Sökning: "noggrannhet"
Visar resultat 31 - 35 av 1414 uppsatser innehållade ordet noggrannhet.
31. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning
Master-uppsats, KTH/Matematisk statistikSammanfattning : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. LÄS MER
32. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
Master-uppsats, KTH/FysikSammanfattning : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). LÄS MER
33. A Predictive Analysis of Customer Churn
Kandidat-uppsats, KTH/Matematisk statistikSammanfattning : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. LÄS MER
34. Ekonomisk betydelse av biometrias kvalitetssäkring för skogsmaskinlag
Uppsats för yrkesexamina på avancerad nivå, SLU/Department of Forest Biomaterials and Technology (from 131204)Sammanfattning : Virkesvärdet påverkas till stor del av skogsmaskinlagens förmåga att aptera och sortera virke enligt apteringsinstruktioner. Syftet med studien var att kvantifiera skillnader i virkesvärde mellan skogsmaskinlag som hade kvalitetssäkring från Biometria (A) och maskinlag utan deras kvalitetssäkring (B). LÄS MER
35. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. LÄS MER