Sökning: "computational"

Visar resultat 21 - 25 av 2462 uppsatser innehållade ordet computational.

1. 21. Groundwater Modelling in southeast Cambodia - Facing irrigation and groundwater level changes during a pandemic

   Master-uppsats, Lunds universitet/Avdelningen för Teknisk vattenresurslära

   Författare :Svea Bertolatus; [2024]
   Nyckelord :Cambodia; GMS Modflow; Groundwater modelling; irrigation; Mekong; Prey Veng; Svay Rieng; Technology and Engineering; Earth and Environmental Sciences;

   Sammanfattning : In the Mekong region, sustainable water resource management is a significant challenge for all countries involved. In Cambodia, where rice production is crucial for household food security and export, groundwater is increasingly used for irrigation during the dry season, leading to higher rice yields. LÄS MER

3. 22. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

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

   Författare :Khalid El Yaacoub; [2024]
   Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER

4. 23. Resource Usage Prediction for Parameter Sweeps with Biochemical System Simulations

   Master-uppsats, Uppsala universitet/Tillämpad beräkningsvetenskap

   Författare :Minjia Zhou; [2024]
   Nyckelord :;

   Sammanfattning : Exploring the behavior of biochemical systems when subjected to certain internal and external changes is fascinating, and these variations can be investigated through computational simulations. However, the computational cost of simulations is often quite high, necessitating an understanding of the computational requirements and resource utilization of these simulations. LÄS MER

5. 24. Leveraging Large Language Models for Firm-Intelligence: A RAG Framework Approach

   Magister-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Niclas Wölner-Hanssen; [2024]
   Nyckelord :Artificial Intelligence; Large Language Models; Retrieval Augmented Generation; Retrieval Augmented Generation Assessment; Contrastive Learning; Mathematics and Statistics;

   Sammanfattning : In the wake of OpenAI's release of ChatGPT in November 2022, powered by the 175 billion parameter neural network GPT-3, the potential applications of Large Language Models (LLMs) in various sectors have become evident. One such application lies in hedge funds and trading desks where knowledge sharing is paramount. LÄS MER

7. 25. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Jonna Matthiesen; [2023-10-24]
   Nyckelord :Compression; Deep Learning; DNN; Hyperparameters; Optimization; Pruning; Hyperparameter Optimisation; Hyperparameter Tuning;

   Sammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER