Sökning: "Flight Search Engine"
Hittade 4 uppsatser innehållade orden Flight Search Engine.
1. Flight search engine CPU consumption prediction
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The flight search engine is a technology used in the air travel industry. It allows the traveler to search and book for the best flight options, such as the combination of flights while keeping the best services, options, and price. The computation for a flight search query can be very intensive given its parameters and complexity. LÄS MER
2. Predictive Maintenance for RM12 with Machine Learning
Magister-uppsats, Högskolan i Halmstad/Akademin för ekonomi, teknik och naturvetenskapSammanfattning : Few components within mechanical engineering possess the fatigue resistance as of high-pressure turbine blades found in jet engines. This as they are designed to perform in extensively high temperatures under severe loading which causes degradation to be an important aspect despite a design, optimized for its environment. LÄS MER
3. GDPR ́s Impact on Sales at Flygresor.se: A Regression Analysis
Kandidat-uppsats, KTH/Matematisk statistikSammanfattning : The possible effects of the General Data Protections Regulations (GDPR) have been widely discussed among policymakers, stakeholders and ordinary people who are the objective for data collection. The purpose of GDPR is to protect people’s integrity and increase transparency for how personal data is used. LÄS MER
4. A Study on Comparison Websites in the Airline Industry and Using CART Methods to Determine Key Parameters in Flight Search Conversion
Kandidat-uppsats, KTH/Matematisk statistikSammanfattning : This bachelor thesis in applied mathematics and industrial engineering and management aimed to identify relationships between search parameters in flight comparison search engines and the exit conversion rate, while also investigating how the emergence of such comparison search engines has impacted the airline industry. To identify such relationships, several classification models were employed in conjunction with several sampling methods to produce a predictive model using the program R. LÄS MER