Log in

Relevant bibliographies by topics / Forecasting of the state of systems / Journal articles

To see the other types of publications on this topic, follow the link: Forecasting of the state of systems.

Journal articles on the topic 'Forecasting of the state of systems'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Forecasting of the state of systems.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

2

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

3

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

4

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

6

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

8

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

9

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

10

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

11

Geetha, Sreenath Jayakumar, Saikat Chakrabarti, Ketan Rajawat, and Vladimir Terzija. "An Asynchronous Decentralized Forecasting-Aided State Estimator for Power Systems." IEEE Transactions on Power Systems 34, no. 4 (2019): 3059–68. http://dx.doi.org/10.1109/tpwrs.2019.2896601.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Mahdi, Qasim Abbood, Andrii Shyshatskyi, Yevgen Prokopenko, 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. http://dx.doi.org/10.15587/1729-4061.2021.232718.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

13

Paulescu, Marius, Oana Mares, Ciprian Dughir, and Eugenia Paulescu. "Nowcasting the Output Power of PV Systems." E3S Web of Conferences 61 (2018): 00010. http://dx.doi.org/10.1051/e3sconf/20186100010.

Full text

Abstract:

This paper presents an innovative procedure for nowcasting the energy production of PV systems. The procedure is relayed on a new version of two-state model for forecasting solar irradiance at ground level and a simplified description of the PV system. The results of testing the proposed procedure against on field measured data are discussed. Generally, the proposed procedure demonstrates a better performance than the main competitor based on ARIMA forecasting of the clearness index.

APA, Harvard, Vancouver, ISO, and other styles

14

Magnusson, L., E. Källén, and J. Nycander. "Initial state perturbations in ensemble forecasting." Nonlinear Processes in Geophysics 15, no. 5 (2008): 751–59. http://dx.doi.org/10.5194/npg-15-751-2008.

Full text

Abstract:

Abstract. Due to the chaotic nature of atmospheric dynamics, numerical weather prediction systems are sensitive to errors in the initial conditions. To estimate the forecast uncertainty, forecast centres produce ensemble forecasts based on perturbed initial conditions. How to optimally perturb the initial conditions remains an open question and different methods are in use. One is the singular vector (SV) method, adapted by ECMWF, and another is the breeding vector (BV) method (previously used by NCEP). In this study we compare the two methods with a modified version of breeding vectors in a l

APA, Harvard, Vancouver, ISO, and other styles

15

Wang, Jianzhou, Chunying Wu, and Tong Niu. "A Novel System for Wind Speed Forecasting Based on Multi-Objective Optimization and Echo State Network." Sustainability 11, no. 2 (2019): 526. http://dx.doi.org/10.3390/su11020526.

Full text

Abstract:

Given the rapid development and wide application of wind energy, reliable and stable wind speed forecasting is of great significance in keeping the stability and security of wind power systems. However, accurate wind speed forecasting remains a great challenge due to its inherent randomness and intermittency. Most previous researches merely devote to improving the forecasting accuracy or stability while ignoring the equal significance of improving the two aspects in application. Therefore, this paper proposes a novel hybrid forecasting system containing the modules of a modified data preproces

APA, Harvard, Vancouver, ISO, and other styles

16

Kumar, Rakesh, Richa Goel, Neeru Sidana, et al. "Enhancing climate forecasting with AI: Current state and future prospect." F1000Research 13 (September 26, 2024): 1094. http://dx.doi.org/10.12688/f1000research.154498.1.

