Готові списки джерел за темами / Forecasting of the state of systems

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Добірка наукової літератури з теми "Forecasting of the state of systems"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 липня 2025

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Статті в журналах з теми "Forecasting of the state of systems"

Afanaseva, Olga S., Galina F. Egorova, and Elena A. Afanaseva. "Forecasting state diagrams two-component salt systems." Vestnik of Samara State Technical University. Technical Sciences Series 32, no. 1 (2024): 6–17. http://dx.doi.org/10.14498/tech.2024.1.1.

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The article proposes a method for forecasting and approximate calculating the two-component systems characteristics state diagrams. The results for 200 salt systems with a common cation and 100 with a common anion systems statistical analysis of fase diagrams are presented. In this paper, the authors propose to consider two signs of the eutectic points presence in binary systems and a method for approximate calculation the eutectic point temperature and concentration values. The first criterion for the presence or absence of eutectic points in the system is determined using specific, isobaric

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Lvovich, Yakov Ye, Andrey P. Preobrazhenskiy, and Tatiana V. Avetisyan. "OPTIMIZATION AND STATE FORECASTING IN TRANSPORTATION SYSTEMS." International Journal of Advanced Studies 12, no. 3 (2022): 109–24. http://dx.doi.org/10.12731/2227-930x-2022-12-3-109-124.

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Optimization of transport work is necessary in case of uncontrollable growth of the described costs. The process of optimizing transport costs at the enterprise begins with an analysis of the current logistics strategy and collection of recommendations for its correction. The following aspects of the transport system of the company are subject to analysis: the method of movement of goods; the choice of vehicle type and its specific model; the selection of the carrier company and other logistics intermediaries; the layout of the company’s storage terminals. An optimized transport system can red

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Іgor, Romanenko, Golovanov Andrii, Khoma Vitalii, et al. "Development of estimation and forecasting method in intelligent decision support systems." Eastern-European Journal of Enterprise Technologies 2, no. 4(110) (2021): 38–47. https://doi.org/10.15587/1729-4061.2021.229160.

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The method of estimation and forecasting in intelligent decision support systems is developed. The essence of the proposed method is the ability to analyze the current state of the object under analysis and the possibility of short-term forecasting of the object state. The possibility of objective and complete analysis is achieved through the use of improved fuzzy temporal models of the object state, an improved procedure for forecasting the object state and an improved procedure for training evolving artificial neural networks. The concepts of a fuzzy cognitive model, in contrast to the known

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Kureichik, V. M., Ye S. Sinyutin, and T. G. Kaplunov. "FORECASTING THE STATE OF TECHNICAL SYSTEMS USING GENETIC ALGORITHMS." Vestnik of Ryazan State Radio Engineering University 65 (2018): 107–12. http://dx.doi.org/10.21667/1995-4565-2018-65-3-107-112.

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Gusiev, O. Yu, V. І. Мagro, and O. I. Nikolska. "TELETRAFFIC FORECASTING IN MEDIA SERVICE SYSTEMS." Radio Electronics, Computer Science, Control, no. 4 (December 22, 2023): 7. http://dx.doi.org/10.15588/1607-3274-2023-4-1.

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Context. The development of information and communication technologies has led to an increase in the volume of information sent over the network. Media service platforms play an important role in the creation and processing of bitrate in the information network. Therefore, there is a need to develop a methodology for predicting bitrate in various media service platforms by creating an effective algorithm that minimizes the forecast error. Objective. The aim of the work is to synthesize in analytical form the state transition matrix of the Kalman filter for nonstationary self-similar proc

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Musaev, A. A., and D. A. Grigoriev. "MACHINE LEARNING BASED CYBER-PHYSICAL SYSTEMS FOR FORECASTING STATE OF UNSTABLE SYSTEMS." Mathematical Methods in Technologies and Technics, no. 7 (2021): 95–103. http://dx.doi.org/10.52348/2712-8873_mmtt_2021_7_95.

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ŻÓŁTOWSKI, Bogdan, Mariusz ŻÓŁTOWSKI, and Adam BARYŁKA. "Modelling the processes of degradation of the state of anthropogenic systems." Inżynieria Bezpieczeństwa Obiektów Antropogenicznych, no. 2 (July 1, 2025): 1–15. https://doi.org/10.37105/iboa.262.

