Search Results - (("Autoencoder applications") OR ("Autoencoder publications"))

Anomaly Detection of Time Series Caused by International Revenue Share Fraud : Additive Model and Autoencoder Applications

Authors: Wang, Lingxiao

Index Terms: Fraud detection, Anomaly detection, Machine learning, Bedrägeriupptäckt, Anomalidetektering, Maskininlärning, Computer Sciences, Datavetenskap (datalogi), Computer Engineering, Datorteknik, Computer and Information Sciences, Data- och informationsvetenskap, Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-325848
TRITA-EECS-EX ; 2023:100

A new investment method with AutoEncoder: Applications to crypto currencies

Authors: Masafumi Nakano Akihiko Takahashi

Source: Expert Systems with Applications. 162:113730

Subject Terms: 0502 economics and business, 05 social sciences, 8. Economic growth, 0202 electrical engineering, electronic engineering, information engineering, 1. No poverty, 02 engineering and technology

Access URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3473684
https://www.sciencedirect.com/science/article/pii/S0957417420305546
https://doi.org/10.1016/j.eswa.2020.113730
https://dblp.uni-trier.de/db/journals/eswa/eswa162.html#NakanoT20

Survey on machine learning applied to CNC milling processes.

Authors: Pasandidehpoor, Mohammad Nogueira, Ana Rita Mendes-Moreira, João et al.

Source: Advances in Manufacturing; Dec2025, Vol. 13 Issue 4, p847-885, 39p

INRA: deep autoencoder-based node influence ranking method in complex networks.

Authors: Patel, Asmita Singh, Buddha

Source: International Journal of Data Science & Analytics; Nov2025, Vol. 20 Issue 6, p6019-6039, 21p

Anomaly detection in urban lighting systems using autoencoder and transformer algorithms.

Authors: Śmiałkowski, Tomasz Czyżewski, Andrzej

Source: Scientific Reports; 10/15/2025, Vol. 15 Issue 1, p1-13, 13p

Subject Terms: AUTOENCODERS, MACHINE learning, ENERGY consumption, OUTLIER detection, MUNICIPAL lighting, ARTIFICIAL intelligence, TRANSFORMER models, REAL-time computing

Optimizing 3D printing through enhancements in inverse autoencoder models and guided decoders for predicting mechanical properties.

Authors: Nguyen, Phuong Dong Hoang, Tien-Dat Nguyen, Thanh Q.

Source: Progress in Additive Manufacturing; Oct2025, Vol. 10 Issue 10, p8729-8750, 22p

A New Investment Method with Autoencoder: Applications to Cryptocurrencies

Authors: Nakano, Masafumi Takahashi, Akihiko

Source: SSRN Electronic Journal ; ISSN 1556-5068

Availability: http://dx.doi.org/10.2139/ssrn.3473684

NeuroHybridNet: A Hybrid EEG Classification Model with Autoencoder-Enhanced Fractal-Wavelet Features.

Authors: TEKİN, Hazret

Source: Dicle University Journal of Engineering / Dicle Üniversitesi Mühendislik Dergisi; eyl2025, Vol. 16 Issue 3, p643-661, 19p

Deep Neural Network with Anomaly Detection for Single-Cycle Battery Lifetime Prediction.

Authors: Lee, Junghwan Wang, Longda Jung, Hoseok et al.

Source: Batteries; Aug2025, Vol. 11 Issue 8, p288, 22p

Subject Terms: AUTOENCODERS, DEEP learning, ARTIFICIAL neural networks, DATA integrity, REMAINING useful life, OUTLIER detection, ELECTRIC vehicles

Industry 5.0 and Digital Twins in the Chemical Industry: An Approach to the Golden Batch Concept.