Full text

Abstract:

Background The escalating impact of climate change underscores the critical need for advanced and sustainable climate forecasting techniques. This review examines the current state and future prospects of leveraging Artificial Intelligence (AI) for climate forecasting, focusing on enhancing accuracy and identifying complex patterns in large datasets. Methods A systematic bibliometric methodology was employed, analyzing peer-reviewed literature from the past two decades. The study screened 455 articles from Scopus and Web of Science databases using specific keywords related to AI and weather fo

APA, Harvard, Vancouver, ISO, and other styles

17

Hayes, Barry Patrick, and Milan Prodanovic. "State Forecasting and Operational Planning for Distribution Network Energy Management Systems." IEEE Transactions on Smart Grid 7, no. 2 (2016): 1002–11. http://dx.doi.org/10.1109/tsg.2015.2489700.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Knyazev, Nikita, Anton Pershin, Anna Golovkina, and Vladimir Kozynchenko. "Forecasting the state of complex network systems using machine learning methods." Cybernetics and Physics, Volume 12, 2023, Number 2 (September 30, 2023): 129–35. http://dx.doi.org/10.35470/2226-4116-2023-12-2-129-135.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Umgiesser, Georg, Marco Bajo, Christian Ferrarin, et al. "The prediction of floods in Venice: methods, models and uncertainty (review article)." Natural Hazards and Earth System Sciences 21, no. 8 (2021): 2679–704. http://dx.doi.org/10.5194/nhess-21-2679-2021.

Full text

Abstract:

Abstract. This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to

APA, Harvard, Vancouver, ISO, and other styles

20

Lees, Matthew J. "Data-based mechanistic modelling and forecasting of hydrological systems." Journal of Hydroinformatics 2, no. 1 (2000): 15–34. http://dx.doi.org/10.2166/hydro.2000.0003.

Full text

Abstract:

The paper presents a data-driven approach to the modelling and forecasting of hydrological systems based on nonlinear time-series analysis. Time varying parameters are estimated using a combined Kalman filter and fixed-interval-smoother, and state-dependent parameter relations are identified leading to nonlinear extensions to common time-series models such as the autoregressive exogenous (ARX) and general transfer function (TF). This nonlinear time-series technique is used as part of a data-based mechanistic modelling methodology where models are objectively identified from the data, but are o

APA, Harvard, Vancouver, ISO, and other styles

21

Alomar, Miquel L., Vincent Canals, Nicolas Perez-Mora, Víctor Martínez-Moll, and Josep L. Rosselló. "FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting." Computational Intelligence and Neuroscience 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/3917892.

Full text

Abstract:

Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC) has arisen as a strategic technique to design recurrent neural networks (RNNs) with simple learning capabilities. In this work, we show a new approach to implement RC systems with digital gates. The proposed method is based on the use of probabilistic computing concepts to reduce the hardware required to implement different arithmetic operations.

APA, Harvard, Vancouver, ISO, and other styles

22

Dan, Jingpei, Wenbo Guo, Weiren Shi, Bin Fang, and Tingping Zhang. "Deterministic Echo State Networks Based Stock Price Forecasting." Abstract and Applied Analysis 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/137148.

Full text

Abstract:

Echo state networks (ESNs), as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock pri

APA, Harvard, Vancouver, ISO, and other styles

23

Liu, Wen-Jie, Yu-Ting Bai, Xue-Bo Jin, Ting-Li Su, and Jian-Lei Kong. "Adaptive Broad Echo State Network for Nonstationary Time Series Forecasting." Mathematics 10, no. 17 (2022): 3188. http://dx.doi.org/10.3390/math10173188.

Full text

Abstract:

Time series forecasting provides a vital basis for the control and management of various systems. The time series data in the real world are usually strongly nonstationary and nonlinear, which increases the difficulty of reliable forecasting. To fully utilize the learning capability of machine learning in time series forecasting, an adaptive broad echo state network (ABESN) is proposed in this paper. Firstly, the broad learning system (BLS) is used as a framework, and the reservoir pools in the echo state network (ESN) are introduced to form the broad echo state network (BESN). Secondly, for t

APA, Harvard, Vancouver, ISO, and other styles

24

Sokolova, Ekaterina, and Andrey Sokolov. "The problem of forecasting emergency situations of technical objects." MATEC Web of Conferences 298 (2019): 00052. http://dx.doi.org/10.1051/matecconf/201929800052.

