## 3 Results
### Research Hotspots  
The research literature on TBM performance underwent a comprehensive terminology analysis. The findings of this analysis are visually represented in Figure 4, while the distribution of the primary keywords is detailed in Table 2. Keywords, in research, play a pivotal role as they encapsulate the fundamental arguments and themes of a paper. Analyzing the keywords in the relevant literature of a specific field serves as a valuable tool for identifying research trends and focal points [23]. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**No.** & **Keyword** & **Frequency** & **Relevance** & **No.** & **Keyword** & **Frequency** & **Relevance** \\ \hline
1 & Prediction & 152 & 0.3335 & 11 & Accuracy & 71 & 0.442 \\
2 & Test & 126 & 0.4792 & 12 & Estimation & 71 & 0.6167 \\
3 & Efficiency & 110 & 0.4838 & 13 & Technique & 68 & 0.4818 \\
4 & Disc cutter & 100 & 0.9397 & 14 & Simulation & 66 & 1.1793 \\
5 & Force & 99 & 0.6139 & 15 & Database & 62 & 1.0776 \\
6 & Cutter & 93 & 0.6988 & 16 & Interaction & 61 & 0.5368 \\
7 & Index & 88 & 0.4663 & 17 & Coefficient & 59 & 0.7648 \\
8 & Penetration rate & 88 & 0.6442 & 18 & Ground & 58 & 0.9006 \\
9 & Algorithm & 83 & 0.5215 & 19 & Uniaxial compressive & 57 & 1.1401 \\
10 & Prediction model & 74 & 0.3399 & 20 & Mechanism & 56 & 1.4459 \\ \hline \end{tabular}
\end{table} 
Table 2: Hot keywords in TBM performance studies. The process of extracting these keywords was carried out using VOSviewer, with a predefined threshold of 15 occurrences (i.e., keywords that appeared at least 15 times), involving the consolidation of keywords with similar meanings and the removal of keywords not directly relevant to the current study. Through these operations, a total of 197 pertinent keywords were identified, forming a network of 9610 interconnected relationships. Figure 4: Hot topic analysis. (**A**) Keyword network visualization. (**B**) Keyword overlay visualization. (**C**) Keyword density visualization. These relationships can be effectively categorized into the following three overarching themes: \"mining\", \"TBM performance prediction\", and \"testing\", as visually represented in Figure 4A. The cumulative strength of these keyword connections amounts to 29,040, indicating a notably strong interrelation among these keywords. Broadly speaking, the examination of test studies encompassed the majority of the keywords, signaling a heightened level of research activity within this domain. This prevalence can be ascribed to the inherent nature of most TBM performance prediction models, which tend to be theoretical and intricately empirical. The inclusion of keywords such as \"behavior\", \"cutter head\", \"cutter wear\", \"deformation\", \"disc cutter\", \"dynamic model\", \"joint\", \"hard rock\", \"mechanics\", \"numeric simulation\", \"test result\", and others underscores the exploration by researchers into rock and machine parameters. These investigations often take place in laboratory settings and play a pivotal role in the development of the aforementioned prediction models. This reflects the meticulous examination of factors that exert an influence on TBM performance, further enriching the field's knowledge base. The temporal progression of keywords is visually presented in Figure 4B, with color bars ranging from purple to yellow. In this color scheme, purple denotes the earlier appearance of a keyword, while yellow signifies more recent occurrences. Examining this temporal evolution, we observe that keywords such as \"cutter head\", \"depth\", \"orientation\", \"rock\", \"property\", and \"joint spacing\" emerge in the earlier stages, highlighting the predominant focus of early studies on understanding rock mechanisms and related factors. In the medium term, we notice an increased prominence of words like \"prediction\", \"efficiency\", \"index\", \"tensile strength\", \"UCS\", and \"wear\". This shift reflects a transition in researchers' perspective from fundamental theoretical aspects towards performance indicators.