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Relevant bibliographies by topics / Electrical engineering-time series analysis

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Academic literature on the topic 'Electrical engineering-time series analysis'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

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Journal articles on the topic "Electrical engineering-time series analysis"

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Meena Chavan. "Time Series Analysis in Electrical Load Forecasting." Panamerican Mathematical Journal 35, no. 1s (2024): 210–19. http://dx.doi.org/10.52783/pmj.v35.i1s.2307.

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Time series analysis in electricity load projection is a key part of the energy sector because it makes it possible to control and distribute energy more efficiently. It is important to have accurate load forecasts in order to balance supply and demand, make power systems run more efficiently, and lower operating costs. This essay covers a wide range of ways that time series analysis can be used to guess how much electricity will be used. The study looks at a number of different models, such as the autoregressive integrated moving average (ARIMA), exponential smoothing, and machine learning me

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OSTERHAGE, HANNES, and KLAUS LEHNERTZ. "NONLINEAR TIME SERIES ANALYSIS IN EPILEPSY." International Journal of Bifurcation and Chaos 17, no. 10 (2007): 3305–23. http://dx.doi.org/10.1142/s0218127407019081.

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The framework of the theory of nonlinear dynamics provides powerful concepts and algorithms to study complicated dynamics such as brain electrical activity (electroencephalogram, EEG). Although different influencing factors render the use of nonlinear measures in a strict sense problematic, converging evidence from various investigations now indicates that nonlinear EEG analysis provides a means to reliably characterize different states of physiological and pathophysiological brain function. We here focus on applications of nonlinear EEG analysis in epileptology. Epilepsy affects more than 50

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Broersen, P. M. T., and S. de Waele. "Time series analysis in a frequency subband." IEEE Transactions on Instrumentation and Measurement 52, no. 4 (2003): 1054–60. http://dx.doi.org/10.1109/tim.2003.814823.

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Beňová, Mariana, Branislav Dobrucký, Jozef Šedo, et al. "A Novel Approach to Transient Fourier Analysis for Electrical Engineering Applications." Applied Sciences 14, no. 21 (2024): 9888. http://dx.doi.org/10.3390/app14219888.

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This paper presents a detailed investigation into the application of transient Fourier analysis in select electrical engineering contexts. Two novel approaches for addressing transient analysis are introduced. The first approach combines the Fourier series with the Laplace–Carson (L-C) transform in the complex domain, utilizing complex time vectors to streamline the computation of the original function. The inverse transformation back into the time domain is achieved using the Cauchy-Heaviside (C-H) method. The second approach applies the Fourier transform (F-Τ) for the transient analysis of a

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Petitjean, Francois, and Jonathan Weber. "Efficient Satellite Image Time Series Analysis Under Time Warping." IEEE Geoscience and Remote Sensing Letters 11, no. 6 (2014): 1143–47. http://dx.doi.org/10.1109/lgrs.2013.2288358.

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Voloshko, Anatolii V., Yaroslav S. Bederak, and Oleksandr A. Kozlovskyi. "AN IMPROVED PRE-FORECASTING ANALYSIS OF ELECTRICAL LOADS OF PUMPING STATION." Resource-Efficient Technologies, no. 4 (February 21, 2020): 20–29. http://dx.doi.org/10.18799/24056537/2019/4/265.

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Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods

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Voloshko, A. V., Ya S. Bederak, and O. A. Kozlovskyi. "AN IMPROVED PRE-FORECASTING ANALYSIS OF ELECTRICAL LOADS OF PUMPING STATION." Resource-Efficient Technologies, no. 4 (February 21, 2020): 20–29. http://dx.doi.org/10.18799/24056529/2019/4/265.

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Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods

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Stoffer, David S. "Time series analysis by state space models." Automatica 39, no. 5 (2003): 954–55. http://dx.doi.org/10.1016/s0005-1098(03)00027-x.

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Broersen, P. M. T., and R. Bos. "Time-Series Analysis if Data Are Randomly Missing." IEEE Transactions on Instrumentation and Measurement 55, no. 1 (2006): 79–84. http://dx.doi.org/10.1109/tim.2005.861247.

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A., D. Awasare. "Fourier Series Analysis in Engineering: Advancements and Applications." Journal of Applied Mathematics and Statistical Analysis 5, no. 2 (2024): 21–24. https://doi.org/10.5281/zenodo.11208733.