Full text

Abstract:

The problem of edge state forecasting has a wide field of application. To begin with, it arises when one develops a technical diagnostics system as the problem of forecasting emergency situations of technical objects. When the ecological system is concerned it appears as the problem of forecasting unfavorable development of the ecological situation. In case of investment analysis it evolves as the problem of forecasting the risks of no profit. In medical diagnostic automated systems it is the forecasting disease progression and transition.

APA, Harvard, Vancouver, ISO, and other styles

25

Chen, Liang, and Jijun Zhang. "A Forecast Model of City Natural Gas Daily Load Based on Data Mining." Scientific Programming 2022 (March 11, 2022): 1–14. http://dx.doi.org/10.1155/2022/1562544.

Full text

Abstract:

Data mining technology is more and more widely used in the daily load forecasting of natural gas systems. It is still difficult to carry out high-precision, timely intraday load forecasting and intraday load dynamic characteristics clustering for natural gas systems. Based on data mining technology, this paper proposes a stable intraday load forecasting method for the natural gas flow state-space model. The load sensitivity under the current operating conditions of the system is obtained by calculation; the sample space of the state space is established through data processing; the partitions

APA, Harvard, Vancouver, ISO, and other styles

26

Gou, Yuanfang, Cheng Guo, and Risheng Qin. "Ultra short term power load forecasting based on the fusion of Seq2Seq BiLSTM and multi head attention mechanism." PLOS ONE 19, no. 3 (2024): e0299632. http://dx.doi.org/10.1371/journal.pone.0299632.

Full text

Abstract:

Ultra-short-term power load forecasting is beneficial to improve the economic efficiency of power systems and ensure the safe and stable operation of power grids. As the volatility and randomness of loads in power systems, make it difficult to achieve accurate and reliable power load forecasting, a sequence-to-sequence based learning framework is proposed to learn feature information in different dimensions synchronously. Convolutional Neural Networks(CNN) Combined with Bidirectional Long Short Term Memory(BiLSTM) Networks is constructed in the encoder to extract the correlated timing features

APA, Harvard, Vancouver, ISO, and other styles

27

Panasenko, Natalia, and Alexander Sukhinov. "Forecasting coastal systems based on satellite images." E3S Web of Conferences 592 (2024): 06022. http://dx.doi.org/10.1051/e3sconf/202459206022.

Full text

Abstract:

In the Southern region of Russia, biotic, biological and anthropogenic factors are constantly in effect. To simulate various options for the development of biological and geophysical processes in marine and coastal systems, there is a need to develop and create non-stationary spatially heterogeneous interconnected mathematical models. For practical application of the models, real input data (boundary and initial conditions) and information on the initial parameters are required. This information can be obtained using spacecraft. This paper presents the developed software and algorithmic tools

APA, Harvard, Vancouver, ISO, and other styles

28

Кладченко, Ірина. "ПРОГНОЗУВАННЯ ТРАЄКТОРІЇ НАЦІОНАЛЬНОГО ЕКОНОМІЧНОГО РОЗВИТКУ МЕТОДАМИ ГАРМОНІЙНОГО І СПЕКТРАЛЬНОГО АНАЛІЗУ". Economical 1, № 1(22) (2020): 115–31. http://dx.doi.org/10.31474/1680-0044-2020-1(22)-115-131.

