Essays about: "support for learning"

Showing result 1 - 5 of 1281 essays containing the words support for learning.

  1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Nikolaos Staikos; [2024]
    Keywords : Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Abstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE

  2. 2. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Anastasia Sarelli; [2024]
    Keywords : Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

    Abstract : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. READ MORE

  3. 3. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting

    University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Author : Elie Roudiere; [2024]
    Keywords : Railway; Track geometry; Machine learning; Statistics; Predictive maintenance; Botniabanan; Järnväg; spårgeometri; maskininlärning; statistik; förebyggande underhåll; Botniabanan;

    Abstract : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. READ MORE

  4. 4. Android Malware Detection Using Machine Learning

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Rahul Sai Kesani; [2024]
    Keywords : Malware; Machine Learning; Random Forest; Sequential Neural Network.;

    Abstract : Background. The Android smartphone, with its wide range of uses and excellent performance, has attracted numerous users. Still, this domination of the Android platform also has motivated the attackers to develop malware. The traditional methodology which detects the malware based on the signature is unfit to discover unknown applications. READ MORE

  5. 5. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Alexander Florean; [2024]
    Keywords : Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

    Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE