\documentclass[review]{elsarticle}
%\documentclass[1p]{elsarticle}
\usepackage{geometry}
\usepackage{epsfig}
\usepackage{latexsym}
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\journal{Compoddddddddddddddddddddddddddddtes}
\bibliographystyle{elsarticle-num}
\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
答え1
これは誤った問題です。
LaTeXはセクションヘッダーの直後でページを分割することはなく、
\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 ...
実行可能なページ区切りは、「It has three main…」と「\noindentIn order…」の後のみです。
そのため、LaTeX はそれらを取得します。テキストを追加すると、問題がなくなることがわかります。
いくつかコメントが必要です。
使用する場合
elsarticleはないページ設定、キャプションの形式、そして一般的にスタイルを変更しようとすると、geometry、、、、、、captionfullpagesetspacefancyhdrsectstyあなたはスタイルを好まないかもしれませ
elsarticleんが、彼らは好みます。そして、最終決定権を持つのは、論文を提出するジャーナルです。このパッケージは
epsfig約30年間廃止されています。パッケージ
latexsymは に置き換える必要がありますamssymb。
パッケージを何度もロードすることはコーディングのずさんさを意味します。必要なパッケージだけをロードし、一度。