Full text

Abstract:

Improving of the methodological tools for the national economies behavior’s forecasting in the context of increasing the validity and analytical characteristics of state economic strategies in conditions of high volatility, lack of trend stability and non-stationary dynamics of external and internal socio-economic processes by implementing interdisciplinary methods of Fourier analysis and their adaptation to the specifics of the socio-economic systems’ functioning and development. Methodology. The forecasting’s targeting as an important independent stage in the process of analytical assessment

APA, Harvard, Vancouver, ISO, and other styles

29

Niu, Dongxiao, Ling Ji, Yongli Wang, and Da Liu. "Echo state network with wavelet in load forecasting." Kybernetes 41, no. 10 (2012): 1557–70. http://dx.doi.org/10.1108/03684921211276747.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

MASHKOV, Oleg, Volodymyr PRYSIAZHNIY, and Tamara OVODENKO. "DIRECTIONS OF APPLICATION OF THE SYSTEMS APPROACH IN THE SYSTEM OF STATE MANAGEMENT OF ENVIRONMENTAL SAFETY USING AEROSPACE TECHNOLOGIES." Bulletin of the Taras Shevchenko National University of Kyiv. National security 2, no. 2 (2024): 17–24. https://doi.org/10.17721/3041-1912.2024/2-3/11.

Full text

Abstract:

Background. The topic of evaluating the application of a systemic approach in the system of state management of environmental security with the use of aerospace technologies became especially relevant for Ukrainian society with the beginning of the war, since military actions caused primary and transboundary impacts on the environment and natural resources and caused risks for ecosystems, the economy of Ukraine and beyond . Therefore, there is a need to join the European and world experience of assessing and restoring disturbed ecosystems by means of a systematic analysis of processes and phen

APA, Harvard, Vancouver, ISO, and other styles

31

Dezhi Li, Wilson Wang, and Fathy Ismail. "Fuzzy Neural Network Technique for System State Forecasting." IEEE Transactions on Cybernetics 43, no. 5 (2013): 1484–94. http://dx.doi.org/10.1109/tcyb.2013.2259229.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Yamashkin, Anatoliy, Stanislav Yamashkin, Vladimir Erofeev, and Anna Piksaykina. "Geodiagnostics of lithogydrogenic systems for forecasting exoggeodynamic processes." MATEC Web of Conferences 265 (2019): 03008. http://dx.doi.org/10.1051/matecconf/201926503008.

Full text

Abstract:

The landscape indication, based on the automated analysis of remote sensing data, is one of the key methods of research and mapping of lithohydrogene geosystems. The article describes a set of methods for effective detection of types of lithohydrogene systems, including a set of modules for identifying dynamic and invariant descriptors of the territory; assessment of geophysical diversity of landscapes; analysis of the geophysical shell through the calculation of the descriptors of the neighborhood; ensemble-analysis of remote sensing data for monitoring the state of geosystems and forecasting

APA, Harvard, Vancouver, ISO, and other styles

33

Khlaponin, Y. I., N. H. Qasim, and D. M. Tarasiuk. "FORECASTING THE STATE OF TELECOMMUNICATION NETWORKS USING QUANTILE AND LOGISTIC REGRESSION METHODS." Collection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University, no. 80 (2023): 91–97. http://dx.doi.org/10.17721/2519-481x/2023/80-10.

Full text

Abstract:

In today's modern world, the ubiquity of information technology has intertwined telecommunications systems with every facet of human life. It's challenging to fathom a world where you're disconnected from the "World Wide Web" or unable to exchange data instantly via the intricate web of modern mobile devices. The vitality of staying connected online cannot be overstated, and ensuring the smooth functioning of telecommunications systems is paramount. This paper delves into the pivotal task of predicting and managing the performance of these networks, employing quantile and logical regression te

APA, Harvard, Vancouver, ISO, and other styles

34

Casolaro, Angelo, Vincenzo Capone, Gennaro Iannuzzo, and Francesco Camastra. "Deep Learning for Time Series Forecasting: Advances and Open Problems." Information 14, no. 11 (2023): 598. http://dx.doi.org/10.3390/info14110598.

