Bibliografías temáticas / Time recursive energy

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Literatura académica sobre el tema "Time recursive energy"

Autor: Grafiati
Publicado: 7 de junio de 2025
Última modificación: 2 de agosto de 2025

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Artículos de revistas sobre el tema "Time recursive energy"

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Slutsker, I. W., S. Mokhtari, and K. A. Clements. "Real time recursive parameter estimation in energy management systems." IEEE Transactions on Power Systems 11, no. 3 (1996): 1393–99. http://dx.doi.org/10.1109/59.535680.

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Rocha, Rodolfo Varraschim, Denis Vinicius Coury, and Renato Machado Monaro. "Recursive and non-recursive algorithms for power system real time phasor estimations." Electric Power Systems Research 143 (February 2017): 802–12. http://dx.doi.org/10.1016/j.epsr.2016.08.034.

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Dong, Shigui, Na Wang, Xueyan Wang, and Zihao Lu. "Extended Recursive Three-Step Filter for Linear Discrete-Time Systems with Dual-Unknown Inputs." Energies 16, no. 15 (2023): 5603. http://dx.doi.org/10.3390/en16155603.

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This paper proposes two new extended recursive three-step filters for linear discrete systems with dual-unknown inputs, which can simultaneously estimate unknown input and state. Extended recursive three-step filter 1 (ERTSF1) introduces an innovation for obtaining the estimates of the unknown input in the measurement equation, then derives the estimates of the unknown input in the state equation. After that, it uses the already obtained estimates of the dual-unknown inputs to correct the one-step prediction of the state, and finally, it obtains the minimum-variance unbiased estimate of the sy
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Sheltami, Tarek R., Danish Sattar, Elhadi M. Shakshuki, and Ashraf S. Mahmoud. "Real-Time Performance Evaluation for Flooding and Recursive Time Synchronization Protocols over Arduino and XBee." International Journal of Distributed Sensor Networks 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/652041.

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Time synchronization is a crucial part of distributed systems. It is often required for data reliability and coordination in wireless sensor networks (WSNs). Wireless sensor networks have three major goals: time synchronization, low bandwidth operation, and energy efficiency. Different time synchronization algorithms are aimed at achieving these objectives using various methods. This paper presents performance evaluation of two state-of-the-art time synchronization protocols, namely, Flooding Time Synchronization Protocol and Recursive Time Synchronization Protocol. To achieve time synchroniza
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5

Nelson-Isaacs, Sky. "Eliminating the Second-Order Time Dependence from the Time Dependent Schrödinger Equation Using Recursive Fourier Transforms." Quantum Reports 6, no. 3 (2024): 323–48. http://dx.doi.org/10.3390/quantum6030021.

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A strategy is developed for writing the time-dependent Schrödinger Equation (TDSE), and more generally the Dyson Series, as a convolution equation using recursive Fourier transforms, thereby decoupling the second-order integral from the first without using the time ordering operator. The energy distribution is calculated for a number of standard perturbation theory examples at first- and second-order. Possible applications include characterization of photonic spectra for bosonic sampling and four-wave mixing in quantum computation and Bardeen tunneling amplitude in quantum mechanics.
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Hu, Xuekai, Siming Zeng, Liang Meng, Tiecheng Li, and Qian Zhang. "Fast-tracking method of inertial constant based on system identification." Science and Technology for Energy Transition 79 (2024): 4. http://dx.doi.org/10.2516/stet/2023045.

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Aiming at the problem of quantitative inertia evaluation of a new energy electric power system, the system inertia constant tracking method based on system identification is studied. The method is divided into two categories: non-recursive algorithm and recursive algorithm. The non-recursive algorithm uses a batch of data for batch processing to obtain the estimated value of the identification model parameters. The recursive algorithm is based on the estimated value of the model parameter at the previous moment and corrects the estimated value based on the new data currently obtained. From the
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Madhiarasan, Manoharan, Mohamed Louzazni, and Brahim Belmahdi. "Statistical Analysis of Novel Ensemble Recursive Radial Basis Function Neural Network Performance on Global Solar Irradiance Forecasting." Journal of Electrical and Computer Engineering 2023 (March 28, 2023): 1–10. http://dx.doi.org/10.1155/2023/2554355.

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Reliable operation of energy management systems, grid stability, and managing energy demand responses are becoming challenging because of the flickering nature of solar irradiance. Accurate forecasting of global solar irradiance, i.e., global horizontal irradiance (GHI), plays a significant role in energy policy-making and the energy market. This paper proposes a novel global solar irradiance forecasting model based on the ensemble recursive radial basis function neural networks (ERRBFNNs). The various atmospheric inputs based on the built ensemble recursive radial basis function neural networ
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Bouhdid, Badia, Wafa Akkari, and Sofien Gannouni. "Low Cost Recursive Localization scheme for High Density Wireless Sensor Networks." International Journal on Semantic Web and Information Systems 13, no. 3 (2017): 68–88. http://dx.doi.org/10.4018/ijswis.2017070104.

