Relevant bibliographies by topics / Drift Detection Methods

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Drift Detection Methods'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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 'Drift Detection Methods.'

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 "Drift Detection Methods"

1

Kumar, Sanjeev, Ravendra Singh, Mohammad Zubair Khan, and Abdulfattah Noorwali. "Design of adaptive ensemble classifier for online sentiment analysis and opinion mining." PeerJ Computer Science 7 (August 5, 2021): e660. http://dx.doi.org/10.7717/peerj-cs.660.

Full text
Abstract:
DataStream mining is a challenging task for researchers because of the change in data distribution during classification, known as concept drift. Drift detection algorithms emphasize detecting the drift. The drift detection algorithm needs to be very sensitive to change in data distribution for detecting the maximum number of drifts in the data stream. But highly sensitive drift detectors lead to higher false-positive drift detections. This paper proposed a Drift Detection-based Adaptive Ensemble classifier for sentiment analysis and opinion mining, which uses these false-positive drift detect
APA, Harvard, Vancouver, ISO, and other styles
2

Sankara Prasanna Kumar, M., A. P. Siva Kumar, and K. Prasanna. "Data Mining Models of High Dimensional Data Streams, and Contemporary Concept Drift Detection Methods: a Comprehensive Review." International Journal of Engineering & Technology 7, no. 3.6 (2018): 148. http://dx.doi.org/10.14419/ijet.v7i3.6.14959.

Full text
Abstract:
Concept drift is defined as the distributed data across multiple data streams that change over the time. Concept drift is visible only when the type of collected data changes after some stable period. The emergence of concept drift in data streams leads to increase misclassification and performing degradation of data streams. In order to obtain accurate results, identification of such concept drifts must be visible. This paper focused on a review of the issues related to identifying the changes occurred in the various multivariate high dimensional data streams. The insight of the manuscript is
APA, Harvard, Vancouver, ISO, and other styles
3

Wares, Scott, John Isaacs, and Eyad Elyan. "Burst Detection-Based Selective Classifier Resetting." Journal of Information & Knowledge Management 20, no. 02 (2021): 2150027. http://dx.doi.org/10.1142/s0219649221500271.

Full text
Abstract:
Concept drift detection algorithms have historically been faithful to the aged architecture of forcefully resetting the base classifiers for each detected drift. This approach prevents underlying classifiers becoming outdated as the distribution of a data stream shifts from one concept to another. In situations where both concept drift and temporal dependence are present within a data stream, forced resetting can cause complications in classifier evaluation. Resetting the base classifier too frequently when temporal dependence is present can cause classifier performance to appear successful, w
APA, Harvard, Vancouver, ISO, and other styles
4

Zhang, Wei, and Yuan. "Novel Drift Reduction Methods in Foot-Mounted PDR System." Sensors 19, no. 18 (2019): 3962. http://dx.doi.org/10.3390/s19183962.

Full text
Abstract:
The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to imp
APA, Harvard, Vancouver, ISO, and other styles
5

Frias-Blanco, Isvani, Jose del Campo-Avila, Gonzalo Ramos-Jimenez, Rafael Morales-Bueno, Agustin Ortiz-Diaz, and Yaile Caballero-Mota. "Online and Non-Parametric Drift Detection Methods Based on Hoeffding’s Bounds." IEEE Transactions on Knowledge and Data Engineering 27, no. 3 (2015): 810–23. http://dx.doi.org/10.1109/tkde.2014.2345382.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Sirola, Miki, and Jaakko Talonen. "Combining Neural Methods and Knowledge-Based Methods in Accident Management." Advances in Artificial Neural Systems 2012 (July 30, 2012): 1–6. http://dx.doi.org/10.1155/2012/534683.

Full text
Abstract:
Accident management became a popular research issue in the early 1990s. Computerized decision support was studied from many points of view. Early fault detection and information visualization are important key issues in accident management also today. In this paper we make a brief review on this research history mostly from the last two decades including the severe accident management. The author’s studies are reflected to the state of the art. The self-organizing map method is combined with other more or less traditional methods. Neural methods used together with knowledge-based methods const
APA, Harvard, Vancouver, ISO, and other styles
7

Jaeschke, Carsten, Johannes Glöckler, Marta Padilla, Jan Mitrovics, and Boris Mizaikoff. "An eNose-based method performing drift correction for online VOC detection under dry and humid conditions." Analytical Methods 12, no. 39 (2020): 4724–33. http://dx.doi.org/10.1039/d0ay01172j.