Full text

Abstract:

A time series is a sequence of time-ordered data, and it is generally used to describe how a phenomenon evolves over time. Time series forecasting, estimating future values of time series, allows the implementation of decision-making strategies. Deep learning, the currently leading field of machine learning, applied to time series forecasting can cope with complex and high-dimensional time series that cannot be usually handled by other machine learning techniques. The aim of the work is to provide a review of state-of-the-art deep learning architectures for time series forecasting, underline r

APA, Harvard, Vancouver, ISO, and other styles

35

Singh, Vijay Raj, Manoj V, Sunil Kumar GP, Dr Sheshappa S. N, and Prof Mr Byre Gowda B. K. "Equity Market Price Prediction Forecast and Analysis with Technical Indicators and Diversification Analysis Using Deep Learning Technique." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 4462–71. http://dx.doi.org/10.22214/ijraset.2023.51297.

Full text

Abstract:

Abstract: Many experts, analysts, and novice investors have found it challenging to predict valuations of shares. Investors are, in fact, quite interested in the field of price forecasting for equity study. Many investors are interested in understanding the future state of the equity market in order to make a smart and profitable investment. By giving helpful information like the equity market's future direction, good and effective equity market prediction systems assist traders, investors, and analysts. equity market price forecasting is a challenging undertaking that often necessitates inten

APA, Harvard, Vancouver, ISO, and other styles

36

Anafi, Nurin Fadhlina Mohd, Norzailawati Mohd Noor, and Hasti Widyasamratri. "A Systematic Review of Real-time Urban Flood Forecasting Model in Malaysia and Indonesia -Current Modelling and Challenge." Jurnal Planologi 20, no. 2 (2023): 150. http://dx.doi.org/10.30659/jpsa.v20i2.30765.

Full text

Abstract:

Several metropolitan areas in tropical Southeast Asia, mainly in Malaysia and Indonesia have lately been witnessing unprecedentedly severe flash floods owing to unexpected climate change. The fast water flooding has caused extraordinarily serious harm to urban populations and social facilities. In addition, urban Southeast Asia generally has insufficient capacity in drainage systems, complex land use patterns, and a largely susceptible population in confined urban regions. To lower the urban flood risk and strengthen the resilience of vulnerable urban populations, it has been of fundamental re

APA, Harvard, Vancouver, ISO, and other styles

37

NaitMalek, Youssef, Mehdi Najib, Mohamed Bakhouya, and Mohamed Essaaidi. "Embedded Real-time Battery State-of-Charge Forecasting in Micro-Grid Systems." Ecological Complexity 45 (January 2021): 100903. http://dx.doi.org/10.1016/j.ecocom.2020.100903.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Panasenko, N. D. "Forecasting the Coastal Systems State using Mathematical Modelling Based on Satellite Images." Computational Mathematics and Information Technologies 7, no. 4 (2024): 54–65. http://dx.doi.org/10.23947/2587-8999-2023-7-4-54-65.

Full text

Abstract:

Introduction. Coastal systems of Southern Russia are constantly exposed to biotic, abiotic and anthropogenic factors. In this regard, there is a need to develop non-stationary spatially inhomogeneous interconnected mathematical models that make it possible to reproduce various scenarios for the dynamics of biological and geochemical processes in coastal systems. There is also the problem of the practical use of mathematical modelling, namely its equipping with real input data (boundary, initial conditions, information about source functions). An operational source of ﬁeld information can be da

APA, Harvard, Vancouver, ISO, and other styles

39

Kozitsin, Viacheslav, Iurii Katser, and Dmitry Lakontsev. "Online Forecasting and Anomaly Detection Based on the ARIMA Model." Applied Sciences 11, no. 7 (2021): 3194. http://dx.doi.org/10.3390/app11073194.

Full text

Abstract:

Real-time diagnostics of complex technical systems such as power plants are critical to keep the system in its working state. An ideal diagnostic system must detect any fault in advance and predict the future state of the technical system, so predictive algorithms are used in the diagnostics. This paper proposes a novel, computationally simple algorithm based on the Auto-Regressive Integrated Moving Average model to solve anomaly detection and forecasting problems. The good performance of the proposed algorithm was confirmed in numerous numerical experiments for both anomaly detection and fore

APA, Harvard, Vancouver, ISO, and other styles

40

Henonin, Justine, Beniamino Russo, Ole Mark, and Philippe Gourbesville. "Real-time urban flood forecasting and modelling – a state of the art." Journal of Hydroinformatics 15, no. 3 (2013): 717–36. http://dx.doi.org/10.2166/hydro.2013.132.

Full text

Abstract:

All urban drainage networks are designed to manage a maximum rainfall. This situation implies an accepted flood risk for any greater rainfall event. This risk is often underestimated as factors such as city growth and climate change are ignored. But even major structural changes cannot guarantee that urban drainage networks would cope with all future rain events. Thus, being able to forecast urban flooding in real time is one of the main issues of integrated flood risk management. Runoff and hydraulic models can be essential elements of flood forecast systems, as an active part of the system o

APA, Harvard, Vancouver, ISO, and other styles

41

Chitwatkulsiri, Detchphol, and Hitoshi Miyamoto. "Real-Time Urban Flood Forecasting Systems for Southeast Asia—A Review of Present Modelling and Its Future Prospects." Water 15, no. 1 (2023): 178. http://dx.doi.org/10.3390/w15010178.

Full text

Abstract:

Many urban areas in tropical Southeast Asia, e.g., Bangkok in Thailand, have recently been experiencing unprecedentedly intense flash floods due to climate change. The rapid flood inundation has caused extremely severe damage to urban residents and social infrastructures. In addition, urban Southeast Asia usually has inadequate capacities in drainage systems, complicated land use patterns, and a large vulnerable population in limited urban areas. To reduce the urban flood risk and enhance the resilience of vulnerable urban communities, it has been of essential importance to develop real-time u

APA, Harvard, Vancouver, ISO, and other styles

42

Trierweiler Ribeiro, Gabriel, João Guilherme Sauer, Naylene Fraccanabbia, Viviana Cocco Mariani, and Leandro dos Santos Coelho. "Bayesian Optimized Echo State Network Applied to Short-Term Load Forecasting." Energies 13, no. 9 (2020): 2390. http://dx.doi.org/10.3390/en13092390.

Full text

Abstract:

Load forecasting impacts directly financial returns and information in electrical systems planning. A promising approach to load forecasting is the Echo State Network (ESN), a recurrent neural network for the processing of temporal dependencies. The low computational cost and powerful performance of ESN make it widely used in a range of applications including forecasting tasks and nonlinear modeling. This paper presents a Bayesian optimization algorithm (BOA) of ESN hyperparameters in load forecasting with its main contributions including helping the selection of optimization algorithms for tu

APA, Harvard, Vancouver, ISO, and other styles

43

Jumaev, O. A., J. T. Nazarov, G. B. Makhmudov, M. T. Ismoilov, and M. F. Shermuradova. "Intelligent control systems using algorithms of the entropie potential method." Journal of Physics: Conference Series 2094, no. 2 (2021): 022030. http://dx.doi.org/10.1088/1742-6596/2094/2/022030.

Full text

Abstract:

Abstract As part of neural network systems, an artificial neural network can perform various functions like diagnostics of technological equipment, control of moving objects and technological processes, forecasting situations, as well as assessing the state and monitoring of technological processes.

APA, Harvard, Vancouver, ISO, and other styles

44

Lagos, Ana, Joaquín E. Caicedo, Gustavo Coria, et al. "State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems." Energies 15, no. 18 (2022): 6545. http://dx.doi.org/10.3390/en15186545.

Full text

Abstract:

The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting models for wind turbines located in different segments of power systems, i.e., in large wind farms, distributed generation, microgrids, and micro-wind turbines installed in residences and buildings. This review c

APA, Harvard, Vancouver, ISO, and other styles

45

Travieso-González, Carlos M., Fidel Cabrera-Quintero, Alejandro Piñán-Roescher, and Sergio Celada-Bernal. "A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used." Applied Sciences 14, no. 13 (2024): 5605. http://dx.doi.org/10.3390/app14135605.

