Relevant bibliographies by topics / Social change – Forecasting / Journal articles

Journal articles on the topic 'Social change – Forecasting'

To see the other types of publications on this topic, follow the link: Social change – Forecasting.
Author: Grafiati
Published: 26 July 2024
Last updated: 27 July 2024

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 'Social change – Forecasting.'

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

Smith, Herbert L. "The social forecasting industry." Climatic Change 11, no. 1-2 (1987): 35–60. http://dx.doi.org/10.1007/bf00138794.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Clive Simmonds, W. H. "Forecasting, social change, and futures in Canada." Technological Forecasting and Social Change 33, no. 4 (July 1988): 297–98. http://dx.doi.org/10.1016/0040-1625(88)90026-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Berk, Richard A., and Thomas F. Cooley. "Errors in forecasting social phenomena." Climatic Change 11, no. 1-2 (1987): 247–65. http://dx.doi.org/10.1007/bf00138803.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Graham, Gary, Anita Greenhill, and Vic Callaghan. "Technological Forecasting and Social Change Special Section: Creative prototyping." Technological Forecasting and Social Change 84 (May 2014): 1–4. http://dx.doi.org/10.1016/j.techfore.2013.11.007.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Ashraf, Rohail, Muhammad Asif Khan, Rafique Ahmed Khuhro, and Zeeshan Ahmed Bhatti. "Knowledge creation dynamics of technological forecasting and social change special issues." Technological Forecasting and Social Change 180 (July 2022): 121663. http://dx.doi.org/10.1016/j.techfore.2022.121663.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Phillips, Fred. "How to publish your research in Technological Forecasting & Social Change." Technological Forecasting and Social Change 146 (September 2019): 488–90. http://dx.doi.org/10.1016/j.techfore.2019.05.022.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Savin, Ivan. "Evolution and recombination of topics in Technological Forecasting and Social Change." Technological Forecasting and Social Change 194 (September 2023): 122723. http://dx.doi.org/10.1016/j.techfore.2023.122723.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Bowonder, B., B. Muralidharan, and T. Miyake. "Forecasting technological change: insights from theories of evolution." Interdisciplinary Science Reviews 24, no. 4 (April 1999): 275–88. http://dx.doi.org/10.1179/030801899678948.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Solodov, S. V., I. B. Mamai, and S. V. Pronichkin. "Framing regional innovation and technology policies for transformative change." IOP Conference Series: Earth and Environmental Science 981, no. 2 (February 1, 2022): 022007. http://dx.doi.org/10.1088/1755-1315/981/2/022007.

Full text
Abstract:
Abstract The current state of social and economic development of regions requires new approaches to increasing the efficiency of their activities, and above all scientific approaches to forecasting, as one of the main components of the strategy of transformative changes. It is proposed to use an architecture based on neuro-fuzzy networks for forecasting regional development, which is characterized by a high learning rate due to the linear dependence of outputs on adjustable weights. Scientific and methodological approaches are developed to determine the global minimum of the learning criterion, taking into account the decision rules “if-then”.
APA, Harvard, Vancouver, ISO, and other styles
10

Salomon, Ilan. "Technological change and social forecasting: the case of telecommuting as a travel substitute." Transportation Research Part C: Emerging Technologies 6, no. 1-2 (February 1998): 17–45. http://dx.doi.org/10.1016/s0968-090x(98)00006-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
11

Phillips, Fred, and Hal Linstone. "Key ideas from a 25-year collaboration at technological forecasting & social change." Technological Forecasting and Social Change 105 (April 2016): 158–66. http://dx.doi.org/10.1016/j.techfore.2016.01.007.

Full text
APA, Harvard, Vancouver, ISO, and other styles
12

Redaktion, TATuP. "Technological Forecasting and Social Change. Special Issue: "Technology Assessment: The End of OTA"." TATuP - Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 6, no. 2 (June 1, 1997): 47–48. http://dx.doi.org/10.14512/tatup.6.2.47.

Full text
APA, Harvard, Vancouver, ISO, and other styles
13

Lu, Ning, and Ying Liu. "A Research into Probabilistic Electricity Load Prediction Based on Demand Response Feature under Smart Grid Environment." Applied Mechanics and Materials 380-384 (August 2013): 3098–102. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3098.

Full text
Abstract:
The construction of grid plays an important role in national economic development, social stability and peoples life. In case that electricity market adopts real time electricity price, users active participation and real time response to electricity price will change the traditional load prediction from rigid forecasting to flexible forecasting which takes electricity demand response into consideration. By using wavelet analysis and error characteristics analysis, the researches into the probabilistic predicting method for demand changes under the real time electricity pricing is carried out. The probabilistic load prediction result shall enable decision makers to better understand the load change range in the future and make more reasonable decision. Meanwhile, it shall provide support to electricity system risk analysis.
APA, Harvard, Vancouver, ISO, and other styles
14

Fuchs, Johann, Doris Söhnlein, and Patrizio Vanella. "Migration Forecasting—Significance and Approaches." Encyclopedia 1, no. 3 (August 2, 2021): 689–709. http://dx.doi.org/10.3390/encyclopedia1030054.

