On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,236 papers · 148 categories

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7 results for “VoLTE”

Optimal Design of Volt/VAR Control Rules of Inverters using Deep Learningmath.OC

Optimal Volt/VAR control rules designed using deep learning.

problem Designing optimal Volt/VAR control rules for DERs to regulate voltage fluctuations.

method Formulated as a deep learning problem, where a DNN emulates Volt/VAR dynamics and optimizes rule parameters.

result DNN-based optimization outperforms MINLP in efficiency and accuracy.

Volt/VAR control DERs Deep learning Optimization Stability

2022-11-17abs ↗pdf ↗

Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cellscs.NI

RL-based power control improves VoLTE performance in indoor small cells.

problem Improving VoLTE performance in indoor small cells with RL.

method RL-based closed-loop power control algorithm.

result Significant improvement in voice retainability and MOS.

RL VoLTE Power Control Small Cells Indoor

2017-07-10abs ↗pdf ↗

Scalable Optimal Design of Incremental Volt/VAR Control using Deep Neural Networksmath.OC

Optimal Volt/VAR control rules are designed using deep neural networks.

problem Designing optimal Volt/VAR control rules for distributed energy resources (DERs).

method Formulate optimal rule design as a bilevel program, then reformulate it as training a deep neural network (DNN). Use proximal gradient descent (PGD) iterations to emulate Volt/VAR dynamics.

result The proposed solution can be adapted to single/multi-phase feeders and achieves enhanced steady-state voltage profiles.

Volt/VAR control distributed energy resources deep neural networks bilevel programming proximal gradient descent

2023-01-04abs ↗pdf ↗

A Framework for Automated Cellular Network Tuning with Reinforcement Learningcs.NI

Paper proposes RL algorithms for optimizing cellular network performance.

problem Improving cellular network performance against wireless impairments.

method Formulated as a reinforcement learning problem and developed two algorithms: PC and SON.

result RL algorithms outperform industry standards in simulated environments.

reinforcement learning cellular networks reliable communication wireless impairments power control

2018-08-13abs ↗pdf ↗

VolTS: A Volatility-based Trading System to forecast Stock Markets Trend using Statistics and Machine Learningq-fin.TR

VolTS uses stats & ML to forecast stock market trends based on volatility.

problem Capturing profitable trading opportunities from market dynamics.

method Combines statistical analysis with machine learning; k-means++ clustering, Granger causality test.

result Effective at identifying profitable trading opportunities through volatility clusters and Granger causality.

volatility trading strategy machine learning statistical analysis Granger causality

2023-07-25abs ↗pdf ↗

Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processescs.LG

New models improve stock and wind speed forecasting.

problem Lack of posterior distribution in stochastic volatility models.

method Re-cast stochastic volatility models as hierarchical Gaussian processes with specialized covariance functions.

result Volt and Magpie models significantly outperform baselines in forecasting.

Gaussian processes stochastic volatility forecasting multitask stock

2022-07-13abs ↗pdf ↗

Regression-based Inverter Control for Decentralized Optimal Power Flow and Voltage Regulationeess.SY

The paper proposes a data-driven method for optimal power flow and voltage regulation in distribution grids.

problem Optimal power flow and voltage regulation in decentralized power grids.

method The approach uses a network model, historic data, and regression to find functions approximating optimal reactive power injections for inverters.

result The method achieves near-optimal results in voltage- and capacity-constrained loss minimization and voltage flattening.

optimal power flow voltage regulation regression distributed generation inverters

2019-02-20abs ↗pdf ↗