Full text

Abstract:

The increasing penetration of solar energy into the grid has led to management difficulties that require high accuracy forecasting systems. New techniques and approaches are emerging worldwide every year to improve the accuracy of solar power forecasting models and reduce uncertainty in predictions. This article aims to evaluate and compare various solar power forecasting methods based on their characteristics and performance using imagery. To achieve this goal, this article presents an updated analysis of diverse research, which is classified in terms of the technologies and methodologies app

APA, Harvard, Vancouver, ISO, and other styles

46

Sun, Guang, Jingjing Lin, Chen Yang, et al. "Stock Price Forecasting: An Echo State Network Approach." Computer Systems Science and Engineering 36, no. 3 (2021): 509–20. http://dx.doi.org/10.32604/csse.2021.014189.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Samkharadze, R., and L. Gachechiladze. "CONTROL PROBLEMS IN POWER SYSTEMS AND EXPERT SYSTEMS." Slovak international scientific journal, no. 93 (March 12, 2025): 9–13. https://doi.org/10.5281/zenodo.15011064.

Full text

Abstract:

The article offers an overview and analysis of energy system control problems. It considers the current state and prospects for the creation and use of expert systems for power system control and substantiates the necessity of using expert systems for multi-criteria control of power systems' normal daily regimes. It is shown that the scope of application of expert systems in the energy sector is quite wide: planning of power system modes, control and control of electric power systems, restoration of power supply after an accident, identifying locations of faults in the power grid, analysis of

APA, Harvard, Vancouver, ISO, and other styles

48

Areej, Adnan Abed, Repilo Iurii, Zhyvotovskyi Ruslan, et al. "Improvement of the method of estimation and forecasting of the state of the monitoring object in intelligent decision support systems." Eastern-European Journal of Enterprise Technologies 4, no. 3 (112) (2021): 43–55. https://doi.org/10.15587/1729-4061.2021.237996.

Full text

Abstract:

In order to objectively and completely analyze the state of the monitored object with the required level of efficiency, the method for estimating and forecasting the state of the monitored object in intelligent decision support systems was improved. The essence of the method is to provide an analysis of the current state of the monitored object and short-term forecasting of the state of the monitored object. Objective and complete analysis is achieved using advanced fuzzy temporal models of the object state, taking into account the type of uncertainty and noise of initial data. The novelty of

APA, Harvard, Vancouver, ISO, and other styles

49

Clemente, Alfredo V., Alessandro Nocente, and Massimiliano Ruocco. "Global Transformer Architecture for Indoor Room Temperature Forecasting." Journal of Physics: Conference Series 2600, no. 2 (2023): 022018. http://dx.doi.org/10.1088/1742-6596/2600/2/022018.

Full text

Abstract:

Abstract A thorough regulation of building energy systems translates in relevant energy savings and in a better comfort for the occupants. Algorithms to predict the thermal state of a building on a certain time horizon with a good confidence are essential for the implementation of effective control systems. This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings, aiming at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Recent advancements in deep learning have enabled the development of m

APA, Harvard, Vancouver, ISO, and other styles

50

Plakhotnikov, D. P. "Methodology for Choosing Methods for Forecasting Time Series of Cyber-Physical Systems of Fuel and Energy Complex Enterprises." LETI Transactions on Electrical Engineering & Computer Science 15, no. 7 (2022): 20–27. http://dx.doi.org/10.32603/2071-8985-2022-15-7-20-27.

Full text

Abstract:

At the moment, many time series forecasting models have been created. The initial data generated during the operation of cyber-physical systems can be used to predict the future state of the system. The article presents methods for obtaining and processing data on the parameters of cyber-physical systems, their cleaning and building a predictive model for different methods. The methods are compared in terms of the quality of the forecast and the duration of the model building. As a result, the most rational methods for forecasting the time series of cyber-physical systems depending on the pred

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!