Log in

Relevant bibliographies by topics / Energy anomaly detection

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers
Reports

Academic literature on the topic 'Energy anomaly detection'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Energy anomaly detection.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Energy anomaly detection"

1

Jiang, Chao, Shengze Chen, Zhijing Zhang, and Rui Li. "Energy Meter Patch Resistance and Welding Spot Anomaly Detection Method Based on Machine Vision." Journal of Physics: Conference Series 2428, no. 1 (2023): 012045. http://dx.doi.org/10.1088/1742-6596/2428/1/012045.

Full text

Abstract:

Abstract Based on the problems, such as the difficulty of detecting and obtaining evidence of patch resistance replacement and welding spot anomaly in the current field of meter anomaly detection, a patch resistance and welding spot anomaly detection algorithm is proposed based on machine vision. The resistance anomaly detection algorithm combines the K-D tree and Ransac to complete the high-efficiency energy meter registration. It detects the suspected resistance abnormal area through the difference shadow method and then judges the resistance abnormal situation according to the resistance va

APA, Harvard, Vancouver, ISO, and other styles

2

Zhang, Zhe, Yuhao Chen, Huixue Wang, Qiming Fu, Jianping Chen, and You Lu. "Anomaly detection method for building energy consumption in multivariate time series based on graph attention mechanism." PLOS ONE 18, no. 6 (2023): e0286770. http://dx.doi.org/10.1371/journal.pone.0286770.

Full text

Abstract:

A critical issue in intelligent building control is detecting energy consumption anomalies based on intelligent device status data. The building field is plagued by energy consumption anomalies caused by a number of factors, many of which are associated with one another in apparent temporal relationships. For the detection of abnormalities, most traditional detection methods rely solely on a single variable of energy consumption data and its time series changes. Therefore, they are unable to examine the correlation between the multiple characteristic factors that affect energy consumption anom

APA, Harvard, Vancouver, ISO, and other styles

3

Hu, Min, Fan Zhang, and Huiming Wu. "Anomaly Detection and Identification Method for Shield Tunneling Based on Energy Consumption Perspective." Applied Sciences 14, no. 5 (2024): 2202. http://dx.doi.org/10.3390/app14052202.

Full text

Abstract:

Various abnormal scenarios might occur during the shield tunneling process, which have an impact on construction efficiency and safety. Existing research on shield tunneling construction anomaly detection typically designs models based on the characteristics of a specific anomaly, so the scenarios of anomalies that can be detected are limited. Therefore, the research objective of this article is to establish an accurate anomaly detection model with generalization and identification capabilities on multiple types of abnormal scenarios. Inspired by energy dissipation theory, this paper innovativ

APA, Harvard, Vancouver, ISO, and other styles

4

Jin, Hyeonseok, and Kyungbaek Kim. "TCN-USAD for Anomaly Power Detection." Korean Institute of Smart Media 13, no. 7 (2024): 9–17. http://dx.doi.org/10.30693/smj.2024.13.7.9.

Full text

Abstract:

Due to the increase in energy consumption, and eco-friendly policies, there is a need for efficient energy consumption in buildings. Anomaly power detection based on deep learning are being used. Because of the difficulty in collecting anomaly data, anomaly detection is performed using reconstruction error with a Recurrent Neural Network(RNN) based autoencoder. However, there are some limitations such as the long time required to fully learn temporal features and its sensitivity to noise in the train data. To overcome these limitations, this paper proposes the TCN-USAD, combined with Temporal

APA, Harvard, Vancouver, ISO, and other styles

5

Ko, Hoon, Kwangcheol Rim, and Isabel Praça. "Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System." Sensors 21, no. 12 (2021): 4237. http://dx.doi.org/10.3390/s21124237.

