Essays about: "K-means algorithm"
Showing result 21 - 25 of 107 essays containing the words K-means algorithm.
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21. Automatic Physical Cell Identity Planning using Machine Learning
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: The growing needs of communications have a higher demand for data and stream-less services for the users. A unique physical cell identity (PCI) is assigned to transfer data between the cellular base station (gNB) and user equipment (UE). It is used to transmit the data to multiple users simultaneously. READ MORE
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22. Analysis of Drinking Water Delivery Patterns in the Northern Part of Stockholm – Effects of Population Growth, Holidays and Weather Conditions
University essay fromAbstract : Global warming is widely reported to be a cause of water scarcity and increased water con-sumption. As a consequence, it becomes harder for water suppliers to be prepared for increaseddemands. READ MORE
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23. Classification of healthy and Parkinson’s disease state mice using whisker movements
University essay from KTH/DatavetenskapAbstract : Modelling diseases in mice provides a useful way of studying the disease. The motor symptoms of Parkinson’s disease (PD) can be studied by observing the whisker movements of mice with PD condition. Mice use their whiskers to gather information about their environment and guide their locomotion. READ MORE
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24. Understanding Traffic Cruising Causation : Via Parking Data Enhancement
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background. Some computer scientists have recently pointed out that it may be more effective for the computer science community to focus more on data preparation for performance improvements, rather than exclusively comparing modeling techniques. READ MORE
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25. Semi-Supervised Learning for Predicting Biochemical Properties
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The predictive performance of supervised learning methods relies on large amounts of labeled data. Data sets used in Quantitative Structure Activity Relationship modeling often contain a limited amount of labeled data, while unlabeled data is abundant. READ MORE