{"id":6893,"date":"2020-07-03T12:55:25","date_gmt":"2020-07-03T10:55:25","guid":{"rendered":"https:\/\/nr.no\/?post_type=bc_area&#038;p=6893"},"modified":"2024-09-09T11:31:22","modified_gmt":"2024-09-09T09:31:22","slug":"statistical-modeling-machine-learning-and-artificial-intelligence-ai","status":"publish","type":"bc_area","link":"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/","title":{"rendered":"Statistical modelling, Machine learning and Artificial intelligence (AI)"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><strong>We develop methods and practical applications that encompass the spectrum of statistical modelling and machine learning. The very components of artificial intelligence, our expertise enables us to harness the power of AI to solve problems in a range of research areas and in multiple industries.  <\/strong><\/p>\n\n\n\n\n\n<h2 class=\"wp-block-heading\">Statistical modelling<\/h2>\n\n\n\n<p>Statistical modelling is about understanding contexts and making forecasts based when coincidences and uncertainty are involved.<\/p>\n\n\n\n<p>While statistical modelling and machine learning are sometimes used interchangeably, machine learning is often able to detect patterns without the use of models. As we have comprehensive experience and knowledge in both areas, we are able to customise our methods to find the most accurate solution for each problem.<\/p>\n\n\n\n\n\n<h2 class=\"wp-block-heading\">Machine learning<\/h2>\n\n\n\n<p>Machine learning enables computers to automatically detect patterns in data, and the objective is to train algorithms to predict events or make decisions without being explicitly instructed to do so. <\/p>\n\n\n\n<p>As a general tool, machine learning can be utilised in most domains, and we work with a number of clients and partners across different sectors,  including healthcare, finance and climate. <\/p>\n\n\n\n<p>We are particularly interested in enhancing transparency to better understand how systems based on machine learning systems calculate predictions and determine results. In addition to ongoing research in eXplainable artificial intelligence (XAI), we have created the digital toolkit, eXplego, which intends to ease navigation for developers working in this environment. <\/p>\n\n\n\n\n\n<h2 class=\"wp-block-heading\">Language technology<\/h2>\n\n\n\n<p>Language technology is a collective term for various technologies that use natural language as data. <\/p>\n\n\n\n<p>We work with language technology in a number of ways, including text mining, automated transcription and translation. We are especially dedicated to the development of Norwegian language technology and other models with modest amounts of training data available. <\/p>\n\n\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Geomodelling<\/h2>\n\n\n\n<p>We have provided advanced statistical and mathematical modelling for the oil and gas industry for almost forty years.<\/p>\n\n\n\n<p>Geomodelling combines geological knowledge with data in a statistical model, and enables us to understand and predict natural processes on the Earth&#8217;s subsurface or geological features. Geomodels are useful for decision support in all situations where geology is a crucial factor, such as in the  petroleum industry.<\/p>\n\n\n\n<p><br><\/p>\n\n\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\">Research areas<\/h3>\n\n\n\t\t<div id=\"post-type-multi-block_9f7516ccea0517651257063694c9684f\" class=\"wp-block-post-type-multi type-manual style-card-bc_area t2-grid\">\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-6\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/machine-learning\/\" class=\"card-list card-list-area\">\n\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\tMachine learning\n\t\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-6\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/statistical-modeling\/\" class=\"card-list card-list-area\">\n\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\tStatistical modelling\n\t\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-6\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/language-technology\/\" class=\"card-list card-list-area\">\n\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\tLanguage technology\n\t\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-6\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/geomodeling\/\" class=\"card-list card-list-area\">\n\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\tGeomodelling\n\t\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<p class=\"has-text-align-center\"><strong>Contact <\/strong><\/p>\n\n\n\t\t<div id=\"post-type-multi-block_5d471c98901f968a8bafadd060996462\" class=\"wp-block-post-type-multi type-manual style-card-bc_employee t2-grid\">\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-12\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/employees\/petter-abrahamsen\/\" class='card-employee'>\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/05\/petter-abrahamsen-23.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-employee__content\">\n\t\t\t<p class=\"card-employee__name\">Petter Abrahamsen<\/p>\n\t\t\t\t\t\t\t<p class=\"card-employee__position\">Research Director<\/p>\n\t\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\t<\/div>\n\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-12\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/employees\/anders-loland\/\" class='card-employee'>\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/05\/anders-loland-12.