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Relevant bibliographies by topics / Intelligent data analysis

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Academic literature on the topic 'Intelligent data analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 May 2022

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Journal articles on the topic "Intelligent data analysis"

1

Ziegel, Eric R., Michael Berthold, and David J. Hand. "Intelligent Data Analysis." Technometrics 42, no. 4 (2000): 442. http://dx.doi.org/10.2307/1270975.

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Berthold, Michael, and David I. Hand. "Intelligent Data Analysis." Technometrics 42, no. 4 (2000): 442. http://dx.doi.org/10.1080/00401706.2000.10485739.

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Patil, Pradnya, David C. Brown, and Nabil I. Hachem. "Intelligent data analysis systems." Journal of Intelligent Manufacturing 4, no. 2 (1993): 121–37. http://dx.doi.org/10.1007/bf00123906.

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Ventura, S., C. Romero, and A. Abraham. "Foreword: Intelligent data analysis." Journal of Computer and System Sciences 80, no. 1 (2014): 1–2. http://dx.doi.org/10.1016/j.jcss.2013.03.003.

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Zabezhailo, M. I., and E. V. Sinyakova. "On the intelligence of the intelligent data analysis." Automatic Documentation and Mathematical Linguistics 48, no. 2 (2014): 43–50. http://dx.doi.org/10.3103/s0005105514020046.

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Famili, A., Wei-Min Shen, Richard Weber, and Evangelos Simoudis. "Data Preprocessing and Intelligent Data Analysis." Intelligent Data Analysis 1, no. 1 (1997): 3–23. http://dx.doi.org/10.3233/ida-1997-1102.

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FAMILI, A., W. SHEN, R. WEBER, and E. SIMOUDIS. "Data preprocessing and intelligent data analysis." Intelligent Data Analysis 1, no. 1-4 (1997): 3–23. http://dx.doi.org/10.1016/s1088-467x(98)00007-9.

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Chun, Yang-ha, and Moon-ki Cho. "An Empirical Study of Intelligent Security Analysis Methods Utilizing Big Data." Webology 19, no. 1 (2022): 4672–81. http://dx.doi.org/10.14704/web/v19i1/web19311.

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The frequency of cyber-terrorist attacks targeting broadcasting companies or key financial institutions, in which PCs affected by malicious code obstruct normal operations, has been increasing. With the widespread availability of internet technology, the frequency of intelligent cyber-attacks in virtual cyber environments, such as APT attacks, continues to rise. Through an intelligent analysis of cyber threats which are still unknown, it is possible to prevent security accidents before they occur through the use of intelligent security analysis methods based on big data. The researcher conduct

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Hand, David J., Douglas H. Fisher, and Michael R. Berthold. "Advances in intelligent data analysis." Intelligent Data Analysis 4, no. 2 (2000): 93–95. http://dx.doi.org/10.3233/ida-2000-4201.

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Robins, V., J. Abernethy, N. Rooney, and E. Bradley. "Topology and intelligent data analysis." Intelligent Data Analysis 8, no. 5 (2004): 505–15. http://dx.doi.org/10.3233/ida-2004-8507.

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Dissertations / Theses on the topic "Intelligent data analysis"

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Cheng, Gongxian. "Outlier management in intelligent data analysis." Thesis, Birkbeck (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417120.

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Luo, Xu. "Power system fault analysis based on intelligent techniques and intelligent electronic device data." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5797.

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This dissertation has focused on automated power system fault analysis. New contributions to fault section estimation, protection system performance evaluation and power system/protection system interactive simulation have been achieved. Intelligent techniques including expert systems, fuzzy logic and Petri-nets, as well as data from remote terminal units (RTUs) of supervisory control and data acquisition (SCADA) systems, and digital protective relays have been explored and utilized to fufill the objectives. The task of fault section estimation is difficult when multiple faults, failures of pr

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Doumit, Sarjoun S. "IONA: Intelligent Online News Analysis." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544001149153864.

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Corney, David Peter Alfred. "Intelligent analysis of small data sets for food design." Thesis, University College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399765.

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Hammah, Reginald Edmund. "Intelligent delineation of rock discontinuity data using fuzzy cluster analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0012/NQ41436.pdf.

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Synnott, Jonathan. "Analysis, visualisation and simulation of sensor data within intelligent environments." Thesis, Ulster University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.601204.

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Reductions in fertility combined with increases in life expectancy are resulting in a globally ageing population. The result is an increasing strain on healthcare resources as members of the older population are more prone to suffer from chronic illness hence requiring long-term care and management. One current focus of research is to investigate methods of alleviating the increased strain on healthcare resources through the use of intelligent environments (IEs). IEs incorporate the use of sensor technology to facilitate long-term, home-based assessment of health condition with the goal of min

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Zhang, Zixing [Verfasser]. "Semi-Autonomous Data Enrichment and Optimisation for Intelligent Speech Analysis / Zixing Zhang." München : Verlag Dr. Hut, 2015. http://d-nb.info/1074063066/34.