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While existing localization approaches mainly focus on enhancing the accuracy, particular attention has recently been given to reducing the localization algorithm implementation costs. To obtain a tradeoff between location accuracy and implementation cost, recursive localization approaches are being pursued as a cost-effective alternative to the more expensive localization approaches. In the recursive approach, localization information increases progressively as new nodes compute their positions and become themselves reference nodes. A strategy is then required to control and maintain the dist
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Wang, Cheng, Haiyang Huang, Xiongming Lai, and Jianwei Chen. "A New Online Operational Modal Analysis Method for Vibration Control for Linear Time-Varying Structure." Applied Sciences 10, no. 1 (2019): 48. http://dx.doi.org/10.3390/app10010048.

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From the viewpoint of vibration control, if the amplitude of the main frequencies of the vibration response can be reduced, the vibration energy of the structure is greatly reduced. Modal parameters, including modal shapes, natural frequencies, and damping ratios, can reflect the dynamics of the structure and can be used to control the vibration. This paper integrates the idea of “forgetting factor weighting” into eigenvector recursive principal component analysis, and then proposes an operational modal analysis (OMA) method that uses eigenvector recursive PCA with a forgetting factor (ERPCAWF
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Costa, Bruno Sielly Jales, Plamen Parvanov Angelov, and Luiz Affonso Guedes. "Real-Time Fault Detection Using Recursive Density Estimation." Journal of Control, Automation and Electrical Systems 25, no. 4 (2014): 428–37. http://dx.doi.org/10.1007/s40313-014-0128-4.

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Tesis sobre el tema "Time recursive energy"

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Brus, Linda. "Nonlinear Identification and Control with Solar Energy Applications." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8594.

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Capítulos de libros sobre el tema "Time recursive energy"

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Chang, Chein-I. "Recursive Hyperspectral Band Processing for Active Target Detection: Constrained Energy Minimization." In Real-Time Recursive Hyperspectral Sample and Band Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45171-8_13.

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Chang, Chein-I. "Real-Time Recursive Hyperspectral Sample Processing for Active Target Detection: Constrained Energy Minimization." In Real-Time Recursive Hyperspectral Sample and Band Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45171-8_5.

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Bouhdid, Badia, Wafa Akkari, and Sofien Gannouni. "Low Cost Recursive Localization scheme for High Density Wireless Sensor Networks." In Sensor Technology. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2454-1.ch013.

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While existing localization approaches mainly focus on enhancing the accuracy, particular attention has recently been given to reducing the localization algorithm implementation costs. To obtain a tradeoff between location accuracy and implementation cost, recursive localization approaches are being pursued as a cost-effective alternative to the more expensive localization approaches. In the recursive approach, localization information increases progressively as new nodes compute their positions and become themselves reference nodes. A strategy is then required to control and maintain the dist
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4

Bouhdid, Badia, Wafa Akkari, Abdelfettah Belghith, and Sofien Gannouni. "An Efficient Recursive Localization Approach for High-Density Wireless Sensor Networks." In Semantic Web Science and Real-World Applications. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7186-5.ch008.

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Although recursive localization approaches are efficiently used in wireless sensor networks (WSNs), their application leads to increased energy consumption caused by the important communication overhead necessary to achieve the localization task. Indeed, localization information coverage increases iteratively as new nodes estimate their locations and become themselves new reference nodes. However, the uncontrollable number evolution of such nodes leads, especially in high density networks, to wasted energy, important communication overhead and even impacts the localization accuracy due the adv
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5

Zhong, Ying, Bo Zhang, Li Zheng, Dantong Feng, and Xu Ji. "Cleaning Time Prediction Method of Photovoltaic Power Station Based on Short-Term Environmental Change." In Advances in Energy Research and Development. IOS Press, 2022. http://dx.doi.org/10.3233/aerd220032.

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In view of the cleaning problems of photovoltaic (PV) plants, existing studies focus on the optimization of cleaning frequency or cleaning period equivalent. However, few consider the possible influence of short-term weather changes on the optimal cleaning time in this period. This paper proposes a cleaning time prediction algorithm for PV plants. By predicting the comprehensive efficiency of the system, the peak sun power, and the peak sun hour, a recursive algorithm was used to calculate the difference between the expected power generation income and the cleaning cost under different cleanin
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6

Mohamed, Khala, Ismail Elabbassi, Naima El Yanboiy, et al. "Machine Learning-Based Short-Term Photovoltaic Power Forecasting Using Exogenous Meteorological Data." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-1220-0.ch008.

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Machine Learning (ML) plays a transformative role in optimizing energy management processes. Hence, this study evaluates the capability of predicting short-term Photovoltaic (PV) power generation utilizing exogenous weather data through ML techniques, including Support Vector Machine (SVM), Random Forest (RF), and Multilayer Perceptron (MLP). The collected data underwent preprocessing, and the respective models were trained. The aim is to achieve higher prediction accuracy, reduced prediction errors and efficient use of time computation. The results demonstrate promising performance of the pro
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Actas de conferencias sobre el tema "Time recursive energy"

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Rommetveit, Tarjei, Roy Johnsen, Tonni F. Johansen, and Øystein Baltzersen. "High Resolution Ultrasound Wall Thickness Measurements through Polyester Coating and Real-Time Process Control." In CORROSION 2009. NACE International, 2009. https://doi.org/10.5006/c2009-09452.