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-employee__content\">\n\t\t\t<p class=\"card-employee__name\">Anders L\u00f8land<\/p>\n\t\t\t\t\t\t\t<p class=\"card-employee__position\">Research Director<\/p>\n\t\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\t<\/div>\n\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-12\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/employees\/kjersti-aas\/\" class='card-employee'>\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2026\/01\/kjersti-aas-20.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-employee__content\">\n\t\t\t<p class=\"card-employee__name\">Kjersti Aas<\/p>\n\t\t\t\t\t\t\t<p class=\"card-employee__position\">Research Director SAMBA<\/p>\n\t\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\t<\/div>\n\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n<\/div>\n\n\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\">Selected research topics<\/h3>\n\n\n\n<div class=\"wp-block-group has-primary-200-background-color has-background\">\n<div class=\"wp-block-columns has-nr-light-green-background-color has-background is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-vertically-aligned-center is-layout-flow wp-block-column-is-layout-flow\">\n<p>Anomaly detection is a research topic in growth. Anomaly detection is about observing and analysing large data sets over time, and identifying and classifying divergent behaviour. <\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center is-layout-flow wp-block-column-is-layout-flow\">\t\t<div id=\"post-type-multi-block_ab07bc5f9207fd48a2706b6a3712639c\" class=\"wp-block-post-type-multi type-manual style-card t2-grid\">\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-12\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/anomaly-detection\/\" class=\"card-list card-list-default\">\n\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\t\t\tAnomaly detection\n\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-group has-primary-200-background-color has-background\">\n<div class=\"wp-block-columns has-nr-light-green-background-color has-background is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<p><\/p>\n\n\n\n<div class=\"wp-block-group\">\n<p>Explainable Artificial Intelligence (XAI) provides insight into how systems based on machine learning and artificial intelligence (AI) calculate predictions and make decisions. We have created eXplego, a digital toolkit, to ease navigation for developers working in this environment. <\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n\n\t\t<div id=\"post-type-multi-block_139a8373fb44a347af5d8c8970e66e19\" class=\"wp-block-post-type-multi type-manual style-card t2-grid\">\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-12\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/areas\/statistical-modeling-machine-learning-and-artificial-intelligence-ai\/explainable-artificial-intelligence-xai\/\" class=\"card-list card-list-default\">\n\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 24 24\" height=\"24\" width=\"24\" class=\"t2-icon t2-icon-arrowforward\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.9 4.259a1.438 1.438 0 0 1-.147.037c-.139.031-.339.201-.421.359-.084.161-.084.529-.001.685.035.066 1.361 1.416 2.947 3l2.882 2.88-10.19.02c-8.543.017-10.206.029-10.29.075-.282.155-.413.372-.413.685 0 .313.131.53.413.685.084.046 1.747.058 10.29.075l10.19.02-2.882 2.88c-1.586 1.584-2.912 2.934-2.947 3-.077.145-.085.521-.013.66a.849.849 0 0 0 .342.35c.156.082.526.081.68-.001.066-.035 1.735-1.681 3.709-3.656 2.526-2.53 3.606-3.637 3.65-3.742A.892.892 0 0 0 23.76 12a.892.892 0 0 0-.061-.271c-.044-.105-1.124-1.212-3.65-3.742-1.974-1.975-3.634-3.616-3.689-3.645-.105-.055-.392-.107-.46-.083\"\/><\/svg>\n\t\t\t\tExplainable Artificial Intelligence\n\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n<\/div>\n<\/div>\n\n\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\">Selected projects <\/h3>\n\n\n\t\t<div id=\"post-type-multi-block_37b29750e945f14c6f1ba3f8b4517329\" class=\"wp-block-post-type-multi type-manual style-card-bc_project-sm t2-grid\">\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/geophysical-inversion-to-geology\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/02\/GIG-feature-image.jpeg\" alt=\"Aerial shot of steep cliffs against a foggy, grey sky and dark seas.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Geomodelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">A consortium for geological assessments of the seabed (GIG)<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/a-credit-model-for-small-and-medium-sized-enterprises\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/06\/austin-distel-wD1LRb9OeEo-unsplash-scaled.jpg\" alt=\"A group of young professionals sit around a coffee table while a man in a white shirt and black jeans holds a presentation, pointing to a whiteboard. It is a modern corporate space and one person has a laptop open on his lap.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">A credit model for small and medium-sized businesses<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/tilstandsovervakning-i-vind-og-vannkraftverk\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/05\/Ovre_Leirfoss.