## 5 Discussion and Conclusions
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Test** **Order**} & \multirow{2}{*}{\begin{tabular}{c} **Total** \\ **Number of** \\ **Inquiries** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Level 1** \\ **Identical** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Level 2** \\ **Case** \\ **Reuse** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Level 3** \\ **Case** \\ **Trimming** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Level 4** \\ **Case** \\ **Seeking** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Total Number** \\ **of the** \\ **Inquiries of** \\ **OnotCBRA** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **The Amount** \\ **That Has** \\ **Completed** \\ **Processing in** \\ **System \%** \\ \end{tabular} } \\ \hline
1 & 6144 & 60 & 1297 & 903 & 259 & 2519 & 41.0 \\
2 & 6330 & 71 & 1345 & 879 & 237 & 2532 & 40.0 \\
3 & 6007 & 50 & 1301 & 923 & 249 & 2523 & 42.0 \\
4 & 6394 & 37 & 1411 & 890 & 207 & 2545 & 40.0 \\
5 & 5997 & 51 & 1359 & 914 & 229 & 2553 & 42.6 \\ \hline average & 6904.6 & 53.8 & 1342.6 & 901.8 & 236.2 & 2534.4 & 41.1 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Analysis results of learning effectiveness. satisfaction of the candidate case as the judgment for the recommended case? It is suggested that future studies can carry out different recommendation methods. In practice, this study built a cloud energy-saving case-based reasoning agent that integrates multiple intelligent technologies. The development of this agent system relied on the support of web services, ontology, and big data analytics under a cloud environment. This study not only effectively implemented the practical application of OntoIAS but also successfully applied the case-based reasoning technique to the learning performance of the system. Hence, this study has a certain degree of software economic benefits and broad application prospects and can effectively continue with the R&D results of related projects. Academically, this study developed an intelligent cloud energy-saving data processing and decision-making agent. The capability, architecture, and technology involved in this system demonstrate the sound application and integration of case-based reasoning and related technologies as applied to smart environments. This study is unique and innovative and should help contribute to the development of related industries and countries. The authors plan to explore further research from the perspective of vocational colleges and universities, so as to make a contribution toward practical applications and technology integration. This research article contains two authors, including [PERSON] and [PERSON], [PERSON] and [PERSON] jointly designed the overall architecture and related algorithms, and also conceived and designed the experiments; however, [PERSON] coordinated the overall plan and direction of the experiments and related skills; [PERSON] and [PERSON] not only contributed analysis tools but also analyzed the data; [PERSON] performed the experiments; and [PERSON] wrote this paper and related reply. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors would like to thank [PERSON] and [PERSON] for their assistance in earlier system implementation and preliminary experiments. This research is sponsored under grants 106-2221-E-129-008 and 107-2632-E-129-001 by the Ministry of Science and Technology, Taiwan, R.O.C. The authors feel deeply indebted to the Department of Fashion Administration and Management and Department of Information and Communication Engineering, St. John's University, Taiwan, for all aspects of assistance provided. The authors declare no conflict of interest.