## 3 System Architecture
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Types of Reuse** & \begin{tabular}{c} **Whether to Take It** \\ **as a Solution** \\ \end{tabular} & \begin{tabular}{c} **Whether to** \\ **Adapt It** \\ \end{tabular} & \begin{tabular}{c} **Solution** \\ **as a Solution** \\ \end{tabular} \\ \hline \begin{tabular}{c} single-identical \\ (SR(V) = 1) \\ \end{tabular} & Yes & - & - & - \\ \hline \begin{tabular}{c} multiple-identical \\ (SR(V) = 1) \\ \end{tabular} & \begin{tabular}{c} Yes \\ (Randomly select 1 \\ by the system) \\ \end{tabular} & - & - & - \\ \hline \begin{tabular}{c} single-much like \\ (0.85 \(\geq\) SR(V) \(>\) 1) \\ \end{tabular} & Yes & - & - & - \\ \hline \begin{tabular}{c} multiple-much like \\ (0.85 \(\geq\) SR(V) \(>\) 1) \\ \end{tabular} & \begin{tabular}{c} Yes \\ (System selects the \\ case with the highest \\ similarity value) \\ \end{tabular} & - & - & - \\ \hline \begin{tabular}{c} single-like \\ (0.75 \(\geq\) SR(V) \(>\) 0.85) \\ \end{tabular} & No & Yes & Transformational adaptation & Yes \\ \hline \begin{tabular}{c} multiple-like \\ (0.75 \(\geq\) SR(V) \(>\) 0.85) \\ \end{tabular} & No & Yes & \
\begin{tabular}{c} 1. Transformational adaptation \\ 2. Select the case with the \\ highest similarity value \\ as the recommended solution \\ \end{tabular} & Yes \\ \hline
\begin{tabular}{c} Does not meet the \\ threshold \\ (SR(V) \(<\) 0.75) \\ \end{tabular} & No & No & Experts seeking & Yes \\ \hline \hline \end{tabular} Note: SR(V) represents similarity value; “single-” means there was only one candidate case; “multiple-” represents there were several candidate cases; “-” means no action.  
\end{table} 
Table 4: Reuse application-types of problems. The degree of \"case adaptation\", also known as \"case revision\", is between case reuse and case trimming, and this study categorized the case through the application of case revision. In past studies, scholars have summarized a variety of adaptation methods. Considering the applicability of the field related to this study and other considerations, this study chose the substitutional adaptation as the method. There were three main reasons for choosing this method. * First, the advantage of the substitutional adaptation method is that it is not necessary to make any changes to the original case structure. For a case-based system, this method can easily solve similar new problems in the case architecture. Hence, such an adaptation method is most efficient. Taking an energy-saving system as an example, this case-based reasoning mechanism, with the characteristic of cycling, was used in a real-time environment, and using substitutional adaptation could reduce the burden on the system operation. * The similarity value of the case retrieval in this study was calculated by a single type of sensor, and the average value of the sum was the similarity value of the case. Therefore, in the application case adaptation, a single type of sensor and its corresponding values were used as the basis of the index, and the values were slightly adjusted in an appropriate manner. Until the end, the case with the highest similarity value was taken as the recommended case. This method did not perform actions that would damage the case structure, such as adding or deleting columns. Instead, it just made a slight adaptation to the values of the sensors. * This study used the temporary table provided by.Net strategy to improve the problems in RAM. The action was to take SQL (Structured Query Language) to structure the query language through.Net. SQL is a programming language for querying, updating, and managing relational databases. SQL SELECT statement allows specific data to be easily retrieved, sorted, and filtered. Because of these three reasons, this study chose the substitutional adaptation method. Table 5 is the case adaptation, which is an analysis of a single type of sensor. First, the necessary condition for adaptation was that the overall similarity value of the problems and the cases of database shall be 0.75 \(\geq\) SR(V) \(>\) 0.85.