{array}
\usepackage{longtable} % 长表格自动分页,此宏包依赖array宏包
\usepackage{multirow} %不规则表格占用多行

\begin{table}[h!]
  \centering
  \caption{Comparative results of coverage and specificity for synthetic 1-D numeric data with six clusters for selected values of $c$}\label{Tab:comp_TS_Granular_M}
  \begin{tabular}{ccccccccc}
    %\hline
    % after \\: \hline or \cline{col1-col2} \cline{col3-col4} ...
     %\    %\hline
    \toprule
    \multirow{3}{*}{$c$} &\multicolumn{4}{c}{Standard granular TS model}             &   \multicolumn{4}{c}{Proposed granular fuzzy model} \                       \cline{2-9}
                        &\multicolumn{2}{c}{Coverage} &\multicolumn{2}{c}{Specificity} &\multicolumn{2}{c}{Coverage} &\multicolumn{2}{c}{Specificity} \                        \cline{2-9}
                        & Training& Testing& Training& Testing                   & Training& Testing& Training& Testing\    \midrule
    2                  &0.5976   &0.5111   &0.4996  &0.4391                      &0.1667   & 0.1611 &0.1579  &0.1504\    3                  &0.5952   &0.5889   &0.5188  &0.4970                      &0.2429   & 0.1444 &0.2133  &0.1242 \    4                  &0.7214   &0.7667   &0.6374  &0.6161                      &0.4738   & 0.4889 &0.4412  &0.4533 \    6                  &0.7000   &0.7056   &0.6622  &0.6704                      &0.6786   & 0.6556 &0.6403  &0.6172  \    8                  &0.6167   &0.5556   &0.5907  &0.5357                      &0.8000   & 0.8000 &0.7324  &0.7386  \    10                 &0.5524   &0.5167   &0.5336  &0.5029                      &0.8289   & 0.8167 &0.7707  &0.7673  \    %12                 &0.9357   &0.9389   &0.8751  &0.8791                      &0.8190   & 0.9000 &0.7519  &0.8273  
    \bottomrule
  \end{tabular}

\end{table}

\begin{longtable}{p{\linewidth}}
\toprule
\textbf{Algorithm 1} Pseudocode for constructing of input information granules based on FCM prototypes \\endfirsthead

% Appear the table header at the top of every page
\toprule
\textbf{Algorithm 1} Pseudocode for constructing of input information granules based on FCM prototypes \\hline
\endhead

% Appear \hline at the bottom of every page
\hline
\endfoot


\midrule
\textbf{Input:}  Numeric data collection $\bm D$, number of clusters $c$, values of $\alpha, \beta$, and division value of $\Delta \rho$, FCM termination criterion $\epsilon$.\\textbf{Output:} Input granules $A$. \\midrule

01.  normalize $\bm D$ to $(0,1)$ \02. generate a collection of numeric prototypes $\{ [\bm v, w]\}$ by using FCM \03. $i\leftarrow 1$ \04. \textbf{repeat} \05.     \qquad $j\leftarrow1$\06.     \qquad \textbf{repeat}\07.             \qquad\qquad  $\rho_{ij} = j*\Delta\rho$\08.             \qquad\qquad  Calculate ${\rm cov}(A_{ij})$ via \eqref{Eq:cov} \09.             \qquad\qquad  Calculate ${\rm spec}(A_{ij})$ via \eqref{Eq:spec} \10.            \qquad\qquad Calculate $\sigma_{ij}$  via \eqref{Eq:diviation_y}\11.            \qquad\qquad Determine V($\rho_{ij}$) via \eqref{Eq:input_gran_radus_value} \12.            \qquad\qquad $j\leftarrow j+1$\13.     \qquad  \textbf{until} $\rho_{ij}>1$\14.     \qquad  Optimize  $\rho_{i}$ by Max$( V(\rho_{ij}), j=1,2,\ldots,(1/\Delta\rho) )$\15.     \qquad  \textbf{return} prototypes $\bm v_{i}$ and corresponding radii $\rho_{i}$\16.     \qquad  $i \leftarrow i+1$\17. \textbf{until} $i>c$\18. \textbf{return} Input granules $\{ [\boldsymbol v_{1},\rho_{1}], [\boldsymbol v_{2},\rho_{2}],\ldots,[\boldsymbol v_{c},\rho_{c}] \}$, i.e., $\{ A_{1},A_{2},\ldots,A_{c} \}$\19. \textbf{Check} overlaps between $A_{i}$s, \textbf{refresh} $\rho_{i}$s \\noindent \textbf{Output:} $A$ \\bottomrule
\end{longtable}