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Anthropogenic impacts refer to environmental changes caused by or under the influence of humans, directly or indirectly. The article highlights the issue of technical diagnostics and presents selected problems related to the automation of procedures for assessing the degree of degradation of technical objects. The possibilities of using vibration methods with particular emphasis on condition forecasting are indicated. Current knowledge of these problems is insufficient and requires further research on data processing, analysis of the effectiveness of diagnostic and prognostic procedures, colle

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Tina, Giuseppe Marco, Cristina Ventura, Sergio Ferlito, and Saverio De Vito. "A State-of-Art-Review on Machine-Learning Based Methods for PV." Applied Sciences 11, no. 16 (2021): 7550. http://dx.doi.org/10.3390/app11167550.

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In the current era, Artificial Intelligence (AI) is becoming increasingly pervasive with applications in several applicative fields effectively changing our daily life. In this scenario, machine learning (ML), a subset of AI techniques, provides machines with the ability to programmatically learn from data to model a system while adapting to new situations as they learn more by data they are ingesting (on-line training). During the last several years, many papers have been published concerning ML applications in the field of solar systems. This paper presents the state of the art ML models app

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Romanenko, Іgor, Andrii Golovanov, Vitalii Khoma, et al. "Development of estimation and forecasting method in intelligent decision support systems." Eastern-European Journal of Enterprise Technologies 2, no. 4 (110) (2021): 38–47. http://dx.doi.org/10.15587/1729-4061.2021.229160.

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Qasim, Abbood Mahdi, Shyshatskyi Andrii, Prokopenko Yevgen, et al. "Development of estimation and forecasting method in intelligent decision support systems." Eastern-European Journal of Enterprise Technologies 3, no. 9 (111) (2021): 51–62. https://doi.org/10.15587/1729-4061.2021.232718.

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The method of estimation and forecasting in intelligent decision support systems was developed. The essence of the method is the analysis of the current state of the object and short-term forecasting of the object state. Objective and complete analysis is achieved by using improved fuzzy temporal models of the object state and an improved procedure for processing the original data under uncertainty. Also, the possibility of objective and complete analysis is achieved through an improved procedure for forecasting the object state and an improved procedure for learning evolving artificial neural

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Дисертації з теми "Forecasting of the state of systems"

Li, Ying. "Forecasting Long Term Highway Staffing Requirements for State Transportation Agencies." UKnowledge, 2016. http://uknowledge.uky.edu/ce_etds/42.

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The transportation system is vital to the nation’s economic growth and stability, as it provides mobility for commuters while supporting the United States’ ability to compete in an increasingly competitive global economy. State Transportation Agencies across the country continue to face many challenges to repair and enhance highway infrastructure to meet the rapid increasing transportation needs. One of these challenges is maintaining an adequate and efficient agency staff. In order to effectively plan for future staffing levels, State Transportation Agencies need a method for forecasting long

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Quinn, Niall. "Forecasting of ocean state in a complex estuarine environment : the Solent-Southampton Water Estuarine System." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/359671/.

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Coastal flooding is a natural hazard causing devastation to many regions throughout the world, induced by the coincidence of high spring tides, large storm surges and waves. To reduce the risk posed by coastal inundation, warning systems have been developed to enable preparations to an expected threat. Although current operational predictions provide invaluable warnings, uncertainty in model formulations and input datasets, can lead to errors in forecasts. In order to provide coastal managers with the best possible information with which to make decisions, recent research has begun to focus on

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Steed, Chad A. "Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis." Diss., Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-10252008-080937.

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Shafiei, Mehdi. "Distribution network state estimation, time dependency and fault detection." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/124659/2/Mehdi_Shafiei_Thesis.pdf.

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In this research work, the combination of three novel approaches is established to estimate the states of three-phase balanced and unbalanced distribution networks and using the developed methods for high impedance fault detection. The effectiveness of the developed methods are proposing a fast real-time state estimator with a low number of measurement devices, avoiding bad data detection in state estimation, and dynamically updating fault current thresholds to detect high impedance faults in the distribution networks.

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Mansoor, Shaheer. "System Surveillance." Thesis, Linköpings universitet, Statistik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-98189.

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In recent years, trade activity in stock markets has increased substantially. This is mainly attributed to the development of powerful computers and intranets connecting traders to markets across the globe. The trades have to be carried out almost instantaneously and the systems in place that handle trades are burdened with millions of transactions a day, several thousand a minute. With increasing transactions the time to execute a single trade increases, and this can be seen as an impact on the performance. There is a need to model the performance of these systems and provide forecasts to giv

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Paramygin, Vladimir A. "Towards a real-time 24/7 storm surge, inundation and 3-D baroclinic circulation forecasting system for the state of Florida." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024729.

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Chou, Shuo-Ju. "A conceptual methodology for assessing acquisition requirements robustness against technology uncertainties." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39467.