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Abstract Epoxy-, polyester-, paint and similar coatings are often used for external corrosion protection on pipelines and other process equipment. It is well known that ultrasound transducers can determine wall thickness through such coatings. This paper explores how the sensitivity of high resolution pulse-echo ultrasound measurements from permanently installed immersion sensors are affected by measuring through a 300 μm layer of polyester powder coating compared to measuring on plain steel. The results show that the standard deviation is below 6 nm for both specimens. Further, there is no de
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2

Sun, Kang, Ruitong Liu, Manyun Huang, Zhinong Wei, Fangwei Duan, and Guoqiang Sun. "Real-Time Recursive Correction State Estimation Utilizing Only SCADA Measurements." In 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2021. http://dx.doi.org/10.1109/ei252483.2021.9713154.

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Raihan, Sheikh Arif, and Balakumar Balasingam. "Recursive Least Square Estimation Approach to Real-Time Parameter Identification in Li-ion Batteries." In 2019 IEEE Electrical Power and Energy Conference (EPEC). IEEE, 2019. http://dx.doi.org/10.1109/epec47565.2019.9074825.

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Silveira, P. M., C. Duque, T. Baldwin, and P. F. Ribeiro. "Sliding window recursive DFT with dyadic downsampling — A new strategy for time-varying power harmonic decomposition." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275212.

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Hu, Yiran, and Yue-Yun Wang. "Real-Time Battery Model Identification Using a Two Time-Scaled Approach." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3776.

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Battery state estimation (BSE) is one of the most important design aspects of an electrified propulsion system. It includes important functions such as state-of-charge estimation which is essentially for the energy management system. A successful and practical approach to battery state estimation is via real time battery model parameter identification. In this approach, a low-order control-oriented model is used to approximate the battery dynamics. Then a recursive least squares is used to identify the model parameters in real time. Despite its good properties, this approach can fail to identi
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Kim, Sun, and Karl B. Ousterhout. "The Development of a Real Time Recursive Frequency Based Active Chatter Controller." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0254.

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Abstract In most machining processes, large amounts of energy are needed to accomplish the machining operation. When this energy is transmitted through a structure that has minimal damping characteristics, such as a lathe or a milling machine, self sustained oscillations (chatter) can develop. When chatter develops, it can be viewed as a basic performance limitation of the machine tool. In order to suppress the chatter, a real-time controller using digital signal processing techniques has been implemented. This paper discusses a novel method for the real time computation of the transfer functi
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Sadrpour, Amir, Jionghua (Judy) Jin, and A. Galip Ulsoy. "Real-Time Energy-Efficient Path Planning for Unmanned Ground Vehicles Using Mission Prior Knowledge." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3909.

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Surveillance missions that involve unmanned ground vehicles (UGVs) include situations where a UGV has to choose between alternative paths to complete its mission. Currently, UGV missions are often limited by the available on-board energy. Thus, we propose a dynamic most energy-efficient path planning algorithm that integrates mission prior knowledge with real-time sensory information to identify the mission’s most energy-efficient path. Our proposed approach predicts and updates the distribution of energy requirement of alternative paths using recursive Bayesian estimation through two stages:
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8

Huynh, Duy C., Matthew W. Dunnigan, and Stephen J. Finney. "On-line parameter estimation of an induction machine using a recursive least-squares algorithm with multiple time-varying forgetting factors." In 2010 IEEE International Conference on Power and Energy (PECon). IEEE, 2010. http://dx.doi.org/10.1109/pecon.2010.5697624.

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Guevara, Jose L., and Japan Trivedi. "Dynamic Surrogate Model for Oil Production Rates Prediction in SAGD Processes." In SPE Canadian Energy Technology Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212756-ms.

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Abstract In this paper we propose a novel framework for the identification of a dynamic surrogate model (DSM) that can offer a fast and effective prediction of time-varying outputs (e.g., oil rates) of a Steam Assisted Gravity Drainage process. In the framework, the prediction at any given time consists of the addition of two components: a base model plus a correction term. The former is represented by a conventional one-step forecast nonlinear model(s) used recursively to make n-steps ahead forecast. The latter is modeled error term, rationalized under the assumption that the forecast error g
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10

Ekong, Otuekong E., Anthony U. Etim, and Anietie P. Ekong. "Automated Real-Time Electricity Supply Monitoring System." In 27th iSTEAMS-ACity-IEEE International Conference. Society for Multidisciplinary and Advanced Research Techniques - Creative Research Publishers, 2021. http://dx.doi.org/10.22624/aims/isteams-2021/v27p2.

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In many developing countries, several homes are yet to be fitted with the traditional electro-mechanical meter or newer smart meter for measuring electricity consumption. As such, distribution network operators resort to estimated billing. This work proposes a low cost and easy-to-install alternative capable of monitoring the duration of supply which can be used as the basis to generate bills for unmetered customers. The Recursive Waterfall model guided its design and implementation. The system comprises of Electricity Supply Monitoring (ESM) Hub and ESM App. The Hub is the sensing unit and is
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