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In addition to applying the original methods, as they are proposed in the state of the art, we perform the variable selection through techniques like Lasso, Correlation Coefficients (CC), Recursive Feature Elimination (RFE), and Random Forest Feature Importance (RFFI). We then compare time series based models, regression models, neural networks, and non-parametric approaches. Performance is evaluated using metrics including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), Residual Standard Deviation (RSD), and the Coefficient of Determination (R\n                    <jats:sup>2<\/jats:sup>\n                    ). The results show that Random Forest and feature-selection\u2013based Lasso achieve the highest accuracy for predicting the total call volume for each hour of the day throughout the year. For daily call volume, time series\u2013based methods perform best when using weather conditions and temporal variables selected by the RFFI method.\n                  <\/jats:p>","DOI":"10.1145\/3785661","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T12:03:12Z","timestamp":1766145792000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["State-of-the-Art Review and Comparative Experimentation of Emergency Call Prediction Models"],"prefix":"10.1145","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0112-9994","authenticated-orcid":false,"given":"Feriel","family":"Fass","sequence":"first","affiliation":[{"name":"D\u00e9partement d'informatique, Universit\u00e9 de Sherbrooke Facult\u00e9 des Sciences","place":["Sherbrooke, Canada"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8519-7916","authenticated-orcid":false,"given":"Hadia","family":"Mecheri","sequence":"additional","affiliation":[{"name":"D\u00e9partement d'informatique, Universit\u00e9 de Sherbrooke Facult\u00e9 des Sciences","place":["Sherbrooke, Canada"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4188-1361","authenticated-orcid":false,"given":"Djemel","family":"Ziou","sequence":"additional","affiliation":[{"name":"D\u00e9partement d'informatique, Universit\u00e9 de Sherbrooke Facult\u00e9 des Sciences","place":["Sherbrooke, Canada"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4509-8702","authenticated-orcid":false,"given":"Jessica","family":"L\u00e9vesque","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Sherbrooke \u00c9cole de Gestion","place":["Sherbrooke, Canada"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"A. 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