Full text

Abstract:

The biggest problem with conventional anomaly signal detection using features was that it was difficult to use it in real time and it requires processing of network signals. Furthermore, analyzing network signals in real-time required vast amounts of processing for each signal, as each protocol contained various pieces of information. This paper suggests anomaly detection by analyzing the relationship among each feature to the anomaly detection model. The model analyzes the anomaly of network signals based on anomaly feature detection. The selected feature for anomaly detection does not requir

APA, Harvard, Vancouver, ISO, and other styles

6

Savran, Efe, Esin Karpat, and Fatih Karpat. "Energy-Efficient Anomaly Detection and Chaoticity in Electric Vehicle Driving Behavior." Sensors 24, no. 17 (2024): 5628. http://dx.doi.org/10.3390/s24175628.

Full text

Abstract:

Detection of abnormal situations in mobile systems not only provides predictions about risky situations but also has the potential to increase energy efficiency. In this study, two real-world drives of a battery electric vehicle and unsupervised hybrid anomaly detection approaches were developed. The anomaly detection performances of hybrid models created with the combination of Long Short-Term Memory (LSTM)-Autoencoder, the Local Outlier Factor (LOF), and the Mahalanobis distance were evaluated with the silhouette score, Davies–Bouldin index, and Calinski–Harabasz index, and the potential ene

APA, Harvard, Vancouver, ISO, and other styles

7

Xiong, Zhangming, Daofei Zhu, Dafang Liu, Shujing He, and Luo Zhao. "Anomaly Detection of Metallurgical Energy Data Based on iForest-AE." Applied Sciences 12, no. 19 (2022): 9977. http://dx.doi.org/10.3390/app12199977.

Full text

Abstract:

With the proliferation of the Internet of Things, a large amount of data is generated constantly by industrial systems, corresponding in many cases to critical tasks. It is particularly important to detect abnormal data to ensure the accuracy of data. Aiming at the problem that the training data are contaminated with anomalies in autoencoder-based anomaly detection, which makes it difficult to distinguish abnormal data from normal data, this paper proposes a data anomaly detection method that combines an isolated forest (iForest) and autoencoder algorithm. In this method (iForest-AE), the iFor

APA, Harvard, Vancouver, ISO, and other styles

8

Do, Kien, Truyen Tran, and Svetha Venkatesh. "Energy-based anomaly detection for mixed data." Knowledge and Information Systems 57, no. 2 (2018): 413–35. http://dx.doi.org/10.1007/s10115-018-1168-z.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Zheng, Jianbo, Chao Yang, Tairui Zhang, et al. "Dynamic Spectral Graph Anomaly Detection." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 12 (2025): 13410–18. https://doi.org/10.1609/aaai.v39i12.33464.

Full text

Abstract:

Graph anomaly detection is crucial for identifying anomalous nodes within graphs and addressing applications like financial fraud detection and social spam detection. Recent spectral graph neural network methods advance graph anomaly detection by focusing on anomalies that notably affect the distribution of graph spectral energy. Such spectrum-based methods rely on two steps: graph wavelet extraction and feature fusion. However, both steps are hand-designed, capturing incomprehensive anomaly information of wavelet-specific features and resulting in their inconsistent feature fusion. To address

APA, Harvard, Vancouver, ISO, and other styles

10

Li, Jun, Yongbao Liu, Qiang Wang, Zhikai Xing, and Fan Zeng. "Rotating machinery anomaly detection using data reconstruction generative adversarial networks with vibration energy analysis." AIP Advances 12, no. 3 (2022): 035221. http://dx.doi.org/10.1063/5.0085354.

Full text

Abstract:

Rotating machines, such as engines, turbines, or gearboxes, are widely used in modern society. Their mechanical components, such as rotors, bearings, or gears, are the main parts, and any failure in them can lead to a complete shutdown of the rotating machinery. Anomaly detection in such critical systems is essential for the healthy operation of rotating machinery. As the requirement of obtaining sufficient fault data of rotating machinery is challenging to satisfy, a new anomaly detection model is proposed for rotating machinery, which can achieve anomaly detection without fault samples. The

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Energy anomaly detection"

1

Havugimana, Léonce. "IDENTIFYING UNUSUAL ENERGY CONSUMPTIONS OF HOUSEHOLDS : Using Inductive Conformal Anomaly Detection approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20220.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Bergentz, Tobias. "Identifying symptoms of fault in District Heating Substations : An investigation in how a predictive heat load software can help with fault detection." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-174442.