Full text
Abstract:
In the presented study, the possibility of drift counteraction using component removal methods performing drift correction is explored by utilising our recently demonstrated innovative eNose concept, the so-called iLovEnose system.
APA, Harvard, Vancouver, ISO, and other styles
8

Togbe, Maurras Ulbricht, Yousra Chabchoub, Aliou Boly, Mariam Barry, Raja Chiky, and Maroua Bahri. "Anomalies Detection Using Isolation in Concept-Drifting Data Streams." Computers 10, no. 1 (2021): 13. http://dx.doi.org/10.3390/computers10010013.

Full text
Abstract:
Detecting anomalies in streaming data is an important issue for many application domains, such as cybersecurity, natural disasters, or bank frauds. Different approaches have been designed in order to detect anomalies: statistics-based, isolation-based, clustering-based, etc. In this paper, we present a structured survey of the existing anomaly detection methods for data streams with a deep view on Isolation Forest (iForest). We first provide an implementation of Isolation Forest Anomalies detection in Stream Data (IForestASD), a variant of iForest for data streams. This implementation is built
APA, Harvard, Vancouver, ISO, and other styles
9

Pang, Yu, Lu Deng, Jin Zhao Lin, Zhang Yong Li, Guo Quan Li, and Qian Neng Zhou. "Removal Method of Baseline Drift from ECG Signals Based on Morphology Filter." Applied Mechanics and Materials 427-429 (September 2013): 1691–95. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1691.

Full text
Abstract:
Baseline drift is the main noise of ECG signals which affects the detection accuracy so its removal plays a significantrole in the ECG signal preprocessing. Complex calculation and non-optimal signal processing cause problems of ineffective results and low real-time effects in traditional methods. This paper designs a new filter to remove baseline drift based on the theory of mathematical morphology, which is created by the geometric parameters of the ECG signal. Experiments show that the method can effectively remove the noise of baseline drift by simple computation and is helpful to improve
APA, Harvard, Vancouver, ISO, and other styles
10

Xing, Jinlei, and Longhua Mu. "A New Passive Islanding Detection Solution Based on Accumulated Phase Angle Drift." Applied Sciences 8, no. 8 (2018): 1340. http://dx.doi.org/10.3390/app8081340.

Full text
Abstract:
The existing passive methods for islanding detection are mainly based on the detection of voltage and frequency deviation after islanding, using protections such as voltage vector shift (VVS) and rate of change of frequency (ROCOF). Although there are reported issues with these passive methods such as inherent non-detection zones and nuisance trips, utilities prefer the passive methods due to the low cost and simplicity of deployment. In this paper, one composite passive islanding detection method is presented. It tracks the voltage phase angle, the system frequency, and ROCOF every power cycl
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Drift Detection Methods"

1

Pesaranghader, Ali. "A Reservoir of Adaptive Algorithms for Online Learning from Evolving Data Streams." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38190.

Full text
Abstract:
Continuous change and development are essential aspects of evolving environments and applications, including, but not limited to, smart cities, military, medicine, nuclear reactors, self-driving cars, aviation, and aerospace. That is, the fundamental characteristics of such environments may evolve, and so cause dangerous consequences, e.g., putting people lives at stake, if no reaction is adopted. Therefore, learning systems need to apply intelligent algorithms to monitor evolvement in their environments and update themselves effectively. Further, we may experience fluctuations regarding the p
APA, Harvard, Vancouver, ISO, and other styles
2

SANTOS, Silas Garrido Teixeira de Carvalho. "Avaliação criteriosa dos algoritmos de detecção de concept drifts." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/17310.