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The lack of system capability, budget, and schedule robustness against technology performance and development uncertainties has led to major setbacks in recent acquisition programs. This lack of robustness stems from the fact that immature technologies have uncertainties in their expected performance and development times and costs that translate to variations in system effectiveness and program development budget and schedule requirements. As such, the objective of this thesis is to formulate an assessment process that better informs acquisition decision-makers of program requirements robus

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Lewe, Jung-Ho. "An Integrated Decision-Making Framework for Transportation Architectures: Application to Aviation Systems Design." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-04132005-204114/unrestricted/Jung-Ho%5FLewe%5F200505%5Fphd.pdf.

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Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2005.<br>Amy R. Pritchett, Committee Member ; Moore, Mark D., Committee Member ; Wilhite, Alan, Committee Member ; Schrage, Daniel P., Committee Chair ; Mavris, Dimitri N., Committee Co-Chair ; DeLaurentis, Daniel A., Committee Member. Vita. Includes bibliographical references.

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Key, Peter Bernard. "Bayesian forecasting with state space models." Thesis, Royal Holloway, University of London, 1986. http://repository.royalholloway.ac.uk/items/87d86ed9-b2e7-4393-9fef-696f8c0cd147/1/.

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This thesis explores the use of State-Space models in Time Series Analysis and Forecasting, with particular reference to the Dynamic Linear Model (DLM) introduced by Harrison and Stevens. Concepts from Control Theory are employed, especially those of observability, controllability and filtering, together with Bayesian inference and classical forecasting methodology. First, properties of state-space models which depart from the usual Gaussian assumptions are examined, and the predictive consequences of such models are developed. These models can lead to new phenomena, for example it is shown th

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Fischer, Ulrike. "Forecasting in Database Systems." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-133281.

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Time series forecasting is a fundamental prerequisite for decision-making processes and crucial in a number of domains such as production planning and energy load balancing. In the past, forecasting was often performed by statistical experts in dedicated software environments outside of current database systems. However, forecasts are increasingly required by non-expert users or have to be computed fully automatically without any human intervention. Furthermore, we can observe an ever increasing data volume and the need for accurate and timely forecasts over large multi-dimensional data sets.

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Книги з теми "Forecasting of the state of systems"

Brown Do Coutto Filho, Milton. Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4.

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Ray, Ranjan. State-level food demand in India: Some evidence on rank-three demand systems. Centre for Development Economics, Delhi School of Economics, 1998.

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Putman, Stephen H. Integrated transportation and land use forecasting: Sensitivity tests of alternative model systems configuration. U.S. Dept. of Transportation, Federal Highway Administration, Federal Transit Administration, Assistant Secretary for Transportation Policy, 2001.

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Senn, Larry. Summary report: Washington State road weather information systems. Washington State Dept. of Transportation, 2005.

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Orlova, Ekaterina. Econometric methodology of systems research. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1096421.

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The textbook presents the methodology of a comprehensive econometric approach to the analysis, modeling and forecasting of multi-level economic systems, which includes the construction and analysis of econometric models, the study of the possibility of their practical application to identify and justify economic patterns, forecasting the consequences of management decisions. Meets the requirements of the federal state educational standards of higher education of the latest generation. It is intended for bachelors, undergraduates and postgraduates of economic fields. It will also be useful for

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United States. National Oceanic and Atmospheric Administration, ed. Advanced weather interactive processing systems (AWIPS). U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, 1994.

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System, Montana Career Information, and Montana State Occupational Information Coordinating Committee., eds. Montana State Occupational Information Coordinating Committee [and] Career Information System: [newsletter]. Montana SOICC/MCIS, 1994.

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Office, General Accounting. Weather forecasting: Systems architecture needed for national weather service modernization : report to Congressional requesters. The Office, 1994.

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de, Jong Gerard, EXPEDITE Consortium, RAND Europe, Rand Corporation, and European Commission. Directorate-General for Energy and Transport., eds. EXPEDITE: EXpert-system based PrEdictions of demand for internal transport in Europe. RAND, 2003.

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Garcia, Philip. The California State University System: Projections of enrollment demand, 1990 to 2005. California State University, Office of the Chancellor, Division of Analytic Studies, 1991.

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Частини книг з теми "Forecasting of the state of systems"

Brown Do Coutto Filho, Milton. "Observation Capability of Measuring Systems." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_4.

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Brown Do Coutto Filho, Milton. "Forecasting-Aided State Estimation." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_7.

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Brown Do Coutto Filho, Milton. "Static State Estimation." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_2.