Full text

Abstract:

District heating delivers more than 70% of the energy used for heating and domestichot water in Swedish buildings. To stay competitive, district heating needs toreduce its losses and increase capabilities to utilise low grade heat. Finding faultysubstations is one way to allow reductions in supply temperatures in district heatingnetworks, which in turn can help reduce the losses. In this work three suggestedsymptoms of faults: abnormal quantization, drifting and anomalous values, are investigatedwith the help of hourly meter data of: heat load, volume flow, supplyand return temperatures from d

APA, Harvard, Vancouver, ISO, and other styles

3

Guss, Herman, and Linus Rustas. "Applying Machine Learning Algorithms for Anomaly Detection in Electricity Data : Improving the Energy Efficiency of Residential Buildings." Thesis, Uppsala universitet, Byggteknik och byggd miljö, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415507.

Full text

Abstract:

The purpose of this thesis is to investigate how data from a residential property owner can be utilized to enable better energy management for their building stock. Specifically, this is done through the development of two machine learning models with the objective of detecting anomalies in the existing data of electricity consumption. The dataset consists of two years of residential electricity consumption for 193 substations belonging to the residential property owner Uppsalahem. The first of the developed models uses the K-means method to cluster substations with similar consumption pattern

APA, Harvard, Vancouver, ISO, and other styles

4

Wang, Qinghua. "Traffic analysis, modeling and their applications in energy-constrained wireless sensor networks on network optimization and anomaly detection /." Doctoral thesis, Sundsvall : Tryckeriet Mittuniversitetet, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-10690.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Pol, Adrian Alan. "Machine Learning Anomaly Detection Applications to Compact Muon Solenoid Data Quality Monitoring." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS083.

Full text

Abstract:

La surveillance de la qualité des données qui proviennent des expériences de physique des hautes énergies est une tâche exigeante mais cruciale pour assurer que les analyses physiques sont basées en données de la meilleure qualité possible. Lors de l’expérience Compact Muon Solenoid opérant au Grand collisionneur de hadrons du CERN, le paradigme actuel d’évaluation de la qualité des données est basé sur l’examen détaillé d’un grand nombre de tests statistiques. Cependant, la complexité toujours croissante des détecteurs et le volume des données de surveillance appellent un changement de paradi

APA, Harvard, Vancouver, ISO, and other styles

6

Halaj, Jozef. "Detekce anomálií v IoT sítích." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417286.

Full text

Abstract:

The goal of the thesis was an analysis of IoT communication protocols, their vulnerabilities and the creation of a suitable anomaly detector. It must be possible to run the detector on routers with the OpenWRT system. To create the final solution, it was necessary to analyze the communication protocols BLE and Z-Wave with a focus on their security and vulnerabilities. Furthermore, it was necessary to analyze the possibilities of anomaly detection, design and implement the detection system. The result is a modular detection system based on the NEMEA framework. The detection system is able to de

APA, Harvard, Vancouver, ISO, and other styles

7

Dridi, Aicha. "A novel efficient time series deep learning approach using classification, prediction and reinforcement : energy and telecom use case." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS010.

Full text

Abstract:

La croissance massive des capteurs (température, humidité, accéléromètre, capteur de position) et des appareils mobiles (smartphones, tablettes, smartwatch …) fait que la quantité de données générées augmente de manière explosive. Cette immense quantité de données peut être collectée et gérée. Le travail réalisé durant cette thèse vise à proposer en un premier temps une approche qui traite un type de données spécifique qui sont les séries temporelles. Pour ce faire nous avons utilisé des méthodes de classification basées sur des réseaux de neurones convolutifs ainsi que des multi layer percept

APA, Harvard, Vancouver, ISO, and other styles

8

Boudargham, Nadine. "Competent QoS-aware and energy efficient protocols for body sensor networks." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCD007.

