\documentclass[review]{elsarticle}
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% packages for tables
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\begin{document}
\begin{frontmatter}
\title{xvcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccczvvvvvvvvvvvvv}
%\tnotetext[mytitlenote]{Fully documented templates are available in the elsarticle package on %\href{http://www.ctan.org/tex-archive/macros/latex/contrib/elsarticle}{CTAN}.}
%% or include affiliations in footnotes:
\author[mymainaddress]{Fasdgggggggggemi}
\author[mysecondaryaddress]{Tosdgssdgn sdgfard}
\author[mythirdaddress]{Dosdggsdgol Yoo\corref{mycorrespondingauthor}}
\cortext[mycorrespondingauthor]{Corresponding author} \ead{dysdggggggggggggggggggggggkr}
%\ead[url]{http://fens.sabanciuniv.edu/en/people/faculty/detail/2689}
%\href{http://fens.sabanciuniv.edu/en/people/faculty/detail/2689}{E}
\address[mymainaddress]{Faasfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffdansk, Poland}
\address[mysecondaryaddress]{Insasffffffffffff Machinery, Pafsaafolfish Academy of Sasffffffffffffffffffffffffff Pafsnd}
\address[mythirdaddress]{Departasff Architeasffse and Architecasfasfasfafeering, Yoasfaf Universasfsafasfl, South Korea}
\begin{abstract}
\noindent Predicting the mechanical properties of reinforced concretes accurately has been a concern as these attributes are generally required by design criteria. Thus, in recent years, there has been a dramatic increase in the application of machine learning algorithms to solve complicated engineering problems. Predictive models are strong solution for time consuming numerical simulations and expensive experimental works. The present study discussed the important properties of different types of reinforced concretes as well as an extensive analysis of artificial intelligence methods utilized for predicting those attributes. Key observations, challenges, and future trends are also detailed. This work is a precious resource for researchers in choosing accurate models, which match their applications. It motivates material engineers to become familiar and employ machine learning techniques applied in this field for predicting material properties of reinforced concrete structures.
\end{abstract}
\begin{keyword}
Machine learning; Data-asffffffffffffion techniques; Artificial neural network; Reinforced concrete; Mafsssssssssssssssssss
\end{keyword}
\end{frontmatter}
beam, slab, column, wall, pier
답변1
이것은 잘못된 문제입니다.
LaTeX는 섹션 헤더 바로 다음에 페이지를 나누지 않습니다.
\subsection{FRP laminate}
It has three main types of GFRP, CFRP, and AFRP.
\subsubsection{Near Surface Mounted (NSM) FRP reinforcing rebar}
\subsection{FRP reinforcing rebar}
\section{Experimental controlling test}
\subsection{Non-Destructive Testing (NDT)}
\subsection{Pull off test}
\subsection{Tensile strength test}
\section{Experimental study}
\subsection{Reinforced concrete structure}
\subsection{Steel structure}
\subsection{Infrastructure}
\section{Numerical investigation}
\subsection{Reinforced concrete structure}
\subsection{Steel structure}
\subsection{Infrastructure}
\section{Designing methods of FRP}
\section{Optimization methods}
\section{Machine learning algorithms}
\section{Recommendations and gaps}
\section{Conclusions}
\noindent In order ...
실행 가능한 유일한 페이지 중단 지점은 "It has three main..." 및 " \noindentIn order..." 다음입니다.
그래서 LaTeX가 그것들을 가져갑니다. 텍스트를 추가하면 문제가 해결되는 것을 확인할 수 있습니다.
일부 의견은 순서대로입니다.
당신이 사용한다면
elsarticle당신은해야~ 아니다페이지 설정, 캡션 형식 및 일반적으로 스타일을 수정해 보십시오. 그러니 제거해야 해geometry,caption,fullpage,setspace,fancyhdr,sectsty당신은 스타일을 좋아하지 않을 수도 있지만
elsarticle그들은 그렇습니다. 그리고 최종 결정을 내리는 것은 귀하가 논문을 제출한 저널입니다.이 패키지는
epsfig약 30년 동안 사용되지 않았습니다.패키지를
latexsym으로 교체해야 합니다amssymb.
패키지를 여러 번 로드하는 것은 코딩이 엉성함을 나타냅니다. 필요한 패키지만 로드하고한 번.