Authors: Redchuk, Andrés Walas Mateo, Federico

Source: ChemEngineering; Aug2025, Vol. 9 Issue 4, p78, 10p

Subject Terms: DIGITAL twin, SUSTAINABILITY, BATCH processing, INDUSTRY 4.0, BIOSYNTHESIS, PROCESS optimization, DIGITAL technology, CHEMICAL industry

Comparative Analysis of Recurrent vs. Temporal Convolutional Autoencoders for Detecting Container Impacts During Quay Crane Handling.

Authors: Jakovlev, Sergej Eglynas, Tomas Pocevicius, Edvinas et al.

Source: Journal of Marine Science & Engineering; Jul2025, Vol. 13 Issue 7, p1231, 23p

Subject Terms: AUTOENCODERS, EDGE computing, CONVOLUTIONAL neural networks, CRANES (Machinery), OUTLIER detection, SHIPPING containers, REAL-time computing

Financial Modelling System Using Deep Neural Networks (DNNs) for Financial Risk Assessments.

Authors: Naveed, Hafiz Muhammad Yanchun, Pan Memon, Bilal Ahmed et al.

Source: International Social Science Journal; Mar2025, Vol. 75 Issue 255, p137-154, 18p

Subject Terms: ARTIFICIAL neural networks, INVESTORS, FOREIGN exchange, INVESTMENT policy, FINANCIAL risk

Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network.

Authors: Zhou, Yang Xie, Chi Wang, Gang-Jin et al.

Source: Financial Innovation; 2/24/2025, Vol. 11 Issue 1, p1-52, 52p

Subject Terms: GRAPH neural networks, DEEP learning, FINANCIAL markets, MARKETING management, ECONOMETRICS

Migrating birds optimization-based feature selection for text classification.

Authors: Kaya, Cem Kilimci, Zeynep Hilal Uysal, Mitat et al.

Source: PeerJ Computer Science; Aug2024, p1-31, 31p

Subject Terms: FEATURE selection, PARTICLE swarm optimization, NAIVE Bayes classification, CLASSIFICATION, ALGORITHMS

How to Construct a Lower Risk FOF Based on Correlation Network? The Method of Principal Component Risk Parity Asset Allocation.

Authors: Bai, Wei Zhang, Junting Liu, Haifei et al.

Source: Journal of Systems Science & Complexity; Jun2024, Vol. 37 Issue 3, p1052-1079, 28p

Autoencoders and their applications in machine learning: a survey.

Authors: Berahmand, Kamal Daneshfar, Fatemeh Salehi, Elaheh Sadat et al.

Source: Artificial Intelligence Review; Feb2024, Vol. 57 Issue 2, p1-52, 52p

Detecting Anomalies in Simulated Nuclear Data Using Autoencoders.

Authors: Mena, Pedro Borrelli, R. A. Kerby, Leslie

Source: Nuclear Technology; Jan2024, Vol. 210 Issue 1, p112-125, 14p

Data-Driven Machine Learning Methods for Nontechnical Losses of Electrical Energy Detection: A State-of-the-Art Review.

Authors: Pazderin, Andrey Kamalov, Firuz Gubin, Pavel Y. et al.

Source: Energies (19961073); Nov2023, Vol. 16 Issue 21, p7460, 33p

Subject Terms: ELECTRICAL energy, ENERGY dissipation, MACHINE learning, ANOMALY detection (Computer security), ARTIFICIAL intelligence

A Review of Research on Spectrum Sensing Based on Deep Learning.

Authors: Zhang, Yixuan Luo, Zhongqiang

Source: Electronics (2079-9292); Nov2023, Vol. 12 Issue 21, p4514, 42p

Subject Terms: DEEP learning, MACHINE learning, TELECOMMUNICATION, COGNITIVE radio, ARTIFICIAL intelligence

Machine Learning and Pattern Recognition Methods in Chemistry From Multivariate and Data Driven Modeling

Authors: Jahan B. Ghasemi

Resource Type: eBook.

Subjects: Machine learning, Chemistry--Data processing, Multivariate analysis, Pattern recognition systems

Categories: SCIENCE / Chemistry / Physical & Theoretical