{"id":25,"date":"2024-01-07T03:12:17","date_gmt":"2024-01-07T03:12:17","guid":{"rendered":"https:\/\/theglobalforecast.com\/?p=25"},"modified":"2024-01-08T03:13:00","modified_gmt":"2024-01-08T03:13:00","slug":"energy-consumption-forecast","status":"publish","type":"post","link":"https:\/\/theglobalforecast.com\/index.php\/2024\/01\/07\/energy-consumption-forecast\/","title":{"rendered":"Energy Consumption Forecast"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"25\" class=\"elementor elementor-25\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e812a15 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e812a15\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e369218\" data-id=\"e369218\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e58af2e elementor-widget elementor-widget-text-editor\" data-id=\"e58af2e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\tThe analysis explores the model&#8217;s behavior by varying income, job type, and city. Notably, the model&#8217;s predictions are predominantly influenced by income, revealing a clear positive correlation. As income increases, energy consumption tends to rise. On the other hand, simulating job types and cities yields relatively consistent results, suggesting that the model&#8217;s predictions are less sensitive to these categorical features. This indicates that income is the most significant factor in predicting energy consumption, while job type and city have a relatively minor impact.\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ec70875 elementor-widget elementor-widget-image\" data-id=\"ec70875\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/theglobalforecast.com\/wp-content\/uploads\/2024\/01\/GettyImages-1208790364-1024x576-1.jpg\" class=\"attachment-large size-large wp-image-14\" alt=\"\" srcset=\"https:\/\/theglobalforecast.com\/wp-content\/uploads\/2024\/01\/GettyImages-1208790364-1024x576-1.jpg 1024w, https:\/\/theglobalforecast.com\/wp-content\/uploads\/2024\/01\/GettyImages-1208790364-1024x576-1-300x169.jpg 300w, https:\/\/theglobalforecast.com\/wp-content\/uploads\/2024\/01\/GettyImages-1208790364-1024x576-1-768x432.jpg 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-716ee30 elementor-widget elementor-widget-text-editor\" data-id=\"716ee30\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p>In conclusion, the Random Forest Regressor model demonstrates robust predictive capabilities for estimating energy consumption. It achieves good accuracy in its predictions, as evidenced by low MAE, MSE, and a high R2 score. The model&#8217;s reliance on income as the dominant predictor implies that changes in income strongly influence energy consumption. However, the model appears less sensitive to variations in job type and city. These insights can help stakeholders better understand the dynamics of energy consumption and make informed decisions for resource allocation and policy planning.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>The analysis explores the model&#8217;s behavior by varying income, job type, and city. Notably, the model&#8217;s predictions are predominantly influenced [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/posts\/25"}],"collection":[{"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/comments?post=25"}],"version-history":[{"count":10,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/posts\/25\/revisions"}],"predecessor-version":[{"id":36,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/posts\/25\/revisions\/36"}],"wp:attachment":[{"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/media?parent=25"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/categories?post=25"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/theglobalforecast.com\/index.php\/wp-json\/wp\/v2\/tags?post=25"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}