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Anomaly detection in wind and hydropower plants\u00a0\u00a0<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/the-cleanup-project\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2020\/08\/garmin-b-DDkyGrfvp40-unsplash-1.jpg\" alt=\"Machine learning methods to automatically anonymize text documents with personal data\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Image analysis<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Automatically anonymising text documents (CLEANUP)<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/automatic-detection-and-prediction-of-anomalies-in-complex-it-systems\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2021\/11\/karsten-winegeart-pJ6HTjx-LV0-unsplash.jpg\" alt=\"Automatic detection and prediction of anomalies in complex IT systems\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Automatic detection and prediction of anomalies in complex IT systems<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/dynamic-pricing-of-short-term-rental-properties\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/01\/steven-ungermann-91gtDRwmfsw-unsplash-1-scaled.jpg\" alt=\"A white-painted living room featuring a desk, a beige sofa and coffee table and a round dining table with chairs. There are windows at the end of the room.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Dynamic pricing of short-term rental properties<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/estimating-population-density-and-disease-transmission-in-salmon-farms\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/01\/bob-brewer-udVjzhI9gXs-unsplash-scaled.jpg\" alt=\"An aerial view of an open water fish farm. Each section of the farm is a circular pen (cage) surrounded by water. Image by Bob Brewer via Unsplash.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Modelling population density and disease transmission in salmon farms<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/fish-stock-assessment-and-harvest-quota\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/12\/Fish_farming_on_Astafjorden_in_Gratangen_Troms_og_Finnmark_Norway_2022_June.jpg\" alt=\"The image shows a fish farm in Northern Norway and a boat passing by. In the background a mountainous coastline is visible.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Fish stock assessment and harvest quota<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/geopard-an-eventbased-object-model\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2021\/07\/leopard-on-mountain-2553358.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Geomodelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">An event-based object model (GEOPARD)<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/prediction-of-vys-passenger-traffic\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2022\/02\/Tog-og-passasjerer-pa-Oslo-S-VY-01684-Foto_Mads__Kristiansen-scaled.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">How many passengers travel with Vy at any given time?<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/predicting-the-market-value-of-liabilities\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/11\/micheile-henderson-SoT4-mZhyhE-unsplash-scaled.jpg\" alt=\"A green plant in a clear glass cup filled with coins.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Predicting the market value of liabilities<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/rewacc\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2024\/09\/bilde1-3-1.jpg\" alt=\"The image shows a green, open industrial waster container (a skip) with various contents piled into it.\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Machine learning<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Smarter waste management with machine learning and radar sensors (ReWaCC)<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"t2-grid-item-col-4\">\n\t\t\t\t\t\t<a href=\"https:\/\/nr.no\/en\/projects\/timothy-cultivars-under-climate-change\/\" class=\"card-post card-project\">\n\t\t\t\t\t<figure>\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2021\/11\/Timotei.jpg\" alt=\"\">\n\t\t\t<\/figure>\n\t\t\t\t<div class=\"card-post__content\">\n\t\t\t\t\t\t\t<ul class=\"card-post__categories\">\n\t\t\t\t\t\t\t\t\t\t\t<li>Statistical modelling<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<h3 class=\"card-post__title\">Timothy cultivars under climate change<\/h3>\n\t\t<\/div>\n\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t","protected":false},"featured_media":6872,"parent":0,"menu_order":35,"template":"","meta":{"_acf_changed":false,"_trash_the_other_posts":false,"editor_notices":[],"footnotes":""},"class_list":["post-6893","bc_area","type-bc_area","status-publish","has-post-thumbnail"],"acf":[],"_links":{"self":[{"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/bc_area\/6893","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/bc_area"}],"about":[{"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/types\/bc_area"}],"version-history":[{"count":4,"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/bc_area\/6893\/revisions"}],"predecessor-version":[{"id":32708,"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/bc_area\/6893\/revisions\/32708"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/media\/6872"}],"wp:attachment":[{"href":"https:\/\/nr.no\/en\/wp-json\/wp\/v2\/media?parent=6893"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}