Full text

Abstract:

Les réseaux de capteurs corporels (RC2) sont constitués de bio-capteurs à faibles ressources énergétiques et de calcul. Ils collectent des données physiologiques du corps humain et de son environnement, et les transmettent à un coordinateur comme le PDA (Personal Digital Assistant) ou un smartphone, pour être acheminé ensuite aux experts de santé. Les réseaux de capteurs corporels collaboratifs (RC3) sont une collection de RC2 qui se déplacent dans une zone donnée et collaborent,interagissent et échangent des données entre eux pour identifier l'activité du groupe et surveiller l'état individue

APA, Harvard, Vancouver, ISO, and other styles

9

Martin-Burtart, Nicolas. "Développement d'algorithmes d'analyse spectrale en spectrométrie gamma embarquée." Phd thesis, Université de Strasbourg, 2012. http://tel.archives-ouvertes.fr/tel-00869554.

Full text

Abstract:

Jusqu'au début des années 1980, la spectrométrie gamma aéroportée a avant tout été utilisée pour des applications géophysiques et ne concernait que la mesure des concentrations dans les sols des trois radionucléides naturels (K40, U238 et Th232). Durant les quinze dernières années, un grand nombre de dispositifs de mesures a été développé, la plupart après l'accident de Tchernobyl, pour intervenir en cas d'incidents nucléaires ou de surveillance de l'environnement. Les algorithmes développés ont suivi les différentes missions de ces systèmes. La plupart sont dédiés à l'extraction des signaux à

APA, Harvard, Vancouver, ISO, and other styles

10

Cherdo, Yann. "Détection d'anomalie non supervisée sur les séries temporelle à faible coût énergétique utilisant les SNNs." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4018.

Full text

Abstract:

Dans le cadre de la maintenance prédictive du constructeur automobile Renault, cette thèse vise à fournir des solutions à faible coût énergétique pour la détection non supervisée d'anomalies sur des séries temporelles. Avec l'évolution récente de l'automobile, de plus en plus de données sont produites et doivent être traitées par des algorithmes d'apprentissage automatique. Ce traitement peut être effectué dans le cloud ou directement à bord de la voiture. Dans un tel cas, la bande passante du réseau, les coûts des services cloud, la gestion de la confidentialité des données et la perte de don

APA, Harvard, Vancouver, ISO, and other styles

More sources

Books on the topic "Energy anomaly detection"

1

Ouyang, Tinghui, Yusen He, Xun Shen, Zhenhao Tang, and Yahui Zhang, eds. Advanced Anomaly Detection Technologies and Applications in Energy Systems. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-83250-141-2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Energy anomaly detection"

1

Ding, Yu. "Anomaly Detection and Fault Diagnosis." In Data Science for Wind Energy. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429490972-15.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Haddad, Hatem, Feres Jerbi, and Issam Smaali. "Toward Unsupervised Energy Consumption Anomaly Detection." In IFIP Advances in Information and Communication Technology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63215-0_25.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Bhatia, Rashmi, Rohini Sharma, and Ajay Guleria. "Anomaly Detection Systems Using IP Flows: A Review." In Springer Proceedings in Energy. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0235-1_80.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Mazzara, Manuel, and Alberto Sillitti. "Energy-Aware Anomaly Detection in Railway Systems." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48590-9_23.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Rakesh, Rinit, Gurpinder Singh, Anil Swarnkar, Nikhil Gupta, and K. R. Niazi. "Anomaly Detection in Short-Term Load Forecasting." In Intelligent Computing Techniques for Smart Energy Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0252-9_56.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Bilendo, Francisco, Hamed Badihi, and Ningyun Lu. "Wind Turbine Anomaly Detection Based on SCADA Data." In Handbook of Smart Energy Systems. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-97940-9_35.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Bilendo, Francisco, Hamed Badihi, and Ningyun Lu. "Wind Turbine Anomaly Detection Based on SCADA Data." In Handbook of Smart Energy Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-72322-4_35-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Kaushik, Keshav, and Vinayak Naik. "A Real-Time Non-Invasive Anomaly Detection Technique for Cooling Systems." In Energy Informatics. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48649-4_8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Liu, Xiufeng, Nadeem Iftikhar, Per Sieverts Nielsen, and Alfred Heller. "Online Anomaly Energy Consumption Detection Using Lambda Architecture." In Big Data Analytics and Knowledge Discovery. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43946-4_13.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Karpontinis, Dimitrios, and Georgios Alexandridis. "Transformer-Based Anomaly Detection in Energy Consumption Data." In IFIP Advances in Information and Communication Technology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63227-3_23.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Energy anomaly detection"