Full text
Abstract:
Migration is defined as the permanent change in an individual’s usual residence. Forecasting migration is an important requisite for population forecasts or for planning in fields that depend on the future size and structure of the population, such as economics, epidemiology, social insurance, or infrastructure. As migration is the most volatile of all demographic components, its modeling is especially difficult. International migration can be modeled and forecast very differently; users should be familiar with the flaws and strengths of these different approaches.
APA, Harvard, Vancouver, ISO, and other styles
15

Kashin, Konstantin, Gary King, and Samir Soneji. "Explaining Systematic Bias and Nontransparency in U.S. Social Security Administration Forecasts." Political Analysis 23, no. 3 (2015): 336–62. http://dx.doi.org/10.1093/pan/mpv011.

Full text
Abstract:
The accuracy of U.S. Social Security Administration (SSA) demographic and financial forecasts is crucial for the solvency of its Trust Funds, other government programs, industry decision-making, and the evidence base of many scholarly articles. Because SSA makes public insufficient replication information and uses antiquated statistical forecasting methods, no external group has ever been able to produce fully independent forecasts or evaluations of policy proposals to change the system. Yet, no systematic evaluation of SSA forecasts has ever been published by SSA or anyone else—until a companion paper to this one. We show that SSA's forecasting errors were approximately unbiased until about 2000, but then began to grow quickly, with increasingly overconfident uncertainty intervals. Moreover, the errors are largely in the same direction, making the Trust Funds look healthier than they are. We extend and then explain these findings with evidence from a large number of interviews with participants at every level of the forecasting and policy processes. We show that SSA's forecasting procedures meet all the conditions the modern social-psychology and statistical literatures demonstrate make bias likely. When those conditions mixed with potent new political forces trying to change Social Security, SSA's actuaries hunkered down, trying hard to insulate their forecasts from strong political pressures. Unfortunately, this led the actuaries into not incorporating the fact that retirees began living longer lives and drawing benefits longer than predicted. We show that fewer than 10% of their scorings of major policy proposals were statistically different from random noise as estimated from their policy forecasting error. We also show that the solution to this problem involves SSA or Congress implementing in government two of the central projects of political science over the last quarter century: (1) transparency in data and methods and (2) replacing with formal statistical models large numbers of ad hoc qualitative decisions too complex for unaided humans to make optimally.
APA, Harvard, Vancouver, ISO, and other styles
16

Agamirov, K. V. "Social Sphere as an Object of Legal Regulation and Legal Forecasting." Lex Russica 1, no. 2 (February 28, 2020): 106–24. http://dx.doi.org/10.17803/1729-5920.2020.159.2.106-124.

Full text
Abstract:
The importance of legal forecasting lies in the study of legal phenomena and processes that occur under the influence of economic, political, demographic, ideological, and international factors of change, and in the development of proposals for the optimal development of legislation for their subsequent inclusion in legislative work plans. The main methodological problem of legal forecasting is to reveal the essence of the category "legal system and the future", the dynamics of which determines the quality of predictive research at all levels: strategies for the development of Russian legislation; legal institutions; legal education and law making; legal behavior of the individual (sociological aspect of forecasting). Representing a system of certain theoretical principles, forms and methods, as well as epistemological regularities for obtaining probabilistic judgments about the future state of legal and state phenomena and processes, the methodology of legal forecasting is aimed at improving the effectiveness of normative acts in all branches of law. It determines the most rational ways of developing the legal system as a whole. The paper analyzes the state of legal regulation in the field of maternal, child and family protection, social security, labor relations and some other areas of social reality. Using legal methods of forecasting, the author sketches the socio-legal institutional and industry models based on political-legal, socio-economic and spiritual factors, which are important landmarks to improve social relations, legal institutions and standards. The author proposes specific measures for the modernization of the legislative institutions in the socio-legal environment corresponding to the socio-cultural processes taking place in society and expected changes in the socio-cultural conditions in the future based on experienced or anticipated social needs. Conclusion: the current stage and social dynamics of social development require urgent legislative measures to ensure a decent human existence and implement the provision of article 2 of the Constitution of the Russian Federation on his rights and freedoms as the highest value.
APA, Harvard, Vancouver, ISO, and other styles
17

Zhovtianska, Valeria. "Psychological principles of modeling as a methodological area of social forecasting." SCIENTIFIC STUDIOS ON SOCIAL AND POLITICAL PSYCHOLOGY 51, no. 48 (January 10, 2022): 9–15. http://dx.doi.org/10.61727/sssppj/2.2021.09.

Full text
Abstract:
The article aimed to identify the psychological foundations of modeling social phenomena to predict their development. Modeling, extrapolation, and expert methods are the most common methodological areas of social prognosis. The literature now pays more attention to extrapolation and expert methods, despite the inherent shortcomings and limitations in these methodological areas compared to modeling. This is because modeling requires identifying the fundamental causes for social processes, which is a problem area in modern science. Based on theoretical analysis, the article substantiates the thesis that the modeling of social development processes should outline the understanding of its psychological mechanisms and factors. Since, in the ontological sense, the agent of this development is a person as a member of society, it is the content of the mental life of society members that determines the vector of social change. At the same time, when modeling social processes, it is crucial to consider the cultural achievements of a particular society, which can be identified with the initial position to which the vector of further social development will be applied. In practical terms, the design of prognostic models of social development involves the identification of psychological characteristics important for determining the functioning of society and understanding the psychological mechanisms through which these characteristics affect social development. Besides, short-term and medium-term forecasts for determining the vector of development of society can be based on current measurements of these characteristics. Forecasting social changes for a more significant time perspective requires generalized models of social development, which would take into account time changes in the psychological aspects. The psychological principles described in the article can be directly used in the design of prognostic models of social development processes, which is a prospect for further work and determines the practical value of the study
APA, Harvard, Vancouver, ISO, and other styles
18

Record, Nicholas R., and Andrew J. Pershing. "Facing the Forecaster’s Dilemma: Reflexivity in Ocean System Forecasting." Oceans 2, no. 4 (November 12, 2021): 738–51. http://dx.doi.org/10.3390/oceans2040042.

Full text
Abstract:
Unlike atmospheric weather forecasting, ocean forecasting is often reflexive; for many applications, the forecast and its dissemination can change the outcome, and is in this way, a part of the system. Reflexivity has implications for several ocean forecasting applications, such as fisheries management, endangered species management, toxic and invasive species management, and community science. The field of ocean system forecasting is experiencing rapid growth, and there is an opportunity to add the reflexivity dynamic to the conventional approach taken from weather forecasting. Social science has grappled with reflexivity for decades and can offer a valuable perspective. Ocean forecasting is often iterative, thus it can also offer opportunities to advance the general understanding of reflexive prediction. In this paper, we present a basic theoretical skeleton for considering iterative reflexivity in an ocean forecasting context. It is possible to explore the reflexive dynamics because the prediction is iterative. The central problem amounts to a tension between providing a reliably accurate forecast and affecting a desired outcome via the forecast. These two objectives are not always compatible. We map a review of the literature onto relevant ecological scales that contextualize the role of reflexivity across a range of applications, from biogeochemical (e.g., hypoxia and harmful algal blooms) to endangered species management. Formulating reflexivity mathematically provides one explicit mechanism for integrating natural and social sciences. In the context of the Anthropocene ocean, reflexivity helps us understand whether forecasts are meant to mitigate and control environmental changes, or to adapt and respond within a changing system. By thinking about reflexivity as part of the foundation of ocean system forecasting, we hope to avoid some of the unintended consequences that can derail forecasting programs.
APA, Harvard, Vancouver, ISO, and other styles
19

Coelho, Edviges, and Luis C. Nunes. "Forecasting mortality in the event of a structural change." Journal of the Royal Statistical Society: Series A (Statistics in Society) 174, no. 3 (March 15, 2011): 713–36. http://dx.doi.org/10.1111/j.1467-985x.2010.00687.x.

Full text
APA, Harvard, Vancouver, ISO, and other styles
20

Kajikawa, Yuya, Cristian Mejia, Mengjia Wu, and Yi Zhang. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses." Technological Forecasting and Social Change 182 (September 2022): 121877. http://dx.doi.org/10.1016/j.techfore.2022.121877.

Full text
APA, Harvard, Vancouver, ISO, and other styles
21

Kraus, Sascha, Satish Kumar, Weng Marc Lim, Jaspreet Kaur, Anuj Sharma, and Francesco Schiavone. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change." Technological Forecasting and Social Change 189 (April 2023): 122381. http://dx.doi.org/10.1016/j.techfore.2023.122381.

Full text
APA, Harvard, Vancouver, ISO, and other styles
22

Balatsky, Evgeny, and Nataly Ekimova. "Public administration tools: Forecasting vs Designing." Upravlenets 12, no. 1 (March 4, 2021): 18–31. http://dx.doi.org/10.29141/2218-5003-2021-12-1-2.

Full text
Abstract:
The article discusses the expediency of abandoning the tool of social forecasting in the practice of public administration in favor of planning and design methods. The methodological basis rests on the conceptual imperative of the impossibility to produce adequate forecasts in the modern world, which is supported by such respected researchers as Douglas North, George Soros, Nassim Taleb and Arnold Toynbee. The fairness of this thesis is illustrated using methods of comparison and analysis. The study analyses the main factors that cast doubt on the possibility and expediency of preserving the tool of social prognostics: the failure of the scenario forecast format; the need for foreknowledge of events rather than values of traditional macro-parameters; the extension of Arnold Toynbee’s principle from a historical retrospective to studying the prospects; the economic growth rate indicator (GDP) losing its indicative universality and the emergence of alternative measures of social development (Gross National Happiness, culture and environment preservation); critical attitude of the intellectual elite to the possibility of social forecasting; unreliability of the source statistics; the expectation of the end of economic growth, a change in the development regime and quantitative forecasting devaluation by the leading experts – Douglas North, Robert Lucas, Tom Piketty, Richard Heinberg; the completion of the mission of capitalism in the form of the Neo-Malthusian trap and robotomics (mass introduction of robots to the economy). The authors prove that amid fading interest in traditional forecasting, alternative prognostication methods are emerging, such as planning, designing, futurology, foresight and strategic intelligence. Devaluation of forecast tools leads to the need to change the old doctrine of public administration, based on forecast documents, to a new one implying a transition to active construction of the future through directive designing and planning. The theoretical and practical significance of the study lies in substantiating the principles of a new management system: expanding the planning and design horizon (up to 30 years); introducing a mechanism for implementing plans and projects; introducing mechanisms for pre-project foresight; creating a twolevel economic management system; and moving from the quantity paradigm to the quality one.
APA, Harvard, Vancouver, ISO, and other styles
23

Land, Kenneth C., and Stephen H. Schneider. "Forecasting in the social and natural sciences: An overview and analysis of isomorphisms." Climatic Change 11, no. 1-2 (1987): 7–31. http://dx.doi.org/10.1007/bf00138793.

Full text
APA, Harvard, Vancouver, ISO, and other styles
24

Qiu, Richard T. R., Anyu Liu, Jason L. Stienmetz, and Yang Yu. "Timing matters: crisis severity and occupancy rate forecasts in social unrest periods." International Journal of Contemporary Hospitality Management 33, no. 6 (June 8, 2021): 2044–64. http://dx.doi.org/10.1108/ijchm-06-2020-0629.

Full text
Abstract:
Purpose The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example. Design/methodology/approach Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy. Findings Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises. Originality/value The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.
APA, Harvard, Vancouver, ISO, and other styles
25

Bryzhan, Iryna, Vira Chevhanova, Оlesya Hryhoryeva, and Lyudmyla Svystun. "Approaches to forecasting demography trends in the management of integrated area development." Economy and forecasting 2020, no. 2 (October 12, 2020): 16–31. http://dx.doi.org/10.15407/econforecast2020.02.016.

Full text
Abstract:
The article is devoted to the innovative approach in the management of the area development for Ukraine based on demographic forecasting. Demographic forecasting is an essential element of informational supply for development and implementation of mid- and long-term social-economic development strategy and public administration of the area development. It is emphasized that the approach to solve this problem should be comprehensive. One of the modern options to settle the problem is based on borrowing European expertise on integrated development, which results, apart from social-economic growth and environment improvement, in significant increase in the number of European urban dwellers. Detailed demographic forecast should make a ground for decision-making and development of integrated area plans. Integrated development of areas, primarily urban ones, involves the development of all urban environment elements: transport, economy, economic and social infrastructure, etc. Therefore, it requires vertical integration, on one hand, of various public administration levels – national, regional, and local ones, and, on the other, of private sector and public society. Based on the analysis of demographic forecasting methods, the authors propose their own approach to area population forecasting, combining the component method that considers the net migration indices, the future employment estimating method and the similarity (correlation) method. The authors offer their own approach for area population forecasting based on a combination of cohort group method (considers the net migration indices), future employment estimate and similarity (correlation) methods. The common indices (birth and death rates, migration) should be the key components. However, the factors for their future changes should be defined individually based on the trends in the city's social-economic development. The proposed method takes into account the impact of the key drivers capable to change significantly the demographic forecasting when developing normative and functional demo-forecast options, and should make up the basis for social-economic strategic plans of urban development to be implemented by local authorities and self-government bodies. The theoretical provisions are supported with practical data of demographic forecasting for the implementation of integrated development strategy for the town of Poltava (Ukraine). Authors argue that demographic forecasting is optimal under the following conditions: detailed social-economic analysis of the city; and identification of strengths and weaknesses, and opportunities and threats. Based on the performed analysis and the objectives of perspective development, one can assess the opportunities for the improvement of demographic situation in the cities.
APA, Harvard, Vancouver, ISO, and other styles
26

Singh, Shiwangi, Sanjay Dhir, V. Mukunda Das, and Anuj Sharma. "Bibliometric overview of the Technological Forecasting and Social Change journal: Analysis from 1970 to 2018." Technological Forecasting and Social Change 154 (May 2020): 119963. http://dx.doi.org/10.1016/j.techfore.2020.119963.

Full text
APA, Harvard, Vancouver, ISO, and other styles
27

Liu, Dongyao. "The prediction and analysis of global climate change based on SARIMA." Applied and Computational Engineering 40, no. 1 (February 21, 2024): 268–73. http://dx.doi.org/10.54254/2755-2721/40/20230665.

Full text
Abstract:
Global climate change is a significant challenge that the world is currently facing. Accurate prediction of global climate change is essential for environmental protection, agricultural production, and social development. This study explores the utilization of the Seasonal Autoregressive Integrated Moving Average (SARIMA) model for forecasting global climate change. The SARIMA model is a machine learning algorithm that can effectively capture seasonal patterns and non-linear characteristics of climate data. The study initiates by performing data preprocessing tasks, which encompass data cleaning, managing missing values, and converting the data into a suitable format for analysis. The SARIMA model is then constructed, considering the seasonality and autocorrelation of the climate data. Historical climate data is used to train the SARIMA models, which are then utilized to forecast future global climate changes. The predictive performance of the models is evaluated to validate the effectiveness and accuracy of the SARIMA model in global climate change prediction. Experimental results indicate that the SARIMA model effectively captures the underlying patterns and dynamics of the climate data. The accurate predictions of the SARIMA model have practical implications for understanding and forecasting global climate change. These forecasts provide insightful information for policy formulation and decision-making, aiding in the development of innovative strategies to mitigate and adapt to climate change.
APA, Harvard, Vancouver, ISO, and other styles
28

Klyuchnikova, E. M., L. G. Isaeva, A. V. Masloboev, T. E. Alieva, L. V. Ivanova, and G. N. Kharitonova. "Future narratives for key sectors of the economy of the Murmansk region in the context of global changes in the Arctic." Arctic: Ecology and Economy, no. 1(25) (March 2017): 19–31. http://dx.doi.org/10.25283/2223-4594-2017-1-19-31.

Full text
Abstract:
This article presents forecast of the future development of the key industries of the Murmansk region under the climate change conditions, and developments that can be used as the background for discussing measures for adaptation to climate changes and producing long-term documents. We have revealed a wide range of scenarios to identify the uncertainties that the region will inevitably face and that should be taken into account when making decisions already now. We have used the forecasting method taking into account the two critical parameters: the climate change on the regional level and the global trends in the socio-economic development. The narratives from the Shared Socioeconomic Pathways (SSPs) have been used as boundary conditions for creating scenarios of Murmansk region development. The local experts - representatives of industries, regional and local authorities, non-governmental and scientific organizations were involved in the forecasting process. The foresight research methodology was chosen because it is more than a long-term and strategic planning and forecasting corresponds to the social progress, in particular, the society democratization in its main areas: engaging citizens to managing the state affairs and creating conditions for manifestation of their initiatives. As a result, the issues of forecasting the future trends and challenges in the key sectors of the economy of the Arctic under the changing climate, depending on the forecast global development trends were considered. The necessity of using a structured, coherent to the global trends approach to working out regional and corporate development strategies is substantiated. On the example of the Murmansk region, the possible scenarios of development of the mining industry, and energy and human potentials depending on the global changes, including the climate change are considered.
APA, Harvard, Vancouver, ISO, and other styles
29

Illston, Bradley G., Jeffrey B. Basara, Christopher Weiss, and Mike Voss. "The WxChallenge: Forecasting Competition, Educational Tool, and Agent of Cultural Change." Bulletin of the American Meteorological Society 94, no. 10 (October 1, 2013): 1501–6. http://dx.doi.org/10.1175/bams-d-11-00112.1.

Full text
Abstract:
The WxChallenge, a project developed at the University of Oklahoma, brings a state-of-the-art, fun, and exciting forecast contest to participants at colleges and universities across North America. The challenge is to forecast the maximum and minimum temperatures, precipitation, and maximum wind speeds for select locations across the United States over a 24-h prediction period. The WxChallenge is open to all undergraduate and graduate students, as well as higher-education faculty, staff, and alumni. Through the use of World Wide Web interfaces accessible by personal computers, tablet computer, and smartphones, the WxChallenge provides a state-of-the-art portal to aid participants in submitting forecasts and alleviate many of the administrative issues (e.g., tracking and scoring) faced by local managers and professors. Since its inception in 2006, 110 universities have participated in the contest and it has been utilized as part of the curricula for 140 classroom courses at various institutions. The inherently challenging nature of the WxChallenge has encouraged its adoption as an educational tool. As its popularity has grown, professors have seen the utility of the Wx-Challenge as a teaching aid and it has become an instructional resource of many meteorological classes at institutions for higher learning. In addition to evidence of educational impacts, the competition has already begun to leave a cultural and social mark on the meteorological learning experience.
APA, Harvard, Vancouver, ISO, and other styles
30

Roh, Seungkook, and Jae Young Choi. "Exploring Signals for a Nuclear Future Using Social Big Data." Sustainability 12, no. 14 (July 10, 2020): 5563. http://dx.doi.org/10.3390/su12145563.

Full text
Abstract:
Since the start of the new Korean government in 2017, the Korean nuclear energy system has undergone a major change. This change in national energy policy can be forecasted by analyzing social big data. This study verifies whether future forecasting methodologies using weak signals can be applied to Korean nuclear energy through text mining the data of web news between 2005 and 2018, comparing and applying the methodology to notable events (i.e., the UAE nuclear power plant (NPP) contract and nuclear phase-out). In addition, we predict what changes will be made in the Korean nuclear energy system post-2019. Keywords extracted through text mining were quantitatively classified into a weak signal or a strong signal using a Keyword Emergence Map (KEM) and a Keyword Issue Map (KIM). The extracted keywords predicted the contract of the UAE NPPs in 2009 and nuclear phase-out in 2017. Furthermore, keywords revealing future signals beyond 2019 were found to be ‘nuclear phase-out’ and ‘wind energy’. The weak-signal methodology can be applied as a tool to predict future energy trends during the current circumstance of the rapidly changing world energy market.
APA, Harvard, Vancouver, ISO, and other styles
31

Kim, Kyeong-Baek, Ji-Hoon Cho, and Sang-Bum Kim. "Model-Based Dynamic Forecasting for Residential Construction Market Demand: A Systemic Approach." Applied Sciences 11, no. 8 (April 19, 2021): 3681. http://dx.doi.org/10.3390/app11083681.

Full text
Abstract:
According to the previous research, proper demand forecasting could help construction-related firms in effective planning for future market changes. However, existing market demand forecasting models are somewhat limited, and most of them bear some critical shortcomings. This research aims to develop a forecasting model for the Korean residential construction industry using system dynamics. In developing the market forecasting model, this research uses variables that significantly impact future construction market change. Many of the existing models do not include as many variables as this model, and none of them have considered complex interlocking effects among these variables. This model is also the first model using a system-based approach by looking at the target industry as a ‘one complex system’ rather than focusing on individual variables’ impact on future market changes. By employing system dynamics, it is possible to consider qualitative and quantitative aspects and produce long-term market forecasting results. The developed market forecasting model consists of two main modules, the first being a prediction module for the grassroots construction market and the second for operation and maintenance (O&M) and the demolition market. Sixteen input variables are grouped into four categories: social, economy, regulation, and past market size among over 25 identified variables. The model utilizes a mathematical function system using the designed feedback loops in producing future market forecasts. Based on the validation tests with past market data, it turns out that the model is reliable, with the determination coefficient (R2) being over 0.7 on all tested occasions. According to the model’s forecasting results, the Korean construction market’s size is expected to be 231 billion won in 2015 and 286 billion won in 2030. However, the O&M market’s growth rate is expected to be higher than 180%, which is much bigger than those of the grass-root and demolition markets. Thus, this research model is realistic according to the construction paradigm change. This research is considered one of the pioneering studies in construction market forecasting by employing dynamic inter-relationships among various input variables. Therefore, the market forecasting results can be interpreted as more practical and can provide more insights to the construction industry stakeholders. The model is envisioned to provide the public sector with useful guidelines in preparing future public market supply strategies such as construction budget allocations. It would also be helpful for the private sector to develop more proactive and accurate demand strategies for timely decision-making.
APA, Harvard, Vancouver, ISO, and other styles
32

Gbangou, Talardia, Erik Van Slobbe, Fulco Ludwig, Gordana Kranjac-Berisavljevic, and Spyridon Paparrizos. "Harnessing Local Forecasting Knowledge on Weather and Climate in Ghana: Documentation, Skills, and Integration with Scientific Forecasting Knowledge." Weather, Climate, and Society 13, no. 1 (January 2021): 23–37. http://dx.doi.org/10.1175/wcas-d-20-0012.1.

Full text
Abstract:
AbstractImproved weather and climate forecast information services are important to sustain small-scale crop production in many developing countries. Previous studies recognized the value of integrating local forecasting knowledge (LFK) with scientific forecasting knowledge (SFK) to support farmers’ decision-making. Yet, little work has focused on proper documentation, quality verification, and integration techniques. The skills of local and scientific forecasts were compared, and new integration approaches were derived over the coastal zone of Ghana. LFK indicators were documented, and farmers were trained to collect indicators’ observations and record rainfall in real time using digital tools and rain gauges, respectively, in 2019. Dichotomous forecasts verification metrics were then used to verify the skills of both local and scientific forecasts against rainfall records. Farmers use a diverse set of LKF indicators for both weather and seasonal climate time-scale predictions. LFK indicators are mainly used to predict rainfall occurrence, amount of seasonal rainfall, dry spell occurrence, and onset and cessation of the rainy season. The average skill of a set of LFK indicators in predicting one-day rainfall is higher than individual LFK indicators. Also, the skills of a set of LFK indicators can potentially be higher than the forecasts given by the Ghana Meteorological Agency for the Ada District. The results of the documentation and skills indicate that approaches and methods developed for integrating LFK and SFK can contribute to increasing forecast resolution and skills and reducing recurring tensions between the two knowledge systems. Future research and application of these methods can help improve weather and climate information services in Ghana.
APA, Harvard, Vancouver, ISO, and other styles
33

Zenian, S. "The SIR Model for COVID-19 in Malaysia." Journal of Physics: Conference Series 2314, no. 1 (August 1, 2022): 012007. http://dx.doi.org/10.1088/1742-6596/2314/1/012007.

