\noindent P_{(i,D_n)}=\frac{{\tau }^{\alpha }_{(i,D_n\ )}\ \ {\eta }^{\beta }_{(i,D_n\ )}}{\sum^k_{j=0}{{\tau }^{\alpha }_{\ (j,D_n\ \ )}\ \ {\eta }^{\beta }_{(\ j,D_n\ )}}}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \eqref{GrindEQ__1_}
\noindent where $P_{(i,D_n)}$ is the probability of choosing data object $D_n$ in cluster i , $\tau (i,D_n)$ and $\eta (i,D_n)$ are the pheromone and heuristic information assigned to data object $D_n$ in cluster i respectively, $\alphaup$ and $\betaup$ are constant parameters that determines the relative influence of the pheromone and heuristic information and k is the number of clusters.
答案1
像这样吗?
请注意,我已经从根本上简化并精简了与数学相关的代码。
\documentclass{article}
\begin{document}
\begin{equation} \label{GrindEQ_1}
P_{i,D_n} = \frac{\tau^\alpha_{i,D_n} \, \eta^\beta_{i,D_n}}{
\sum^k_{j=1} \tau^\alpha_{j,D_n} \, \eta^\beta_{j,D_n}}\,,
\quad i=1,\dots,k
\end{equation} % no blank line after "\end{equation}"
where $P_{i,D_n}$ is the probability of choosing data object~$D_n$ in
cluster~$i$; $\tau_{i,D_n}$ and $\eta_{i,D_n}$ are the pheromone and
heuristic information assigned to data object~$D_n$ in cluster~$i$,
respectively; $\alpha$ and~$\beta$ are constant parameters that determine
the relative influence of the pheromone and heuristic information; and~$k$
is the number of clusters.
\end{document}