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<em>Fourier series analysis stands as a cornerstone in engineering, offering powerful insights into the representation and manipulation of periodic functions. This research paper delves into the advancements and applications of Fourier series analysis across various engineering domains. Through an in-depth exploration of relevant scholarly works, the paper highlights key methodologies, techniques, and case studies where Fourier series analysis has been effectively employed. The abstract examines the utilization of Fourier series in signal processing, where it serves as a fundamental tool for s

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Dissertations / Theses on the topic "Electrical engineering-time series analysis"

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Rawizza, Mark Alan. "Time-series analysis of multivariate manufacturing data sets." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10895.

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Singh, Pushpendra. "Some studies on a generalized fourier expansion for nonlinear and nonstationary time series analysis." Thesis, IIT Delhi, 2016. http://localhost:8080/xmlui/handle/12345678/7064.

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Lee, Fung-Man. "Studies in time series analysis and forecasting of energy data." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36032.

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Hutchinson, James M. "A radial basis function approach to financial time series analysis." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/12216.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (p. 153-159).<br>by James M. Hutchinson.<br>Ph.D.

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Modlin, Danny Robert. "Utilizing time series analysis to forecast long-term electrical consumption /." Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/modlind/dannymodlin.pdf.

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Dzunic, Zoran Ph D. Massachusetts Institute of Technology. "A Bayesian latent time-series model for switching temporal interaction analysis." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103723.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 153-157).<br>We introduce a Bayesian discrete-time framework for switching-interaction analysis under uncertainty, in which latent interactions, switching pattern and signal states and dynamics are inferred from noisy and possibly missing observations of these signals. We propose reasoning over posterior distribution of these latent variables as a means of combating and characterizing uncer

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Lindberg, Johan. "A Time Series Forecast of the Electrical Spot Price : Time series analysis applied to the Nordic power market." Thesis, Umeå universitet, Institutionen för fysik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-41898.

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In this report six different models for predicting the electrical spot price on the Nordic power exchange, Nord Pool, are developed and compared. They are evaluated against the already existing model as well as the naive test, which is a forecast where the last week’s observations are used as a prognosis for the coming week. The models developed are constructed so that the models for different time resolutions are combined to create a full model. Harmonic regression with a linear trend are used to identify a yearly trend while SARIMAX/SARIMA time series models are used on a daily and hourly ba

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Thungtong, Anurak. "Synchronization, Variability, and Nonlinearity Analysis: Applications to Physiological Time Series." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1364316597.

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Shashidhar, Akhil. "Generalized Volterra-Wiener and surrogate data methods for complex time series analysis." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/41619.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (leaves 133-150).<br>This thesis describes the current state-of-the-art in nonlinear time series analysis, bringing together approaches from a broad range of disciplines including the non-linear dynamical systems, nonlinear modeling theory, time-series hypothesis testing, information theory, and self-similarity. We stress mathematical and qualitative relationships between key algorithms in the respective disciplines in addition to describin

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Siracusa, Michael Richard 1980. "Dynamic dependence analysis : modeling and inference of changing dependence among multiple time-series." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53303.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 183-190).<br>In this dissertation we investigate the problem of reasoning over evolving structures which describe the dependence among multiple, possibly vector-valued, time-series. Such problems arise naturally in variety of settings. Consider the problem of object interaction analysis. Given tracks of multiple moving objects one may wish to describe if and how these objects are interacting over

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Books on the topic "Electrical engineering-time series analysis"

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Mohajer, Maryam. Monlinear time series analysis of electrical activity in a slice model of epilepsy. National Library of Canada, 1999.

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Wei, Y. Common waveform analysis: A new and practical generalization of Fourier analysis. Kluwer Academic Publishers, 2000.

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1927-, Akaike Hirotsugu, and Kitagawa G. 1948-, eds. The practice of time series analysis. Springer, 1999.

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Reinsel, Gregory C. Elements of Multivariate Time Series Analysis. Springer US, 1993.

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Machiwal, Deepesh. Hydrologic Time Series Analysis: Theory and Practice. Springer Netherlands, 2012.

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Bittanti, Sergio. Time Series and Linear Systems. Springer Berlin Heidelberg, 1986.

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Box, George E. P. Time series analysis: Forecasting and control. 4th ed. John Wiley, 2008.

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Box, George E. P. Time series analysis: Forecasting and control. 3rd ed. Prentice Hall, 1994.

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Box, George E. P. Time series analysis: Forecasting and control. 4th ed. John Wiley, 2008.

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Montgomery, Douglas C. Introduction to time series analysis and forecasting. John Wiley, 2007.

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Book chapters on the topic "Electrical engineering-time series analysis"

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Ao, Sio-Iong. "Applied Time Series Analysis." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8768-3_2.

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Kathuria, Charu, Deepti Mehrotra, Shalini Bhartiya, and Navnit Kumar Misra. "The Analysis of Time Series Data." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4687-5_17.

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He, Yuefan, Shuangcheng Zhang, Qianyi Wang, Qi Liu, Wei Qu, and Xiaowei Hou. "HECTOR for Analysis of GPS Time Series." In Lecture Notes in Electrical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0005-9_16.

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Sai Anand, M., and R. Ramalakshmi. "Time Series Analysis to Forecast Wind Speed." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2177-3_38.

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Ahmia, Oussama, and Nadir Farah. "Electrical Load Forecasting: A Parallel Seasonal Approach." In Time Series Analysis and Forecasting. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28725-6_26.

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Hahm, Jaegyoon, Oh-Kyoung Kwon, Sangwan Kim, et al. "Astronomical Time Series Data Analysis Leveraging Science Cloud." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5076-0_60.

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Cheng, Xiaorong, and Xiaomeng Zhao. "Network Risk Prediction Based on Time Series Analysis." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40618-8_92.

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Ma, Yiguo, Guanchen Zhou, and Ying Jiao. "Geographical Profile Based on Time-Series Analysis Model." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40630-0_5.

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Sejwal, Sahil, Kartik Aggarwal, and Soumya Ranjan Nayak. "Time Series Analysis of Crypto Currency Using ARIMAX." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5974-7_20.

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Pallavi, M., Awakash Mishra, Jayashree M. Kudari, and Ankit Belwal. "Identifying Acute Disseminated Encephalomyelitis with Time Series Analysis." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8043-3_102.

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Conference papers on the topic "Electrical engineering-time series analysis"

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Khair, Asdaqul, Lesnanto Multa Putranto, and Dyonisius Dony Ariananda. "Time Series Analysis for Solar Irradiance Forecasting: A Systematic Review." In 2025 15th International Conference on Electrical Engineering (ICEENG). IEEE, 2025. https://doi.org/10.1109/iceeng64546.2025.11031366.

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Surekha, Reshma, Divya Gupta, Adarsh Kumar Jha, Maridu Bhargavi, and Poorna Sai. "Stock Price Forecasting by Time Series Analysis." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910437.

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Zhen, Yang, Zhang Haiqing, Gong Cheng, et al. "Photovoltaic Power Impact Analysis Based on Nonlinear Correlation and Time Series Model." In 2024 7th Asia Conference on Energy and Electrical Engineering (ACEEE). IEEE, 2024. http://dx.doi.org/10.1109/aceee62329.2024.10652074.

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Wu, Shuhong, Jingyu Zhou, Yihong Zhang, and Ye Feng. "Time Series Analysis of Electric Vehicle Charging Station Layout Based on LSTM Model." In 2024 4th International Conference on Energy, Power and Electrical Engineering (EPEE). IEEE, 2024. https://doi.org/10.1109/epee63731.2024.10875344.

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Wang, Xinxiu. "Prediction Algorithm of Dance Movement Rhythm and Coordination Based on Time Series Analysis." In 2024 International Conference on Power, Electrical Engineering, Electronics and Control (PEEEC). IEEE, 2024. https://doi.org/10.1109/peeec63877.2024.00107.

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Gupta, Muktesh. "Optimizing Time Series Denoising with an Improved Singular Spectrum Analysis Approach." In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2025. https://doi.org/10.1109/sceecs64059.2025.10940692.

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Hussein, Areej, Gerald Guan Gan Goh, Mohammad Ali Anbar, Mohammad Nassr, Mariya I. Semenova, and Tatiana V. Aksenova. "Comparative Evaluation of Machine Learning Models for Time Series Forecasting in Network Traffic Analysis." In 2025 7th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2025. https://doi.org/10.1109/reepe63962.2025.10971155.