Full text
Abstract:
Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-07-11T12:33:28Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) silas-dissertacao-versao-final-2016.pdf: 1708159 bytes, checksum: 6c0efc5f2f0b27c79306418c9de516f1 (MD5)<br>Made available in DSpace on 2016-07-11T12:33:28Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) silas-dissertacao-versao-final-2016.pdf: 1708159 bytes, checksum: 6c0efc5f2f0b27c79306418c9de516f1 (MD5) Previous issue date: 2015-02-27<br>FACEPE<br>A
APA, Harvard, Vancouver, ISO, and other styles
3

Kadlčík, Libor. "Implementace rekonstrukčních metod pro čtení čárového kódu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220266.

Full text
Abstract:
Bar code stores information in the form of series of bars and gaps with various widths, and therefore can be considered as an example of bilevel (square) signal. Magnetic bar codes are created by applying slightly ferromagnetic material to a substrate. Sensing is done by reading oscillator, whose frequency is modulated by presence of the mentioned ferromagnetic material. Signal from the oscillator is then subjected to frequency demodulation. Due to temperature drift of the reading oscillator, the demodulated signal is accompanied by DC drift. Method for removal of the drift is introduced. Also
APA, Harvard, Vancouver, ISO, and other styles
4

Smithbauer, David Paul. "Analysis and Application of Automated Methods for Detecting Pulsars in the Green Bank Telescope 350MHz Drift-Scan Survey." Thesis, West Virginia University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1523624.

Full text
Abstract:
<p> A significant portion of the process of detecting pulsars from radio sky surveys remains a largely manual task. The visual inspection of data in order to detect and validate potential pulsar candidates is by far the most time consuming portion of the overall process. Coupled with the fact that well over a Petabyte of pulsar survey data has been archived, the task of identifying these valuable phenomena is tedious and time consuming.</p><p> Using data from a survey performed with the National Radio Astronomy Observatory&rsquo;s (NRAO&rsquo;s) Green Bank Telescope (GBT) in 2007, this thesi
APA, Harvard, Vancouver, ISO, and other styles
5

Chiu, Yao-Ching, and 邱耀慶. "A Parallel Detection and Prediction Method for Concept Drift in Dynamic Data Driven Application System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/e864zc.

Full text
Abstract:
碩士<br>國立交通大學<br>資訊管理研究所<br>103<br>The traditional data analysis and prediction method assumes that data distribution is stable. Therefore, it can predict unlabeled data precisely by analyzing the historical data. However, in today’s big-data environment, which is changing frequently, the traditional approach can no longer be effective; it cannot handle concept drift in a Dynamic Data Driven Application System (DDDAS). This thesis proposes a parallel detection and prediction method for concept drift in DDDAS. The proposed method can detect changing data and then feedback to the prediction model
APA, Harvard, Vancouver, ISO, and other styles
6

Obenauff, Alexander. "A progressive learning method for classification of manufacturing errors based on machine data." Master's thesis, 2019. http://hdl.handle.net/10362/76579.

Full text
Abstract:
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>Manufacturing companies face significant market pressure in today’s globalised world. Fierce global competition and product individualisation mean that production systems require continuous optimisation. This means that automation, flexibility and efficiency have all become vital elements for manufacturers. In this paper, a method based on incremental classification used for manufacturing errors is presented. The analysis and classification focus on data of binary form c
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Drift Detection Methods"

1

Carpenter, Philip J. Application of surface geophysics to detection and mapping of mine subsidence fractures in drift and bedrock. Illinois State Geological Survey, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Drift Detection Methods"

