Sökning: "integrated network model"

Visar resultat 1 - 5 av 152 uppsatser innehållade orden integrated network model.

  1. 1. ML implementation for analyzing and estimating product prices

    Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
    Nyckelord :Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

    Sammanfattning : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. LÄS MER

  3. 2. Book retrieval system : Developing a service for efficient library book retrievalusing particle swarm optimization

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Adam Woods; [2024]
    Nyckelord :Particle swarm optimization; indoor positioning system; machine learning; Wi-Fi; RSSI; RTT; artificial neural network; ADAM optimizer; Keras; TensorFlow;

    Sammanfattning : Traditional methods for locating books and resources in libraries often entail browsing catalogsor manual searching that are time-consuming and inefficient. This thesis investigates thepotential of automated digital services to streamline this process, by utilizing Wi-Fi signal datafor precise indoor localization. LÄS MER

  4. 3. Interactive Visualization of Network Models in JavaScript/TypeScript for Web-based Applications

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Morrow Erik; [2023]
    Nyckelord :Networks; Information visualization; Information Theory; Interactive visualization; Nätverk; Informationsvisualisering; Informationsteori; Interaktiv visualisering;

    Sammanfattning : Networks of nodes and links are powerful tools to model complex systems, however, when the number of nodes and links grows to the thousands then even the network becomes too complex to comprehend unless we can simplify and highlight the networks underlying structure. The map equation is a method developed by the researchers at IntegratedScience Lab that uses an information theoretic approach to reveal community structure using the flow of information on the network modeled with random walks. LÄS MER

  5. 4. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Shiwei Dong; [2023]
    Nyckelord :;

    Sammanfattning : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. LÄS MER

  7. 5. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
    Nyckelord :;

    Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER