Sökning: "Evolutionary Algorithms"

Visar resultat 1 - 5 av 78 uppsatser innehållade orden Evolutionary Algorithms.

1. 1. Deployment planning of UAV Base Stations using Multi Objective Evolutionary Algorithms (MOEA)

   Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Nadir Arfi; [2023]
   Nyckelord :Deployment planning; UAV-Base Stations; multi-objective; evolutionary algorithms; fitness approximation;

   Sammanfattning : This research study focuses on solving the deployment planning problem for UAV-BSs using Multi-Objective Evolutionary Algorithms (MOEAs). The main research objectives encompass gridbased modelling of the target area, investigating evolution parameters, and evaluating algorithm performance in diverse deployment scenarios. LÄS MER

3. 2. Database Tuning using Evolutionary and Search Algorithms

   Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Erica Raneblad; [2023]
   Nyckelord :Database tuning; Performance optimization; Evolutionary algorithms; Particle Swarm Optimization; Database configuration; Hill Climbing;

   Sammanfattning : Achieving optimal performance of a database can be crucial for many businesses, and tuning its configuration parameters is a necessary step in this process. Many existing tuning methods involve complex machine learning algorithms and require large amounts of historical data from the system being tuned. LÄS MER

4. 3. Automated Image Pre-Processing for Optimized Text Extraction Using Reinforcement Learning and Genetic Algorithms

   Kandidat-uppsats,

   Författare :Rahmat Rohoullah; Månsson Joakim; [2023]
   Nyckelord :BRISK; YOLO; Reinforcement learning; Evolutionary algorithm; OCR; Image pre-processing; Computer vision; BRISK; YOLO; Förstärkningslärning; Evolutionär algorithm; OCR; Bildförbehandling; Datorseende;

   Sammanfattning : This project aims to develop an automated image pre-processing chain to extract valuable information from appliance labels before recycling. The primary goal is to improve optical character recognition accuracy by addressing noise issues using reinforcement learning and an evolutionary algorithm. LÄS MER

5. 4. Trajectory Optimisation of a Spacecraft Swarm Maximising Gravitational Signal

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :Rasmus Maråk; [2023]
   Nyckelord :Spacecraft Swarms; Trajectory Optimisation; Impulsive Manoeuvres; Evolutionary Algorithms; Polyhedral Gravity Model; Small Body Exploration; Discrete Spherical Grids; Svärmande rymdfarkoster; Banoptimering; Impulsiva manövrar; Evolutionära Algoritmer; Polyhedral gravitationsmodell; Utforksning av små kroppar i solsystemet; Diskreta sfäriska rutnät;

   Sammanfattning : Proper modelling of the gravitational fields of irregularly shaped asteroids and comets is an essential yet challenging part of any spacecraft visit and flyby to these bodies. Accurate density representations provide crucial information for proximity missions, which rely heavily on it to design safe and efficient trajectories. LÄS MER

7. 5. A comparative analysis of database sanitization techniques for privacy-preserving association rule mining

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

   Författare :Charlie Mårtensson; [2023]
   Nyckelord :Association rule hiding; privacy-preserving data mining; evolutionary algorithms; performance evaluation; Associationsregeldöljning; sekretessbevarande datautvinning; evolutionära algoritmer; prestandaevaluering;

   Sammanfattning : Association rule hiding (ARH) is the process of modifying a transaction database to prevent sensitive patterns (association rules) from discovery by data miners. An optimal ARH technique successfully hides all sensitive patterns while leaving all nonsensitive patterns public. LÄS MER