1

Hong, Tae Min. "Decision tree-based anomaly detection on FPGA." In 42nd International Conference on High Energy Physics. Sissa Medialab, 2025. https://doi.org/10.22323/1.476.1058.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Ronaghi, Sina, Alessandro Ferrero, Simona Salicone, and Harsha Vardhana Jetti. "Data-Driven Anomaly Detection for Smart Energy Meters." In 2024 IEEE 14th International Workshop on Applied Measurements for Power Systems (AMPS). IEEE, 2024. http://dx.doi.org/10.1109/amps62611.2024.10706664.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Xie, Hao. "Distributed PV Power Anomaly Detection Based on LSTM-Informer." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10990846.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Sanghvi, Malay, and Santosh Kumar Bharti. "Human Crime Anomaly Detection using Deep Learning." In 2025 International Conference on Sustainable Energy Technologies and Computational Intelligence (SETCOM). IEEE, 2025. https://doi.org/10.1109/setcom64758.2025.10932630.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Vaish, Tushar, Dhinakaran M, Sachin Kumar Singh, Rohit Kumar Singh, and Shruti Singh. "Road Anomaly Detection Using Deep Learning Approach." In 2024 International Conference on Communication, Computing and Energy Efficient Technologies (I3CEET). IEEE, 2024. https://doi.org/10.1109/i3ceet61722.2024.10993859.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Kim, Daeho, Eun-Kyu Lee, and Ji-Woo Lee. "Energy-Efficient Anomaly Detection in Autonomous Vehicles Using RSNNs." In 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S). IEEE, 2025. https://doi.org/10.1109/dsn-s65789.2025.00046.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Lucas, Alexandre, Salvador Carvalhosa, and Sara Golmaryami. "Gaussian Mixture Model for Battery Operation Anomaly Detection." In 2024 International Conference on Smart Energy Systems and Technologies (SEST). IEEE, 2024. http://dx.doi.org/10.1109/sest61601.2024.10694471.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Kim, Minha, Jaehoon Shim, Juwon Lee, JongHyun Shin, and Jung-Ik Ha. "Unsupervised Anomaly Detection of Reciprocating Compressors using Auto-Encoder." In 2024 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2024. https://doi.org/10.1109/ecce55643.2024.10861618.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Sun, Guangwei, Chaofan Yin, Tian Xia, Yunpeng Lu, and Jiawei Mao. "An Improved ARIMA Based Anomaly Detection Method for Time Series Data." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10991589.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Le, Xiang, Junjie Yin, Xiaoming Zhou, et al. "SCADA Anomaly Detection Scheme Based on OCSVM-PSO." In 2024 6th International Conference on Energy Systems and Electrical Power (ICESEP). IEEE, 2024. http://dx.doi.org/10.1109/icesep62218.2024.10652121.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Energy anomaly detection"

1

Guo, Yang. User Profiling and Anomaly Detection Through GPU Energy Usage in a High-Performance Computing Environment. National Institute of Standards and Technology, 2025. https://doi.org/10.6028/nist.ir.8569.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Cazenave, Pablo. PR-328-153721-R01 Development of an Industry Test Facility and Qualification Process for ILI Technology. Pipeline Research Council International, Inc. (PRCI), 2016. http://dx.doi.org/10.55274/r0011020.

Full text

Abstract:

The project "Development of an Industry Test Facility and Qualification Processes for in-line inspection (ILI) technology Evaluation and Enhancements" aims to expand knowledge of ILI technology performance and identify gaps where new technology is needed. Additionally, this project aims to provide a continuing resource for ILI technology developers, researchers and pipeline operators to have access to test samples with a range of pipeline integrity threats and vintages and in-line technology test facilities at the Pipeline Research Council International, Inc. (PRCI) Technology Development and

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!