• A Machine Learning approach for Building Segmentation using laser data 

      Finnesand, Erik (Master thesis, 2023)
      Buildings are essential for population information, city management, and policy-making. Various computer vision technologies have proven helpful in building-related scenarios, where segmentation has proven to be the most ...
    • A Web Based Solution to Track Trawl Vessel Activities Over Pipelines in Norwegian Continental Shelf 

      Palanisamy, Anandhakumar (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      Vessel Activities such as trawling and anchoring represent a risk to offshore marine structures such as pipelines, subsea structures, cables and platforms. Third party interference is a major contributor to the damage and ...
    • A Widespread Review of Smart Grids Towards Smart Cities 

      Farmanbar, Mina; Parham, Kiyan; Arild, Øystein; Rong, Chunming (Journal article; Peer reviewed, 2019-11)
      Nowadays, the importance of energy management and optimization by means of smart devices has arisen as an important issue. On the other hand, the intelligent application of smart devices stands as a key element in establishing ...
    • A Widespread Review of Smart Grids Towards Smart Cities 

      Farmanbar, Mina; Parham, Kiyan; Arild, Øystein; Chunming, Rong (Journal article; Peer reviewed, 2019-11)
      Nowadays, the importance of energy management and optimization by means of smart devices has arisen as an important issue. On the other hand, the intelligent application of smart devices stands as a key element in establishing ...
    • Analysis of Residential Household Energy Consumption Using Smart Meter Data 

      Nwemambu, Chibuzor Valentina (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)
      The need to change the source of electricity generation is apparent in the effect of climate change on the environment. Asides from the source change to renewable energy, the necessity for residents to understand their ...
    • Comparative Analysis of Sampling Methods for Imbalanced Classification 

      Li, Rongbing; Koloszyc, Piotr (Master thesis, 2023)
      Assigning class labels to instances is a key component of the machine learning technique known as classification predictive modeling. While concentrating largely on balanced classification problems, which are thought to ...
    • Design og implementering av et interaktivt webgrensesnitt for prognoser om energiforbruk 

      Havstad, Daniel; Vo, Danny; Mohr, Sindre Reidar (Bachelor thesis, 2022)
      Prosjektet bruker modeller for prediksjoner av strømforbruket til hushold i London. Det finnes mange algoritmer som en kan bruke i maskinlærings modeller, de vi har valgt å se nærmere på er LSTM, Perceptron, SLP, MLP, ...
    • Design og implementering av et interaktivt webgrensesnitt for prognoser om energiforbruk 

      Havstad, Daniel; Vo, Danny; Mohr, Sindre Reidar (Bachelor thesis, 2022)
      Prosjektet bruker modeller for prediksjoner av strømforbruket til hushold i London. Det finnes mange algoritmer som en kan bruke i maskinlærings modeller, de vi har valgt å se nærmere på er LSTM, Perceptron, SLP, MLP, ...
    • Detection of MITM using AI 

      Fernandez, Alistar Thomas Cyril (Master thesis, 2023)
      In the current digital era, there is a rising need for interconnected networks and communication systems, which raises the risk of cyberattacks, notably the Man-in-the-Middle (MitM) attack. An adversary intercepts and ...
    • Machine Learning Based Load Forecasting 

      Høllesli, Shiela Marie (Master thesis, 2022)
      Population is increasing rapidly and all the demands like electricity are also increasing. The government in England installed smart meters in order to analyze and follow better the energy consumption. Machine learning ...
    • Short-Term Load Forecasting Using Smart Meter Data: A Generalization Analysis 

      Mehdipourpirbazari, Aida; Farmanbar, Mina; Chakravorty, Antorweep; Chunming, Rong (Peer reviewed; Journal article, 2020-04)
      Short-term load forecasting ensures the efficient operation of power systems besides affording continuous power supply for energy consumers. Smart meters that are capable of providing detailed information on buildings ...
    • Smart Meter Based Load Forecasting for Residential Customers Using Machine Learning Algorithms 

      Resulaj, Redjol (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-12)
      The focus of this thesis is the use of machine learning algorithms to perform next step short term load forecasting on fifty five households in Stavanger, Norway. A dataset containing electricity consumption data for more ...
    • Triangulum City Dashboard: An Interactive Data Analytic Platform for Visualizing Smart City Performance 

      Farmanbar, Mina; Chunming, Rong (Peer reviewed; Journal article, 2020-02)
      Cities are becoming smarter by incorporating hardware technology, software systems, and network infrastructure that provide Information Technology (IT) systems with real-time awareness of the real world. What makes a “smart ...
    • Unlocking Household Electricity Consumption in Pakistan 

      Amber, Khuram Pervez; Ahmad, Rizwan; Farmanbar, Mina; Bashir, Muhammad Anser; Mehmood, Sajid; Khan, Muhammad Sajid; Saeed, Muhammad Umer (Peer reviewed; Journal article, 2021-11)
      In Pakistan, data for household electricity consumption are available in the form of monthly electricity bills only, and, therefore, are not helpful in establishing appliance-wise consumption. Further, it does not help in ...
    • A web based solution to track trawl vessel activities over pipelines in Norwegian Continental Shelf 

      Farmanbar, Mina; Palanisamy, Anandhakumar; Høydal, Anne Britt; Keprate, Arvind; Haug, Gjermund (Peer reviewed; Journal article, 2019)
      Vessel activities such as trawling and anchoring potentially affect pipeline integrity. Therefore, the detailed information about the trawl activity in the area is essential for accurate assessment of pipeline, where to ...