Sökning: "support vector machine regression"
Visar resultat 1 - 5 av 188 uppsatser innehållade orden support vector machine regression.
1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER
2. Android Malware Detection Using Machine Learning
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. The Android smartphone, with its wide range of uses and excellent performance, has attracted numerous users. Still, this domination of the Android platform also has motivated the attackers to develop malware. The traditional methodology which detects the malware based on the signature is unfit to discover unknown applications. LÄS MER
3. Machine Learning Prediction of Enzymes’ Optimal Catalytic Temperatures
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Enzymes that have been genetically engineered to withstand high temperatures are used by industry to make products with less waste and pollution. Different features of protein structure affect the optimal catalytic temperature ("topt") at which enzymes catalyze reactions most efficiently. LÄS MER
4. Mathematical modelling simulation data and artificial intelligence for the study of tumour-macrophage interaction
Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : The study explores the integration of mathematical modelling and machine learning to understand tumour-macrophage interactions in the tumour microenvironment. It details mathematical models based on biochemistry and physics for predicting tumour dynamics, highlighting the role of macrophages. LÄS MER
5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models
Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologiSammanfattning : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). LÄS MER