**4. Conclusions**

In this paper, we first presented a full review of a cascade neural network with a genetic algorithm as applied to space–time forecasting. Experimental results on an air pollution dataset showed that our hybrid methods provide high accuracy as proved by the RMSE, MAE, and sMAPE values. Attributable to its rapid urbanization and industrialization over the last decades, Taiwan faces serious environmental issues, including air pollution. In order to resolve air quality issues, the governmen<sup>t</sup> has taken several countermeasures. The attempt to eliminate SO2 and overall suspended particulate matter was very effective when ever-increasing cars threatened city atmospheres with NOx and particulates. A space–time air pollution analysis over the last 10 years using the monitoring data clearly showed that with urban planning and countermeasure policies, air quality has improved. The analysis should be used to make future policy decisions. Air pollution temporal features were examined herein for Taiwan. The pattern from pollutants to particulates differs in air quality for each location. In a nutshell, the PM, SO2, and NOx levels have drastically increased. Future research should examine using VAR-SARIMA, VAR-ARCH, and other traditional time series as input.

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**Author Contributions:** Conceptualization, R.E.C., H.Y.; methodology, R.E.C., H.Y.; software, R.E.C., H.Y.; validation, R.E.C., H.Y.; formal analysis, R.E.C., H.Y.; investigation, R.E.C., H.Y.; resources, R.E.C., H.Y.; Writing—original draft, R.E.C., H.Y.; writing—review and editing, R.E.C., H.Y.; visualization, R.E.C., H.Y.; supervision, R.E.C., H.Y., R.-C.C., M.B.; project administration, R.E.C., H.Y., R.-C.C., N.E.G., B.D.S., T.T., M.B., P.U.G., B.P.; funding acquisition, R.E.C., R.-C.C., T.T., M.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research fully supported by Faculty of Business and Economics, University of Indonesia. This research is part of Ministry of Science and Technology, Taiwan [MOST-109-2622-E-324-004]. This research is part of Chaoyang University of Technology and the Higher Education Sprout Project, Ministry of Education (MOE), Taiwan, under the project name: "The R&D and the cultivation of talent for health-enhancement products". This research is fully supported by the Directorate General of Research and Community Service, the Ministry of Research, and Technology/National Agency for Research and Innovation of the Republic of Indonesia through World-Class Research Program 2021.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Supplementary code to this article can be found online at https:// github.com/Rezzy94/cascadenn (accessed on 1 May 2021). The copyright of this programming was officially registered on May 31, 2021, by the Directorate General of Intellectual Property—Ministry of Law and Human Rights, the Republic of Indonesia, with the registration number [EC00202125523]

and [000252427], valid for 50 (fifty) years from the first announcement of the work. This copyright registration letter or related rights products are in accordance with article 72 of law number 28 of 2014 concerning copyright.

**Conflicts of Interest:** The authors declare no conflict of interest.