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Joseph, Susmera, Ashly Ann Jo, and Ebin Deni Raj. "Improving Time Series Forecasting Accuracy with Transformers: A Comprehensive Analysis with Explainability." In 2024 Third International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2024. http://dx.doi.org/10.1109/iceeict61591.2024.10718609.

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Guo, Jinyi. "Research on predictive analysis of time series based on big data and artificial intelligence technology." In 2024 IEEE 2nd International Conference on Electrical, Automation and Computer Engineering (ICEACE). IEEE, 2024. https://doi.org/10.1109/iceace63551.2024.10898768.

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Vinya, Viyyapu Lokeshwari, K. K. Manivannan, S. K. Manivannan, C. Sathiyamoorthy, M. Jagadeeswaran, and B. Meenakshi. "Cloud-Enabled Predictive Vehicle Health Monitoring and Maintenance with LSTM Networks for Time-Series Analysis." In 2024 First International Conference on Innovations in Communications, Electrical and Computer Engineering (ICICEC). IEEE, 2024. https://doi.org/10.1109/icicec62498.2024.10808613.

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Reports on the topic "Electrical engineering-time series analysis"

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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concep

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Mazzoni, Silvia, Nicholas Gregor, Linda Al Atik, Yousef Bozorgnia, David Welch, and Gregory Deierlein. Probabilistic Seismic Hazard Analysis and Selecting and Scaling of Ground-Motion Records (PEER-CEA Project). Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2020. http://dx.doi.org/10.55461/zjdn7385.

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This report is one of a series of reports documenting the methods and findings of a multi-year, multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER) and funded by the California Earthquake Authority (CEA). The overall project is titled “Quantifying the Performance of Retrofit of Cripple Walls and Sill Anchorage in Single-Family Wood-Frame Buildings,” henceforth referred to as the “PEER–CEA Project.” The overall objective of the PEER–CEA Project is to provide scientifically based information (e.g., testing, analysis, and resulting loss models) that

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Morin, Shai, Gregory Walker, Linda Walling, and Asaph Aharoni. Identifying Arabidopsis thaliana Defense Genes to Phloem-feeding Insects. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7699836.bard.

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The whitefly (Bemisia tabaci) is a serious agricultural pest that afflicts a wide variety of ornamental and vegetable crop species. To enable survival on a great diversity of host plants, whiteflies must have the ability to avoid or detoxify numerous different plant defensive chemicals. Such toxins include a group of insect-deterrent molecules called glucosinolates (GSs), which also provide the pungent taste of Brassica vegetables such as radish and cabbage. In our BARD grant, we used the whitefly B. tabaci and Arabidopsis (a Brassica plant model) defense mutants and transgenic lines, to gain

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Torres, Marissa, Norberto Nadal-Caraballo, and Alexandros Taflanidis. Rapid tidal reconstruction for the Coastal Hazards System and StormSim part II : Puerto Rico and U.S. Virgin Islands. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41482.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the continuing efforts towards incorporating rapid tidal time-series reconstruction and prediction capabilities into the Coastal Hazards System (CHS) and the Stochastic Storm Simulation System (StormSim). The CHS (Nadal-Caraballo et al. 2020) is a national effort for the quantification of coastal storm hazards, including a database and web tool (https://chs.erdc.dren.mil) for the deployment of results from the Probabilistic Coastal Hazard Analysis (PCHA) framework. These PCHA products are developed from regional studies s

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Veung, Naron, and Seyhah Ven. Exploring Insights into Vocational Skills Development and Industrial Transformation in Cambodia. Cambodia Development Resource Institute, 2021. https://doi.org/10.64202/wp.131.202110.

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Industrial development is central to Cambodia’s economic development as it plans to upgrade the country’s status to an upper-middle-income country by 2030 and to a high-income country by 2050. Equipping the workforce with the skills and competencies that match industrial needs requires a great deal of continuous efforts and resources. In this regard, this paper aims to look into the linkage between skills and transformation based on employers’ perspectives. It explores insights into how companies perceive and use the skills and qualifications of their employees to overcome changes in technolog

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Vargas-Herrera, Hernando, Juan Jose Ospina-Tejeiro, Carlos Alfonso Huertas-Campos, et al. Monetary Policy Report - April de 2021. Banco de la República de Colombia, 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2021.

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1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lowe

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