1

Patil, Malini M. "Handling Concept Drift in Data Streams by Using Drift Detection Methods." In Data Management, Analytics and Innovation. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1274-8_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Pugliese, Victor Ulisses, Renato Duarte Costa, and Celso Massaki Hirata. "Comparative Evaluation of the Supervised Machine Learning Classification Methods and the Concept Drift Detection Methods in the Financial Business Problems." In Enterprise Information Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75418-1_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sobhani, Parinaz, and Hamid Beigy. "New Drift Detection Method for Data Streams." In Adaptive and Intelligent Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23857-4_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Buryakov, Igor A. "Detection of Explosive Vapours in Ambient Air by Ion Nonlinear Drift Spectrometry Method." In Detection of Explosives and Landmines. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0397-1_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pesaranghader, Ali, and Herna L. Viktor. "Fast Hoeffding Drift Detection Method for Evolving Data Streams." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Angelopoulos, Angelos, Anastasios E. Giannopoulos, Nikolaos C. Kapsalis, et al. "Impact of Classifiers to Drift Detection Method: A Comparison." In Proceedings of the International Neural Networks Society. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80568-5_33.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Xia, Yuan, and Yunlong Zhao. "A Drift Detection Method Based on Diversity Measure and McDiarmid’s Inequality in Data Streams." In Green, Pervasive, and Cloud Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64243-3_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Reddy Madhavi, K., A. Vinaya Babu, G. Sunitha, and J. Avanija. "Detection of Concept-Drift for Clustering Time-Changing Categorical Data: An Optimal Method for Large Datasets." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1097-7_72.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Himaja, D., T. Maruthi Padmaja, and P. Radha Krishna. "A Survey of Class Imbalance Problem on Evolving Data Stream." In Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7371-6.ch002.

Full text
Abstract:
Learning from data streams with both online class imbalance and concept drift (OCI-CD) is receiving much attention in today's world. Due to this problem, the performance is affected for the current models that learn from both stationary as well as non-stationary environments. In the case of non-stationary environments, due to the imbalance, it is hard to spot the concept drift using conventional drift detection methods that aim at tracking the change detection based on the learner's performance. There is limited work on the combined problem from imbalanced evolving streams both from stationary and non-stationary environments. Here the data may be evolved with complete labels or with only limited labels. This chapter's main emphasis is to provide different methods for the purpose of resolving the issue of class imbalance in emerging streams, which involves changing and unchanging environments with supervised and availability of limited labels.
APA, Harvard, Vancouver, ISO, and other styles
10

"Biology, Management, and Conservation of Lampreys in North America." In Biology, Management, and Conservation of Lampreys in North America, edited by Abel F. Brumo, Leo Grandmontagne, Steven N. Namitz, and Douglas F. Markle. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874134.ch12.

Full text
Abstract:
&lt;em&gt;Abstract&lt;/em&gt;.—We evaluated two methods for assessing Pacific lamprey &lt;em&gt;Lampetra tridentata&lt;/em&gt; spawning populations (visual counts of spawning adults and redds) and one method for assessing larval production (emergent ammocoete counts from drift nets) in the South Fork Coquille River, Oregon in 2004 and 2005. All three methods generally provided similar portrayals of timing, duration, and magnitude of spawning, including greater abundance in 2004 and seasonally bimodal spawning in 2005. We found a linear relationship between adult and redd counts but a high redd to adult ratio that varied seasonally in both years. The high redd to adult ratio can be attributed to short residence time in spawning areas and temperature or habitat-dependent differences in detection of adults, both of which can undermine adult count data. Redds had relatively longer persistence and larger numbers compared to adults and therefore may be a more practical survey method, but variable redd shape, size, and age, as well as superimposition, presented significant counting errors. Both adult and redd counts had no clear-cut way to quantify errors. Sampling emergent ammocoetes in the drift allowed detection of low density early and late season spawning and would be the preferred survey method when surveys of spawning adults and redds are impractical due to river size, visibility, or access. Even when spawning surveys are practical, emergent ammocoete counts may be better for detecting and monitoring small populations. Disadvantages of ammocoete sampling include nighttime work hours, extra laboratory time, and difficulties with species identification. The general absence of a stock–recruit relationship in lampreys means adult and redd counts are poor predictors of ammocoete production and emergent ammocoete abundance is a poor predictor of spawning abundance. The relationship breaks down because of variability in early survival, which is best detected using data from both spawning surveys and larval drift samples.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Drift Detection Methods"

1

Yu, Shujian, Xiaoyang Wang, and José C. Príncipe. "Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/421.

