# Data-Driven Computational Methods in Fuel Combustion: A Review of Applications
## 4 Statistical Overview
This is a five-fold increase compared to the previous period (7 publications in 2015-2019).The next places were taken by:  
* United States--13 publications (13.4%), of which 10 were in the last five years,
* India--increased from 1 to 11 publications, with 12 in total (12.37%),
* Saudi Arabia--increased from 1 to 10 (11.34%),
* Germany--total increase from 0 to 9 publications (9.28%). There was also a noticeable increase in activity in countries such as Iran, the United Kingdom, Pakistan, Canada, and Malaysia, although their percentage share in the total number of publications did not exceed 5%. Other categories covering other countries accounted for 12 works (12.37%). The number of publications by country by year and the percentage share is presented in Table 3. \begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Country** & **2015–2019** & **2020–2024** & **All Years** & **Share [\%]** \\ \hline All countries & 18 & 79 & 97 & 100.0 \\ China & 7 & 36 & 43 & 44.33 \\ United States & 3 & 10 & 13 & 13.4 \\ India & 1 & 11 & 12 & 12.37 \\ Saudi Arabia & 1 & 10 & 11 & 11.34 \\ Germany & 0 & 9 & 9 & 9.28 \\ Iran & 1 & 4 & 5 & 5.15 \\ United & 1 & 4 & 5 & 5.15 \\ Kingdom & 1 & 3 & 4 & 4.12 \\ Canada & 0 & 4 & 4 & 4.12 \\ France & 2 & 1 & 3 & 3.09 \\ Japan & 1 & 2 & 3 & 3.09 \\ Malaysia & 0 & 3 & 3 & 3.09 \\ Other & 3 & 9 & 12 & 12.37 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Number of publications by country by year and percentage share. Figure 8: Number of publications by country of affiliation of the authors (2015–2019 vs. 2020–2024). The data also shows that 81% of all publications (79 out of 97) were from the last five years, which confirms the rapid development of the research area and its timeliness. According to the data from the chi-square test, the value of the statistic was \(\chi^{2}=11.6\) with 12 degrees of freedom, which translates to a value of \(p=0.48\). This means that no statistically significant relationship was observed between national affiliation and the period of publication. In other words, the increase in the number of publications was general and not limited to a specific geographical region. The summary of data from Table 3 and its visualization in Figures 9 and 10 allows for the assessment of the relationship between the type of analyzed fuel and the calculation methods and research approach used. In the 97 publications analyzed, gasoline was the most frequently studied fuel (30 cases), followed by hydrogen (17), natural gas, and coal (16 each), and the least attention was paid to biomass (10) and biodiesel (11). When it comes to the methods and algorithms used, neural networks and genetic algorithms stand out in particular. The former appeared in as many as 42 papers, most  
Figure 10: Type of research approach (experiment, literature analysis, concept) in relation to the type of fuel. Figure 9: Application of selected calculation methods depending on the type of fuel. often in the context of hydrogen (11 publications), gasoline (11), biodiesel (7), and natural gas (5). Genetic algorithms, present in 39 papers, were most commonly used for gasoline (14), natural gas (12), coal (7), and hydrogen (4). This confirms their wide application, both for the optimization of combustion parameters and for the construction of predictive models. The SVM (support vector machine) method was also relatively popular--18 publications, with a dominant share in research on hydrogen (7), gasoline (5), and carbon (4). In the case of the CFD (Computational Fluid Dynamics) method, a concentration on gasoline (12 cases), coal (4), and natural gas (4) was noticed. PCA, random forests, and regression played a minor role but have been used in supporting analyses such as feature selection and assessment of the impact of input variables. It is also worth noting the low presence of some methods for specific fuels--for example, PCA was not used at all for biodiesel or hydrogen, and random forests did not appear in the work on hydrogen and natural gas.