Sökning: "the Prophet model"

Visar resultat 1 - 5 av 24 uppsatser innehållade orden the Prophet model.

1. 1. Can secular practice and education revive interest in religion in secular Sweden? : A study on the impact of secularism on religious education in Sweden

   Master-uppsats, Högskolan i Gävle/Avdelningen för humaniora

   Författare :MOHD NURUL MOMEN; [2023]
   Nyckelord :Islam: A monotheistic religion characterized by the doctrine of absolute submission to God and reverence for Muhammad as God s chief and last prophet. Islamism: A movement advocating the social and political establishment of Islamic fundamentalism. Quran: The sacred text of Islam; divided into 114 chapters; or suras: revered as the word of God; dictated to Muhammad by the archangel Gabriel and accepted as the foundation of Islamic law; religion; culture; and politics. Secularism: Free from preconceived notions and critical influences and allows one to see oneself as equal to another. It is in this context as indifference to or rejection or exclusion of religion and religious considerations. Religion: A unified system of beliefs and practices relative to sacred things. Or a set of beliefs concerning the cause; nature; and purpose of the universe; especially when considered as the creation of a superhuman agency or agencies; usually involving devotional and ritual observances; and often containing a moral code governing the conduct of human affairs.;

   Sammanfattning : Abstract: The thesis shows that there are no religious barriers in Sweden. It is entirely possible to teach religion in a secular way. LÄS MER

3. 2. Forecasting Monthly Swedish Air Traveler Volumes

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Mark Becker; Peter Jarvis; [2023]
   Nyckelord :Forecasting; SARIMA; Neural network autoregression; Exponential smoothing; the Prophet model; Random Walk; MAE; MAPE; RMSE;

   Sammanfattning : In this paper we conduct an out-of-sample forecasting exercise for monthly Swedish air traveler volumes. The models considered are multiplicative seasonal ARIMA, Neural network autoregression, Exponential smoothing, the Prophet model and a Random Walk as a benchmark model. LÄS MER

4. 3. Forecasting Efficiency in Cryptocurrency Markets : A machine learning case study

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

   Författare :Erik Persson; [2022]
   Nyckelord :Cryptocurrencies; Financial time-series; Multi step-ahead forecasting; Machine Learning; Feature selection; Kryptovalutor; Finansiella tidsserier; Flerstegsprognoser; Maskininlärning; variabelselektion;

   Sammanfattning : Financial time-series are not uncommon to research in an academic context. This is possibly not only due to its challenging nature with high levels of noise and non-stationary data, but because of the endless possibilities of features and problem formulations it creates. LÄS MER

5. 4. Forecasting checking account balance : Using supervised machine learning

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

   Författare :Martin Dannelind; [2022]
   Nyckelord :Time series forecasting; account balance forecasting; economic predicition; Python; GRU; LSTM; RNN; XGBoost; prophet; checking account;

   Sammanfattning : The introduction of open banking has made it possible for companies to build the next generation of applications based on transactional data. Enabling economic forecasts which private individuals can use to make responsible financial decisions. This project investigated forecasting account balances using supervised learning. LÄS MER

7. 5. Electrical Energy consumption prediction for Schools

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

   Författare :Venkata Sreenadh Movva; [2022]
   Nyckelord :Prediction; Electricity energy consumption;

   Sammanfattning : This thesis is a part of the master's in data science course at LTU. The core objective would be to build models that can do a short-term prediction of electricity energy consumption based on historical consumption data. LÄS MER