[1] Rudel, T. (2023). Population, development and tropical deforestation: a cross-national study. In The causes of tropical deforestation (pp. 96–105). Routledge.
[2] Eisenmenger, N., Pichler, M., Krenmayr, N., Noll, D., Plank, B., Schalmann, E., … & Gingrich, S. (2020). The sustainable development goals prioritize economic growth over sustainable resource use: a critical reflection on the SDGs from a socio-ecological perspective. Sustainability science, 15, 1101–1110.
[3] Calka, B., Orych, A., Bielecka, E., & Mozuriunaite, S. (2022). The ratio of the land consumption rate to the population growth rate: A framework for the achievement of the spatiotemporal pattern in Poland and Lithuania. Remote sensing, 14(5), 1074. https://doi.org/10.3390/rs14051074
[4] Koomen, E., Van Bemmel, M. S., Van Huijstee, J., Andrée, B. P. J., Ferdinand, P. A., & Van Rijn, F. J. A. (2023). An integrated global model of local urban development and population change. Computers, environment and urban systems, 100, 101935. https://doi.org/10.1016/j.compenvurbsys.2022.101935
[5] Johnson, T. F., Isaac, N. J. B., Paviolo, A., & González-Suárez, M. (2023). Socioeconomic factors predict population changes of large carnivores better than climate change or habitat loss. Nature communications, 14(1), 74. https://www.nature.com/articles/s41467-022-35665-9
[6] Morgenstern, J. D., Buajitti, E., O’Neill, M., Piggott, T., Goel, V., Fridman, D., … & Rosella, L. C. (2020). Predicting population health with machine learning: a scoping review. BMJ open, 10(10), e037860.
[7] Munir, K., & Shahid, F. S. U. (2021). Role of demographic factors in economic growth of South Asian countries. Journal of economic studies, 48(3), 557–570.
[8] Canudas-Romo, V., Shen, T., & Payne, C. F. (2022). The components of change in population growth rates. Demography, 59(2), 417–431.
[9] Horiuchi, S. (1991). Assessing the effects of mortality reduction on population ageing. Population bulletin of the united nations, 31(32), 38–51.
[10] Yaduvanshi, A., Singh, R., & Kumar, R. (2022). Population changes and sustainability of energy drive cooling demand related risks in urbanized India. Energy and buildings, 260, 111891. https://doi.org/10.1016/j.enbuild.2022.111891
[11] Aslam, R. W., Shu, H., & Yaseen, A. (2023). Monitoring the population change and urban growth of four major Pakistan cities through spatial analysis of open source data. Annals of gis, 29(3), 355–367. https://doi.org/10.1080/19475683.2023.2166989
[12] Salgado, M., Madureira, J., Mendes, A. S., Torres, A., Teixeira, J. P., & Oliveira, M. D. (2020). Environmental determinants of population health in urban settings. A systematic review. BMC public health, 20, 1–11.
[13] Shahvaroughi Farahani, M., & Razavi Hajiagha, S. H. (2021). Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models. Soft computing, 25(13), 8483–8513.
[14] Xue, J., & Shen, B. (2020). A novel swarm intelligence optimization approach: sparrow search algorithm. Systems science & control engineering, 8(1), 22–34.
[15] Zervoudakis, K., & Tsafarakis, S. (2020). A mayfly optimization algorithm. Computers & industrial engineering, 145, 106559. https://doi.org/10.1016/j.cie.2020.106559
[16] Pereira, J. L. J., Francisco, M. B., Diniz, C. A., Oliver, G. A., Cunha Jr, S. S., & Gomes, G. F. (2021). Lichtenberg algorithm: A novel hybrid physics-based meta-heuristic for global optimization. Expert systems with applications, 170, 114522. https://doi.org/10.1016/j.eswa.2020.114522
[17] Gad, A. G. (2022). Particle swarm optimization algorithm and its applications: a systematic review. Archives of computational methods in engineering, 29(5), 2531–2561.
[18] Ang, K. M., Chow, C. E., El-Kenawy, E.-S. M., Abdelhamid, A. A., Ibrahim, A., Karim, F. K., … & Lim, W. H. (2022). A modified particle swarm optimization algorithm for optimizing artificial neural network in classification tasks. Processes, 10(12), 2579. https://doi.org/10.3390/pr10122579
[19] Khandelwal, M. K., & Sharma, N. (2023). A survey on particle swarm optimization algorithm. International conference on communication and computational technologies (pp. 591–602). Springer.
[20] Khishe, M., & Mosavi, M. R. (2020). Chimp optimization algorithm. Expert systems with applications, 149, 113338. https://doi.org/10.1016/j.eswa.2020.113338
[21] Sohail, A. (2023). Genetic algorithms in the fields of artificial intelligence and data sciences. Annals of data science, 10(4), 1007–1018.
[22] Singh, G., & Gupta, N. (2022). A study of crossover operators in genetic algorithms. In Frontiers in nature-inspired industrial optimization (pp. 17–32). Springer. https://link.springer.com/chapter/10.1007/978-981-16-3128-3_2
[23] Zhang, H., & Zhang, Y. (2023). An improved sparrow search algorithm for optimizing support vector machines. IEEE access, 11, 8199–8206.
[24] Madhu, M. S., & others. (2022). Detection of liver disorder using quadratic support vector machine in comparison with rbf svm to measure the accuracy, precision, sensitivity and specificity. 2022 international conference on innovative computing, intelligent communication and smart electrical systems (ICSES) (pp. 1–7). IEEE.
)