Full text
Abstract:
One important assumption underlying common classification models is the stationarity of the data. However, in real-world streaming applications, the data concept indicated by the joint distribution of feature and label is not stationary but drifting over time. Concept drift detection aims to detect such drifts and adapt the model so as to mitigate any deterioration in the model's predictive performance. Unfortunately, most existing concept drift detection methods rely on a strong and over-optimistic condition that the true labels are available immediately for all already classified instances.
APA, Harvard, Vancouver, ISO, and other styles
2

Sakamoto, Yusuke, Ken-Ichi Fukui, Joao Gama, Daniela Nicklas, Koichi Moriyama, and Masayuki Numao. "Concept Drift Detection with Clustering via Statistical Change Detection Methods." In 2015 Seventh International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2015. http://dx.doi.org/10.1109/kse.2015.19.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Pesaranghader, Ali, Herna L. Viktor, and Eric Paquet. "McDiarmid Drift Detection Methods for Evolving Data Streams." In 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 2018. http://dx.doi.org/10.1109/ijcnn.2018.8489260.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Liu, Anjin, Yiliao Song, Guangquan Zhang, and Jie Lu. "Regional Concept Drift Detection and Density Synchronized Drift Adaptation." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/317.

Full text
Abstract:
In data stream mining, the emergence of new patterns or a pattern ceasing to exist is called concept drift. Concept drift makes the learning process complicated because of the inconsistency between existing data and upcoming data. Since concept drift was first proposed, numerous articles have been published to address this issue in terms of distribution analysis. However, most distribution-based drift detection methods assume that a drift happens at an exact time point, and the data arrived before that time point is considered not important. Thus, if a drift only occurs in a small region of th
APA, Harvard, Vancouver, ISO, and other styles
5

Santos, Silas G. T. C., Roberto S. M. Barros, and Paulo M. Goncalves. "Optimizing the Parameters of Drift Detection Methods Using a Genetic Algorithm." In 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2015. http://dx.doi.org/10.1109/ictai.2015.153.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Hong, Yan, and Wenchong Huang. "Investigation of Frequency drift methods of Islanding Detection with multiple PV inverters." In 2014 IEEE International Power Electronics and Application Conference and Exposition (PEAC). IEEE, 2014. http://dx.doi.org/10.1109/peac.2014.7037894.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Shahabuddin, Shahriar, Zaheer Khan, and Markku Juntti. "Concept Drift Detection Methods for Deep Learning Cognitive Radios: A Hardware Perspective." In 2021 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2021. http://dx.doi.org/10.1109/iscas51556.2021.9401358.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Carpenter, Philip J. "Detection and Mapping of Mine Subsidence Fractures in Glacial Drift Using Surface Electrical Methods." In Symposium on the Application of Geophysics to Engineering and Environmental Problems 1996. Environment and Engineering Geophysical Society, 1996. http://dx.doi.org/10.4133/1.2922242.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Yu, Shujian, Ammar Shaker, Francesco Alesiani, and Jose Principe. "Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/385.

Full text
Abstract:
We propose a simple yet powerful test statistic to quantify the discrepancy between two conditional distributions. The new statistic avoids the explicit estimation of the underlying distributions in high-dimensional space and it operates on the cone of symmetric positive semidefinite (SPS) matrix using the Bregman matrix divergence. Moreover, it inherits the merits of the correntropy function to explicitly incorporate high-order statistics in the data. We present the properties of our new statistic and illustrate its connections to prior art. We finally show the applications of our new statistic
APA, Harvard, Vancouver, ISO, and other styles
10

Gadelha de Freitas, Ricardo Dantas, Andre´ Laurindo Maitelli, and Andre´s Ortiz Salazar. "A Wavelet Approach to Pipeline Leak Detection by Pressure Analysis." In ASME 2004 23rd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2004. http://dx.doi.org/10.1115/omae2004-51219.

Full text
Abstract:
One of the most challenging tasks in an oil field is implementation of a software-based leak detection system on a multi-phase flow pipeline. When a leak occurs in a multi-phase flow pipeline, the flow cannot be measured with accuracy. So, none of the various pipeline leak detection methodologies can offer good performance on a multi-phase flow pipeline. This paper will discuss implementation of a leak detection system in a particular oil field using state-of-the-art signal processing techniques to apply to the data collected in a oil pipeline. This leak detection system is still in developmen
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Drift Detection Methods' for particular source types:
Journal articles
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!

To the bibliography