Full text
Abstract:
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 as a global pandemic caused by severe acute respiratory syndrome. This virus is referred to as SARS-CoV-2 and the associated disease is COVID-19. It is an infectious disease that can easily be transmitted via respiratory droplets through direct or indirect contact. This paper presents an epidemiological model of COVID-19 in Malaysia by using Susceptible-Infected-Removed (SIR) as a forecasting model. Forecasting is a technique used to predict or estimate the trend or rate of change for future events. This method can provide a good forecasting result for evaluating public health and social measures in response to the COVID-19 epidemic and also to make timely plans.
APA, Harvard, Vancouver, ISO, and other styles
34

Guaita García, Noelia, Julia Martínez Fernández, and Carl Fitz. "Environmental Scenario Analysis on Natural and Social-Ecological Systems: A Review of Methods, Approaches and Applications." Sustainability 12, no. 18 (September 13, 2020): 7542. http://dx.doi.org/10.3390/su12187542.

Full text
Abstract:
Scenario analysis is a useful tool to facilitate discussions about the main trends of future change and to promote the understanding of global environmental changes implications on relevant aspects of sustainability. In this paper, we reviewed 294 articles published between 1995–2019, to evaluate the state of the art use of models and scenarios to investigate the effects of land use change and climate change on natural and social-ecological systems. Our review focuses on three issues. The first explores the extent to which the environmental dynamics of land use and climate change were jointly analyzed and the spatial scales associated with such integrated studies. The second explores the modelling methodologies and approaches used in the scenario analysis. The third explores the methods for developing or building scenarios. Results show that in most predictions there is little integration of key drivers of change. We find most forecasting studies use a sectoral modelling approach through dynamic spatially distributed models. Most articles do not apply a participatory approach in the development of scenarios. Based on this review, we conclude that there are some gaps in how scenario analysis on natural and social-ecological systems are conducted. These gaps pose a challenge for the use of models and scenarios as predictive tools in decision-making processes in the context of global change.
APA, Harvard, Vancouver, ISO, and other styles
35

Raybould, Caroline. "Trends forecasting as a tool for sustainable education." Fashion, Style & Popular Culture 00, no. 00 (February 18, 2021): 1–14. http://dx.doi.org/10.1386/fspc_00058_1.

Full text
Abstract:
The fashion and textile industry is under increasing scrutiny because of its unethical and unsustainable practices. It is clear there needs to be systemic change towards a more ecological future. One way to achieve this is through education, by equipping students with strategies and skills and by nurturing sustainable mindsets. How can we create the next generation of fashion professionals who can help bring the change that is much needed? Having taught sustainability within various modules on a fashion business degree in the United Kingdom, it was observed that a significant number of students engaged at a deeper level with sustainable thinking when learning trends forecasting research. A pilot study was trialled when teaching a short course in India with a small group of interdisciplinary design students and a questionnaire was conducted after the workshop. This article presents findings and reflections of this cross-cultural experience, with suggestions for future projects and educational approaches.
APA, Harvard, Vancouver, ISO, and other styles
36

Ulanchuk, V., E. Zharun, N. Korotieiev, A. Nepochatenko, and S. Sokoliuk. "Econometric approaches to forecasting financial support of socio-economic development of the region." Collected Works of Uman National University of Horticulture 2, no. 99 (December 22, 2021): 163–71. http://dx.doi.org/10.31395/2415-8240-2021-99-2-163-171.

Full text
Abstract:
In the given article it is noted that the level of forecasting of processes of social development is determined by the efficiency of planning and management of economy and other spheres. Social and economic forecasting of basic trends of social development allows use of special calculation and logic methods, giving the opportunity to determine parameters of functioning of separate elements of productive forces in their interrelation and interdependence. At the current stage of regional development of the state, the forecasting of the management of social-economic processes in the region is urgent, and the need for their improvement in order to obtain effective tools for determining the main guidelines and directions of regional policy. Predictions that include scientific justification should be central to the planned decisions of state authorities and the implementation of social-economic policies in the region, to determine the main directions of its future development, place and role in the national economy. The process of forming a modern system of forecasting regional development in Ukraine took place under conditions of a large-scale state transformation and reorganization. The change in the political regime and reform of the Ukrainian economy, which began in the 1990s, led to the inversion of the role of the territory in the system of public administration. Regions that previously had very limited rights in the agricultural sector, received the right to make political, economic, social, cultural and other decisions on their own. Economic forecasting is necessary for determining ways of society development and economic resources which provide its achievement, for revealing most likely and economically efficient variants of long-term, medium term and current plans, grounding main directions of economic and technical politics, forecasting the consequences of the made decisions and measures taken at present. Application of econometric models in economics gives the opportunity to distinguish and formally describe the most significant, the most essential relations of economic variables and objects, as well as to get new knowledge about the object in the inductive way. In such model, in the simplified form, by many assumptions, the main dependence between economic indicators is determined.
APA, Harvard, Vancouver, ISO, and other styles
37

Badina, S. V. "Forecasting the Costs of Adapting Social Infrastructure to Changing Geocryological Conditions (the Case of Norilsk)." Federalism 28, no. 4 (December 21, 2023): 140–56. http://dx.doi.org/10.21686/2073-1051-2023-4-140-156.