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Zhou, Shang-Ming. "Machine learning and intelligent data analysis for interpretable neuro-fuzzy system modelling." Thesis, University of Essex, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426019.

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Khan, Atif A. "Intelligent data analysis for pattern recognition and medical diagnosis of ageing spine." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66677/.

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Every year, the healthcare industry collects a huge volume of data that is not mined properly and not put to optimal use. Discovery of the hidden patterns and relationships in data often goes unexploited. Data mining in the medical domain is more rigorous and complex to handle as most available raw medical data are voluminous and heterogeneous in nature. This research mines medical data related to human spine by learning patterns through the collected data and develops medical decision support systems based on intelligent system techniques. This study will help medical specialists in clinical

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Ercan, Tolga. "Sustainability Analysis of Intelligent Transportation Systems." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5934.

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Commuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable impacts of the congested roadway problem, Intelligent Transportation Systems (ITS) has been utilized to imp

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Books on the topic "Intelligent data analysis"

1

Berthold, Michael, and David J. Hand, eds. Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4.

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Berthold, Michael, and David J. Hand, eds. Intelligent Data Analysis. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-48625-1.

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Moewes, Christian, and Andreas Nürnberger, eds. Computational Intelligence in Intelligent Data Analysis. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32378-2.

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Pan, Jeng-Shyang, Václav Snášel, Tien-Wen Sung, and Xiao Dong Wang, eds. Intelligent Data Analysis and Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48499-0.

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Berthold, Michael R., Christian Borgelt, Frank Höppner, and Frank Klawonn. Guide to Intelligent Data Analysis. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-260-3.

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Berthold, M. Intelligent data analysis: An introduction. Springer, 1999.

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Hand, David J., Joost N. Kok, and Michael R. Berthold, eds. Advances in Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48412-4.

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Hoffmann, Frank, David J. Hand, Niall Adams, Douglas Fisher, and Gabriela Guimaraes, eds. Advances in Intelligent Data Analysis. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44816-0.

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Abraham, Ajith, Xin Hua Jiang, Václav Snášel, and Jeng-Shyang Pan, eds. Intelligent Data Analysis and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21206-7.

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name, No. Intelligent data analysis: An introduction. 2nd ed. Springer Verlag, 2003.

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Book chapters on the topic "Intelligent data analysis"

1

Schuller, Björn. "Audio Data." In Intelligent Audio Analysis. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36806-6_5.

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Hand, David J. "Introduction." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_1.

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Liu, Xiaohui. "Systems and Applications." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_10.

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Feelders, Ad J. "Statistical Concepts." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_2.

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Taylor, Paul. "Statistical Methods." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_3.

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Ramoni, Marco, and Paola Sebastiani. "Bayesian Methods." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_4.

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Bradley, Elizabeth. "Analysis of Time Series." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_5.

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van den Eijkel, Gerard C. "Rule Induction." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_6.

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Silipo, Rosaria. "Neural Networks." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_7.

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Berthold, Michael. "Fuzzy Logic." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_8.

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Conference papers on the topic "Intelligent data analysis"

1

Shen, Yun, Trevor P. Martin, and Pete Bramhall. "Intelligent Security Data Analysis." In 2009 International Conference on Computational Intelligence and Security. IEEE, 2009. http://dx.doi.org/10.1109/cis.2009.10.

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Wang, Jia, Zhijun Song, Qian Li, Jun Yu, and Fei Chen. "Semantic-based intelligent data clean framework for big data." In 2014 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2014. http://dx.doi.org/10.1109/spac.2014.6982731.

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Filatov, T., and V. Popov. "Intelligent analysis tools for computer based assessments." In DATA MINING AND MIS 2006. WIT Press, 2006. http://dx.doi.org/10.2495/data060371.

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Wen Fan, Yuan Liao, T. Laughner, et al. "Intelligent data analysis for power systems." In 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges. IEEE, 2012. http://dx.doi.org/10.1109/pesgm.2012.6344953.

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Arass, M. El, I. Tikito, and N. Souissi. "Data lifecycles analysis: Towards intelligent cycle." In 2017 Intelligent Systems and Computer Vision (ISCV). IEEE, 2017. http://dx.doi.org/10.1109/isacv.2017.8054938.

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Filice, Monica, Pierantonio Luca, and Alfonso Nastro. "Intelligent Data Analysis in Environmental Sampling." In 2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IEEE, 2005. http://dx.doi.org/10.1109/idaacs.2005.283056.

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Majeed, B., T. Martin, N. Clarke, and Beum-Seuk Lee. "Intelligent data analysis for wellbeing monitoring." In Perspectives in Pervasive Computing. IET, 2005. http://dx.doi.org/10.1049/ic.2005.0782.

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Pintar, Damir, Mihaela Vranic, and Zoran Skocir. "Intelligent data sources and integrated data repository as a foundation for business intelligence analysis." In 2007 15th International Conference on Software, Telecommunications and Computer Networks. IEEE, 2007. http://dx.doi.org/10.1109/softcom.2007.4446123.

