Sökning: "Dynamic clustering algorithm"

Visar resultat 1 - 5 av 16 uppsatser innehållade orden Dynamic clustering algorithm.

1. 1. Design of high performance buildings : Vulnerability of buildings to climate change from an energy perspective

   Master-uppsats, KTH/Hållbara byggnader

   Författare :Robin Gobert; [2022]
   Nyckelord :Climate Change; High Performance Buildings; Dynamic Thermal Simulations; Thermal Regulation; Environmental Regulation; Cooling Needs; Heating Needs; Representative Data; Big Data; Clustering;

   Sammanfattning : The challenge of climate change is twofold: to mitigate (prevent) the causes of climate change and to prepare (adapt) to the inevitable effects and consequences. Building and construction are key sectors for decarbonisation (mitigation). LÄS MER

3. 2. Access Point Selection and Clustering Methods with Minimal Switching for Green Cell-Free Massive MIMO Networks

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

   Författare :Qinglong He; [2022]
   Nyckelord :Cell-free massive MIMO; multi-objective optimization; deep reinforcement learning; AP switch ON OFF; energy efficiency; Cellfri massiv MIMO; multiobjektiv optimering; djup förstärkningsinlärning; AP switch ON OFF; energieffektivitet;

   Sammanfattning : As a novel beyond fifth-generation (5G) concept, cell-free massive MIMO (multiple-input multiple-output) recently has become a promising physical-layer technology where an enormous number of distributed access points (APs), coordinated by a central processing unit (CPU), cooperate to coherently serve a large number of user equipments (UEs) in the same time/frequency resource. However, denser AP deployment in cell-free networks as well as an exponentially growing number of mobile UEs lead to higher power consumption. LÄS MER

4. 3. Understanding Traffic Cruising Causation : Via Parking Data Enhancement

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Mirza Jasarevic; [2021]
   Nyckelord :Machine Learning; Unsupervised Learning; Time Series; Parking; Dynamic Time Warping;

   Sammanfattning : 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. LÄS MER

5. 4. Hierarchical Clustering based Dynamic Subarrays for Hybrid Beamforming Massive MU-MIMO

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

   Författare :Francisco Goncalves Contente; [2020]
   Nyckelord :;

   Sammanfattning : Hybrid Beamforming in multiple input multiple output systems has surged in the past few years as the prime precoding architecture for massive MIMO systems since it addresses the systems performance and complexity/power consumption tradeoff. Most of the literature addresses HBF MIMO with a fixed antenna subarray, however it is possible to further increase the spectral efficiency of the system by dynamically configuring the HBF MIMO subarray according the channel state information of the users. LÄS MER

7. 5. Time-Series Feature Extraction in Embedded Sensor Processing System

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

   Författare :Wenyao Zhu; [2020]
   Nyckelord :;

   Sammanfattning : Embedded sensor-based systems mounted with tens or hundreds of sensors can collect enormous time-series data, while the data analysis on those time-series is commonly conducted on the remote server-side. With the development of microprocessors, there have been increasing demands to move the analysis process to the local embedded systems. LÄS MER