## 5 Conclusions  
This paper aimed to address the claims of visibility over- and under-estimation tendencies resulting from existing empirical equations. To that end, an algorithm was developed to assist in processing various data sets of TSPs and recorded visibilities, and output the best fitting results in terms of equation recurrences accompanied by their estimation percentage of error. The sources consisted of variations in terms of data collection techniques, sites of interest (urban, rural, or regional level) with particulate concentrations as low 25 ug/m\({}^{3}\) and as high as 440 mg/m\({}^{3}\) and corresponding visibilities as high as 56 km and as low as 0.06 km.  
While the results did not yield a decisive conclusion, they did partially substantiate the [PERSON] [13] (average RMSE of 7.16), [PERSON] et al. [14] (average RMSE of 7.07), and [PERSON] et al. [15] (average RMSE of 11.7) equations, which emerged as reliable estimators of visibility with reasonable accuracy compared to other empirical models (average RMSE \(>\) 29). Furthermore, by using our technique, we found that by averaging [PERSON] [13] and [PERSON] et al. [14], [PERSON] [13] and [PERSON] et al. [15], and [PERSON] et al. [14] and [PERSON] et al.'s [15] equations, average RMSE could be further reduced to 5.4, 7.02, and 8.52, respectively.  
Finally, to evaluate the proposed approach, we provided a demonstration of employability, where a study provided signal attenuation measurements at an experimental site with vaguely defined meteorological conditions. Consequently, the conditions were converted into visibility using our findings and found to be in a good agreement with projected ranges of horizontal visibility standards set by the China Meteorological Administration (CMA).  
Conceptualization, H.N.M. and W.I.; methodology, H.N.M.; software, H.N.M.; validation, H.N.M., and W.I.; formal analysis, H.N.M.; investigation, H.N.M.; resources, H.N.M.; data curation, H.N.M.; writing--original draft preparation, H.N.M.; writing--review and editing, W.I.; supervision, W.I.; project administration, W.I.; funding acquisition, W.I. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Environment Classification and Wind Speed Measurements by [26]**} & \multicolumn{3}{c}{**Standards Defined by the China Meteorological Administration (CMA)**} \\ \hline Environment condition & Wind speed, m/s & Calculated visibility, km & Environment condition & Expected horizontal visibility, km \\ Dusty sky & 3.6 (\(\pm\)3.5\%) & 9.9 (\(-\)0.53, \(+\)0.55) & Floating dust & \(<\)10 \\ Sand storm & 3.8 (\(\pm\)3.5\%) & 8.16 (\(-\)0.45, \(+\)0.46) & Blowing sand & 1-10 \\ Heavy sand storm & 7.3 (\(\pm\)3.5\%) & 0.45 (\(-\)0.046, \(+\)0.087) & Dust/sand storm & 0.5-1 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Environment conditions labelled by [26] with the corresponding calculated visibilities and their similarities to the China Meteorological Administration’s standards.  
**Funding:** This research was funded by Universiti Sains Malaysia Research University Individual (RUI) Grant, grant number 1001/PELECT/8014058.  
**Acknowledgments:** Special appreciation to the Malaysia Ministry of Higher Education for the support and School of Electrical and Electronics Engineering, Engineering Campus, USM for the assistance and space in conducting the research.  
**Conflicts of Interest:** The authors declare no conflict of interest.