4.7 Article

Anomaly detection for data accountability of Mars telemetry data

Related references

Note: Only part of the references are listed.
Article Computer Science, Software Engineering

HyperNOMAD: Hyperparameter Optimization of Deep Neural Networks Using Mesh Adaptive Direct Search

Dounia Lakhmiri et al.

Summary: The performance of deep neural networks is highly sensitive to the choice of hyperparameters, tuning them manually is tedious and time-consuming, thus the need for automation. HyperNOMAD, using the MADS algorithm, achieves comparable results to the current state of the art by automating the calibration of hyperparameters.

ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE (2021)

Proceedings Paper Engineering, Aerospace

Automated Data Accountability for Missions in Mars Rover Data

Ryan Alimo et al.

Summary: This paper proposes an automated solution system to assist with Real-Time Operations and automatically identify and report on issues with data transfer, archive, and manipulation throughout the Ground Data System (GDS) process. The paper presents machine learning and deep learning based approaches to automate and optimize the detection of data loss, with the use of various supervised machine learning-based models and fast hyperparameter optimization methods to quickly tune and optimize models in near real-time.

2021 IEEE AEROSPACE CONFERENCE (AEROCONF 2021) (2021)

Article Engineering, Aerospace

Unsupervised Anomaly Detection in Flight Data Using Convolutional Variational Auto-Encoder

Milad Memarzadeh et al.

AEROSPACE (2020)

Article Mathematics, Applied

THE MESH ADAPTIVE DIRECT SEARCH ALGORITHM FOR GRANULAR AND DISCRETE VARIABLES

Charles Audet et al.

SIAM JOURNAL ON OPTIMIZATION (2019)

Article Computer Science, Information Systems

A Survey of Deep Learning-Based Object Detection

Licheng Jiao et al.

IEEE ACCESS (2019)

Article Telecommunications

A Novel Anomaly Detection Algorithm Using DBSCAN and SVM in Wireless Sensor Networks

Hossein Saeedi Emadi et al.

WIRELESS PERSONAL COMMUNICATIONS (2018)

Proceedings Paper Computer Science, Artificial Intelligence

Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding

Kyle Hundman et al.

KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING (2018)

Article Operations Research & Management Science

Delaunay-based derivative-free optimization via global surrogates, part I: linear constraints

Pooriya Beyhaghi et al.

JOURNAL OF GLOBAL OPTIMIZATION (2016)

Article Transportation Science & Technology

Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring

Lishuai Li et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2016)

Proceedings Paper Computer Science, Artificial Intelligence

Survey on Anomaly Detection using Data Mining Techniques

Shikha Agrawal et al.

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 19TH ANNUAL CONFERENCE, KES-2015 (2015)

Article Operations Research & Management Science

Mesh adaptive direct search algorithms for mixed variable optimization

Mark A. Abramson et al.

OPTIMIZATION LETTERS (2009)

Article Mathematics, Applied

Mesh adaptive direct search algorithms for constrained optimization

C Audet et al.

SIAM JOURNAL ON OPTIMIZATION (2006)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)