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Nature Environmental Protection, 2023, 4(2); doi: 10.38007/NEP.2023.040202.

Evaluation and Optimization of Nature Reserve Interpretation System Based on Genetic Algorithm

Author(s)

Manuela Chamizo-Borreguero

Corresponding Author:
Manuela Chamizo-Borreguero
Affiliation(s)

Departamento de ingeniería, Universidad Tecnológica del Perú, Lima 15487, Peru

Abstract

As an important part of tourism services, the interpretation system has received extensive attention in recent years. However, in addition to Taiwan, China’s research on interpretation is still in its infancy. Compared with other countries, there are obvious limitations in research participation, research objects, research content and research methods. This paper aimed to study how to evaluate and optimize the interpretation system of nature reserves based on Genetic Algorithm (GA) and Satisfaction Performance Analysis (IPA). Through a questionnaire survey of tourists, this experiment found that 44.89% of tourists were satisfied with the environmental interpretation system of Z Nature Reserve, and only 2.27% of tourists were not satisfied. It can be seen from the data that tourists were highly satisfied with the environmental interpretation system of Z Nature Reserve. Environmental interpretation is an effective way to carry out environmental education and develop ecotourism. It involves environmental protection, education, tourism, management and other fields. It can play an important role in better understanding the relationship between environment and development, environment and human survival.

Keywords

Nature Reserve, Genetic Algorithm, Interpretation System, Satisfaction Analysis Model Method, Evaluation and Optimization

Cite This Paper

Manuela Chamizo-Borreguero. Evaluation and Optimization of Nature Reserve Interpretation System Based on Genetic Algorithm. Nature Environmental Protection (2023), Vol. 4, Issue 2: 10-21. https://doi.org/10.38007/NEP.2023.040202.

References

[1] Gritsan Yuriy I., Kunakh Olga M., Dubinina Julia J., Kotsun Vadim I., Tkalich Yuriy I. The catena aspect of the landscape diversity of the «Dnipro-Orilsky» natural reserve. Journal of Geology, Geography and Geoecology. (2019) 28(3): 417-431. https://doi.org/10.15421/111939

[2] Kujirakwinja D., Plumptre A.J., Twendilonge A., Mitamba G., Mubalama L., Wasso J.D.D., et al. Establishing the Itombwe Natural Reserve: science, participatory consultations and zoning. Oryx. (2019) 53(1): 49-57. https://doi.org/10.1017/S0030605317001478

[3] Mo R. R., Guoquan Wang, Ding Yang, Weihai Li. Two new species of Amphinemura (Plecoptera: Nemouridae) from Damingshan National Natural Reserve of Guangxi, China. Zootaxa. (2020) 4751(1): 131-142. https://doi.org/10.11646/zootaxa.4751.1.7

[4] ZengRang Xu, Xin Zheng, MingMing Jin. Harmonizing conflicts of land multifunction in natural reserves-Qiangtang National Natural Reserve as an example. Science & Technology Review. (2018) 36(7): 8-13.

[5] Mudrak O. V., YelisavenkoYu.A., Polishchuk V.M., Mudrak G.V.. "Assessment of forest ecosystems of Eastern Podillya natural reserve fund in the regional econet structure." Ukrainian Journal of Ecology 9.1 (2019): 187-192. https://doi.org/10.15421/2019_819

[6] Spinelli Andrea. Returning of Hippocampus hippocampus (Linnaeus, 1758)(Syngnathidae) in the Faro Lake-oriented Natural Reserve of Capo Peloro, Italy. Natural product research. (2020) 34(4): 595-598. https://doi.org/10.1080/14786419.2018.1490909

[7] Lapolo Nurain, Ramli Utina, Dewi Wahyuni K. Baderan. Diversity and density of crabs in degraded mangrove area at Tanjung Panjang Nature Reserve in Gorontalo, Indonesia. Biodiversitas Journal of Biological Diversity. (2018) 19(3): 1154-1159. https://doi.org/10.13057/biodiv/d190351

[8] Polchaninova Nina. Spiders (Arachnida: Araneae) in dry grasslands of south Ukraine: a case study of Yelanetskyi Steppe Natural Reserve. Arachnologische Mitteilungen: Arachnology Letters. (2021) 61(1): 27-35. https://doi.org/10.30963/aramit6105

[9] Ortiz Estefania, Tominaga Masako, Cardace Dawn, Schrenk Matthew O., Hoehler Tori M., Kubo Michael D., et al. Geophysical characterization of serpentinite hosted hydrogeology at the McLaughlin Natural Reserve, Coast Range Ophiolite. Geochemistry, Geophysics, Geosystems. (2018) 19(1): 114-131. https://doi.org/10.1002/2017GC007001

[10] Chernova N. V. Overview of the fish fauna of the Chaunskaya basin-the area of the natural reserve "Chaunskaya Guba" and the port of Pevek (East Siberian Arctic). Proceedings of the Zoological Institute RAS. (2022) 326(1): 30-42. https://doi.org/10.31610/trudyzin/2022.326.1.30

[11] Jinxiang Chen, Feng Zhao, Yanguang Sun, Yilan Yin. Improved XGBoost model based on genetic algorithm. International Journal of Computer Applications in Technology. (2020) 62(3): 240-245. https://doi.org/10.1504/IJCAT.2020.106571

[12] Jalali Zahra, Esmatullah Noorzai, Shahin Heidari. Design and optimization of form and facade of an office building using the genetic algorithm. Science and Technology for the Built Environment. (2020) 26(2): 128-140. https://doi.org/10.1080/23744731.2019.1624095

[13] Shanmugasundaram N., Sushita K., Pradeep Kumar S., Ganesh E.N. Genetic algorithm-based road network design for optimising the vehicle travel distance. International Journal of Vehicle Information and Communication Systems. (2019) 4(4): 344-354. https://doi.org/10.1504/IJVICS.2019.103931

[14] Xiangliu Chen, Xiaoguang Yue, Rita Li, Zhumadillayeva Ainur, Ruru Liu. Design and application of an improved genetic algorithm to a class scheduling system. International Journal of Emerging Technologies in Learning (iJET). (2021) 16(1): 44-59. https://doi.org/10.3991/ijet.v16i01.18225

[15] Rostami Mehrdad, Kamal Berahmand, Saman Forouzandeh. A novel community detection based genetic algorithm for feature selection. Journal of Big Data. (2021) 8(1): 1-27. https://doi.org/10.1186/s40537-020-00398-3