Sökning: "machine learning lstm"
Visar resultat 1 - 5 av 196 uppsatser innehållade orden machine learning lstm.
- Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik
Sammanfattning : Building operations account for a large amount of energy usage and the HVAC (Heating, Ventilation and Air Conditioning) systems are the largest consumer of energy in this sector. To reduce this demand, more energy-efficient control algorithms are implemented and a popular choice for a controller is the model predictive control. LÄS MER
- Master-uppsats, Linköpings universitet/Institutionen för datavetenskap
Sammanfattning : Fraud is a common crime within the insurance industry, and insurance companies want to quickly identify fraudulent claimants as they often result in higher premiums for honest customers. Due to the digital transformation where the sheer volume and complexity of available data has grown, manual fraud detection is no longer suitable. LÄS MER
3. Predicting the Options Expiration Effect Using Machine Learning Models Trained With Gamma Exposure DataKandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The option expiration effect is a well-studied phenome, however, few studies have implemented machine learning models to predict the effect on the underlying stock market due to options expiration. In this paper four machine learning models, SVM, random forest, AdaBoost, and LSTM, are evaluated on their ability to predict whether the underlying index rises or not on the day of option expiration. LÄS MER
4. Prediction of the number of weekly covid-19 infections : A comparison of machine learning methodsMaster-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi
Sammanfattning : The thesis two-folded problem aim was to identify and evaluate candidate Machine Learning (ML) methods and performance methods, for predicting the weekly number of covid-19 infections. The two-folded problem aim was created from studying public health studies where several challenges were identified. LÄS MER
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : In recent years, machine learning models have gained traction in the field of empirical asset pricing for their risk premium prediction performance. In this thesis, we build upon the work of  by first evaluating models similar to their best performing model in a similar fashion, by using the same dataset and measures, and then expanding upon that. LÄS MER