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Bilalli, Besim, Alberto Abelló, Tomàs Aluja-Banet, and Robert Wrembel. "Towards Intelligent Data Analysis: The Metadata Challenge." In International Conference on Internet of Things and Big Data. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005876203310338.

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Semenova, Valentina A., and Sergey V. Smirnov. "Intelligent analysis of incomplete data for buildingformalontologies." In International Conference Information Technology and Nanotechnology 2016. Samara State Aerospace University, Image Processing Systems Institute, Russian Academy of Sciences, 2016. http://dx.doi.org/10.18287/1613-0073-2016-1638-796-805.

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Reports on the topic "Intelligent data analysis"

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Kamath, C. Intelligent Sampling for Surrogate Modeling, Hyperparameter Optimization, and Data Analysis. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1836193.

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Mazari, Mehran, Siavash F. Aval, Siddharth M. Satani, David Corona, and Joshua Garrido. Developing Guidelines for Assessing the Effectiveness of Intelligent Compaction Technology. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.1923.

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Many factors affect pavement compaction quality, which can vary. Such variability may result in an additional number of passes required, extended working hours, higher energy consumption, and negative environmental impacts. The use of Intelligent Compaction (IC) technology during construction can improve the quality and longevity of pavement structures while reducing risk for contractors and project owners alike. This study develops guidelines for the implementation of IC in the compaction of pavement layers as well as performing a preliminary life-cycle cost analysis (LCCA) of IC technology c

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Fink, Eugene, Jaime G. Carbonell, Anatole Gershman, Ganesh Mani, and Dwight Dietrich. Representation and Analysis of Probabilities Intelligence Data (RAPID). Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada498238.

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Stevens, Garrison Nicole, Kendra Lu Van Buren, and Francois M. Hemez. DARHT Multi-intelligence Seismic and Acoustic Data Analysis. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1291257.

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Murdick, Dewey, and Patrick Thomas. Patents and Artificial Intelligence: A Primer. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200038.

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Patent data can provide insights into the most active countries, fields and organizations in artificial intelligence research. This data brief analyzes worldwide trends in AI patenting to offer metrics on inventive activity.

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Mahlberg, Justin, Yaguang Zhang, Sneha Jha, et al. Development of an Intelligent Snowplow Truck that Integrates Telematics Technology, Roadway Sensors, and Connected Vehicle. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317355.

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The Indiana Department of Transportation (INDOT) manages and maintains over 28,000 miles of roadways. Maintenance of the roadways includes pavement repair in the summer as well as snow removal and de-icing in the winter. The prioritization of assets during winter storm events is crucial and impacts travel and safety. The objective of this project was to identify and develop tools INDOT could provide its operators to effectively perform winter operation de-icing activities. This project examined application methods and data to provide analytics and make data-driven decisions for state-wide depl

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Tayeb, Shahab. Protecting Our Community from the Hidden Vulnerabilities of Today’s Intelligent Transportation Systems. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2132.

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The ever-evolving technology interwoven into the transportation industry leaves it frequently at risk for cyber-attacks. This study analyzes the security of a common in-vehicle network, the Controller Area Network (CAN), standard in most vehicles being manufactured today. Like many other networks, CAN comes with inherent vulnerabilities that leave CAN implementations at risk of being targeted by cybercriminals. Such vulnerabilities range from eavesdropping, where the attacker can read the raw data traversing the vehicle, to spoofing, where the attacker can place fabricated traffic on the netwo

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Acharya, Ashwin, Max Langenkamp, and James Dunham. Trends in AI Research for the Visual Surveillance of Populations. Center for Security and Emerging Technology, 2022. http://dx.doi.org/10.51593/20200097.

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Progress in artificial intelligence has led to growing concern about the capabilities of AI-powered surveillance systems. This data brief uses bibliometric analysis to chart recent trends in visual surveillance research — what share of overall computer vision research it comprises, which countries are leading the way, and how things have varied over time.

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Toney, Autumn, and Melissa Flagg. U.S. Demand for AI-Related Talent Part II: Degree Majors and Skills Assessment. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200062.

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Future U.S. competitiveness in artificial intelligence will require a robust AI workforce. This data brief analyzes market demand for AI-related jobs to determine the skills necessary in the field. It concerns jobs considered both “core AI” and “AI-adjacent.”

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Ruvinsky, Alicia, Timothy Garton, Daniel Chausse, Rajeev Agrawal, Harland Yu, and Ernest Miller. Accelerating the tactical decision process with High-Performance Computing (HPC) on the edge : motivation, framework, and use cases. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42169.

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Managing the ever-growing volume and velocity of data across the battlefield is a critical problem for warfighters. Solving this problem will require a fundamental change in how battlefield analyses are performed. A new approach to making decisions on the battlefield will eliminate data transport delays by moving the analytical capabilities closer to data sources. Decision cycles depend on the speed at which data can be captured and converted to actionable information for decision making. Real-time situational awareness is achieved by locating computational assets at the tactical edge. Acceler

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