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Paulescu, Marius, Eugenia Paulescu, Paul Gravila, and Viorel Badescu. "State of the Sky Assessment." In Weather Modeling and Forecasting of PV Systems Operation. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4649-0_3.

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Brown Do Coutto Filho, Milton. "Phasor-Aided State Estimation." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_8.

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von Bülow, Friedrich. "Battery System State of Health Forecasting." In AutoUni – Schriftenreihe. Springer Fachmedien Wiesbaden, 2024. http://dx.doi.org/10.1007/978-3-658-43188-4_8.

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Doan, Nguyen Anh Khoa, Wolfgang Polifke, and Luca Magri. "Physics-Informed Echo State Networks for Chaotic Systems Forecasting." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22747-0_15.

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Brown Do Coutto Filho, Milton. "Power Network Branch Parameters." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_9.

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Brown Do Coutto Filho, Milton. "Criticality Analysis." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_5.

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Brown Do Coutto Filho, Milton. "Closure." In Power System State Estimation and Forecasting. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63288-4_10.

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Тези доповідей конференцій з теми "Forecasting of the state of systems"

Polaki, Ramya, Keshavagari Smithin Reddy, V. Sulochana, Gundala Pallavi, and Prasanna Kumar R. "Enhancing House Price Forecasting with State-Action-Reward-State-Action Algorithm and Deep Q-Learning." In 2024 4th International Conference on Sustainable Expert Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63445.2024.10763162.

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Thorat, Bhagwan Dinkar, and Sunita A. Jahirabadkar. "Deep Learning Methods for Fertilizer Forecasting: Review of State of The Art." In 2024 International Conference on Intelligent Systems and Advanced Applications (ICISAA). IEEE, 2024. https://doi.org/10.1109/icisaa62385.2024.10828751.

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Guo, Jiahui, and Bingqing Nie. "A Forecasting-Aided State Estimator Based on PSO-ELM for Active Distribution Networks." In 2024 International Conference on Artificial Intelligence and Power Systems (AIPS). IEEE, 2024. http://dx.doi.org/10.1109/aips64124.2024.00114.

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Verdone, Alessio, Simone Scardapane, Rodolfo Araneo, and Massimo Panella. "On the Exploration of Graph State-Space Models for Spatio-Temporal Renewable Energy Forecasting." In 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE, 2024. http://dx.doi.org/10.1109/eeeic/icpseurope61470.2024.10751171.

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Chen, Shanmou, Jianxia Wu, Chaolun Zhang, et al. "Robust Power System Forecasting-Aided State Estimation Based on Generalized Loss Cubature Kalman Filter." In 2024 Boao New Power System International Forum - Power System and New Energy Technology Innovation Forum (NPSIF). IEEE, 2024. https://doi.org/10.1109/npsif64134.2024.10883605.

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Panda, Subhra Prakash, Bidush Kumar Sahoo, Bibudhendu Pati, Tanmay Mukherjee, and Sujit Bebortta. "State-of-the-Art Analysis of Stock Market Forecasting: Techniques, Challenges, and Future Scopes." In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES). IEEE, 2024. https://doi.org/10.1109/scopes64467.2024.10990386.

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Yu, Yue, and Yue Wang. "Enabling Forecasting-aided State Estimation in Active Distribution Networks via GRformer-Driven Pseudo-Measurement Modeling." In 2024 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE, 2024. https://doi.org/10.1109/icpsasia61913.2024.10761262.

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Zhang, Pengbin, Hongrui Wang, Kunpeng Xing, and Mingzhe Yuan. "Natural Gas Load Forecasting Based on Multi-Stage Model Identification." In 2024 IEEE 14th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE, 2024. http://dx.doi.org/10.1109/cyber63482.2024.10749400.

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Muralidhar, Nikhil, Sathappan Muthiah, and Naren Ramakrishnan. "DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/441.

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Multivariate time series forecasting is an important task in state forecasting for cyber-physical systems (CPS). State forecasting in CPS is imperative for optimal planning of system energy utility and understanding normal operational characteristics of the system thus enabling anomaly detection. Forecasting models can also be used to identify sub-optimal or worn out components and are thereby useful for overall system monitoring. Most existing work only performs single step forecasting but in CPS it is imperative to forecast the next sequence of system states (i.e curve forecasting). In this

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Satyamsetti, Vijayakrishna, Andreas Michealides, and Antonis Hadjiantonis. "Forecasting on solid state transformer applications." In 2017 International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2017. http://dx.doi.org/10.1109/iss1.2017.8389425.

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Звіти організацій з теми "Forecasting of the state of systems"

Yu, Shu-Ling, and Jon Fricker. A Highway Travel Information System: Forecasting and Publicizing Delays in the Indiana State Highway Network. Purdue University, 2004. http://dx.doi.org/10.5703/1288284313126.

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Capotondi, Antonietta, Victoria J. Coles, Sophie Clayton, et al. Daily to decadal ecological forecasting along North American coastlines. Woods Hole Oceangraphic Institution, 2024. https://doi.org/10.1575/1912/70991.

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Coastal areas share unique intersections of large-scale climate variability and local hydrology, wetland, benthic and pelagic ecosystems, and anthropogenic pressures. Forecasting of harmful environmental conditions for planning, adaptation, and mitigation purposes is both complex and urgently needed. Ecological forecasting is the qualitative or quantitative projection of biogeochemical, organismal or ecosystem state variables and their drivers on timescales that can range from “now” to decades from now. Estimating hypoxia in Chesapeake Bay today, predicting acidity conditions in the Northeast

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Verma, Rajat, Hao Luo, Saloni Deodhar, et al. Forecasting Shifts in Hoosiers’ Travel Demand and Behavior. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317685.

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The changing landscape of transportation technology and traveler behavior, accelerated by recent events like COVID-19, has led to significant shifts in travel demand and vehicle miles traveled in Indiana. This study seeks to understand the long-term implications of these changes and their potential impact on passenger, freight, and micro-mobility movements across the state. To achieve this objective, this project focused on forecasting future transportation demand conditions and carrying out long-range scenario planning by accomplishing four tasks: forecasting travel demand shifts based on loc

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BARKHATOV, NIKOLAY, and SERGEY REVUNOV. A software-computational neural network tool for predicting the electromagnetic state of the polar magnetosphere, taking into account the process that simulates its slow loading by the kinetic energy of the solar wind. SIB-Expertise, 2021. http://dx.doi.org/10.12731/er0519.07122021.

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The auroral activity indices AU, AL, AE, introduced into geophysics at the beginning of the space era, although they have certain drawbacks, are still widely used to monitor geomagnetic activity at high latitudes. The AU index reflects the intensity of the eastern electric jet, while the AL index is determined by the intensity of the western electric jet. There are many regression relationships linking the indices of magnetic activity with a wide range of phenomena observed in the Earth's magnetosphere and atmosphere. These relationships determine the importance of monitoring and predicting ge

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Fu, Gongkang, and Gabriel Bryk. BrM Quantity-Based Bridge Element Deterioration/Improvement Modeling and Software Tools. Illinois Center for Transportation, 2024. http://dx.doi.org/10.36501/0197-9191/24-005.

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This study reviewed the state of the art and practice in bridge element deterioration / improvement modeling. It also developed a new and practical method for such modeling using element quantities in BrM inspection records along with bridge age. For reliable forecasting, this method uses these quantities directly to determine transition probability matrices (TPMs). The example TPMs were found age-dependent for the do-nothing case. Results show that this approach is effective in forecasting the bridge element life. Condition improvement TPMs were also similarly derived from the quantity evolut

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Shifley, Stephen R. A generalized system of models forecasting Central States tree growth. U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, 1987. http://dx.doi.org/10.2737/nc-rp-279.

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Owyang, Michael T., Jeremy M. Piger, and Howard J. Wall. Forecasting National Recessions Using State Level Data. Federal Reserve Bank of St. Louis, 2012. http://dx.doi.org/10.20955/wp.2012.013.

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Monteiro, C., R. Bessa, V. Miranda, et al. Wind power forecasting : state-of-the-art 2009. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/968212.

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Fricker, Jon, and Sunil Saha. Traffic Volume Forecasting Methods for Rural State Highways. Purdue University, 1986. http://dx.doi.org/10.5703/1288284314120.

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Schling, Maja, Roberto Guerrero Compeán, Nicolás Pazos, Allison Bailey, Katie Arkema, and Mary Ruckelshaus. The Economic Impact of Sargassum: Evidence from the Mexican Coast. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004470.

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This paper assesses the local economic impact of pelagic Sargassum seaweed washed ashore in tourism-heavy coastal zones in the Mexican State of Quintana Roo. The study relies on a carefully designed Geographic Information Systems (GIS) dataset of monthly observations from 2016 to 2019 for 157 beach segments. The dataset comprises an innovate measure of Sargassum seaweed presence, remotely sensed nighttime light intensity as a proxy of economic growth, as well as information on key infrastructure, sociodemographic and beach characteristics. We apply a fixed-effects regression model that control

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