Full text
Abstract:
Climate change and increased anthropogenic impact lead to the melting of permafrost and, consequently, destruction and deformation of buildings and structures built on it. This causes significant additional financial costs associated with the need to use specific technologies for the construction and operation of buildings in the permafrost zone, as well as direct and indirect damage from the loss of fixed assets. According to forecasts of geocryological changes, in the Russian Arctic these negative trends should intensify in the future. In this study, using the case of the Norilsk city (Krasnoyarsk Krai, Russia), some problems associated with estimating the costs of adapting healthcare and educational facilities built on permafrost to changes in engineering and geocryological conditions until the middle of the 21st century are analyzed. The analysis showed that the amount of probable costs for the group of objects under consideration associated with direct damage from deformation and destruction of buildings, as well as the need for their liquidation and replacement construction, significantly exceeds the financial resources allocated for this in the relevant strategic documents planning of Norilsk. An effective mechanism for redistributing damage over time and reducing it is the installation of the soil thermal stabilization systems. The paper briefly analyzes the geography of production and consumption of this type of product. The results obtained can be used to develop similar assessments and adaptation programs in cities in the permafrost zone of Russia.
APA, Harvard, Vancouver, ISO, and other styles
38

Hill, Bruce M. "Bayesian Forecasting of Economic Time Series." Econometric Theory 10, no. 3-4 (August 1994): 483–513. http://dx.doi.org/10.1017/s0266466600008641.

Full text
Abstract:
A model is suggested to forecast economic time series. This model incorporates some innovative ideas of Harrison and Stevens [20] for building into the forecasting process important external shocks to the systems. Thus the occurrence of possibly significant real-world events may cause a fundamental change in the time series in question. The Jeffreys-Savage (JS) Bayesian theory of hypothesis testing is used to test the hypothesis that a particular event has been such as to free the series from its immediate past behavior. When the event frees the series in this way, then we model the sequence of observations following such an event (until the next such event) as an exchangeable sequence. In the simplest case of 0–1 valued data, such as in recording the ups and downs of the value of a particular commodity or stock, our alternative hypothesis is a Pólya process, and the null hypothesis is a simple random walk (unit roots model) with p = .50. Any exchangeable sequence is strictly stationary, and the observations in the Polya process are positively correlated, which can give rise to “explosive” behavior of the series at isolated time points. We then use the JS theory to predict future observations by taking a weighted average of the optimal predictions for each model, with weights given by the posterior probabilities of the hypotheses. Results of simulation studies are presented which compare the predictive performance of the fully Bayesian method based upon the JS theory with those based upon the “p-value” or pre-test method. The de Finetti method for scoring predictions is used to assess their empirical performance. A theoretical methodology, which extends the “evaluation game” of Hill [28,37], is developed for comparing predictors.
APA, Harvard, Vancouver, ISO, and other styles
39

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 (October 31, 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 relevance to create real-time urban flood forecasting systems for flood disaster prevention agencies and the urban public. This review examined the state-of-the-art models of real-time forecasting systems for urban flash floods in Malaysia and Indonesia. The real-time system primarily comprises the following subsystems, i.e., rainfall forecasting, drainage system modeling, and inundation area mapping. This review described the current urban flood forecasting modeling for rainfall forecasting, physical-process-based hydraulic models for flood inundation prediction, and data-driven artificial intelligence (AI) models for the real-time forecasting system. The analysis found that urban flood forecasting modeling based on data-driven AI models is the most applied in many metropolitan locations in Malaysia and Indonesia. The analysis also evaluated the existing potential of data-driven AI models for real-time forecasting systems as well as the challenges towards it
APA, Harvard, Vancouver, ISO, and other styles
40

Storozhuk, Anna Yurievna. "DETERMINANTS OF SCIENTIFIC THINKING FROM THE PERSPECTIVE OF SOCIAL EPISTEMOLOGY (on the example of forecasting climate change)." Философия науки, no. 3 (2021): 87–99. http://dx.doi.org/10.15372/ps20210306.

Full text
APA, Harvard, Vancouver, ISO, and other styles
41

Tsai, Yuan-Hui, Chieh-Peng Lin, Hwa-Chun Ma, and Rong-Tsu Wang. "Modeling corporate social performance and job pursuit intention: Forecasting the job change of professionals in technology industry." Technological Forecasting and Social Change 99 (October 2015): 14–21. http://dx.doi.org/10.1016/j.techfore.2015.06.026.

Full text
APA, Harvard, Vancouver, ISO, and other styles
42

Razvodovsky, Y. E., V. Y. Smirnov, and P. B. Zotov. "Forecasting of fatal alcohol poisonings rate in Russia." I.P.Pavlov Russian Medical Biological Herald 24, no. 4 (December 15, 2016): 67–77. http://dx.doi.org/10.23888/pavlovj2016467-77.

Full text
Abstract:
This article tests the possibility of forecasting of fatal alcohol poisonings rate in Russia using the analysis of time series from 1956 to 2013. The results from present study support the hypothesis that a change in the affordability of alcohol was the key determinant of dramatic fluctuations in the fatal alcohol poisonings rate in Russia during the last decades. Most visible effect of measures on restriction of alcohol’s availability was during antialcohol campaign 1985-1988 and following the adoption of new antialcohol initiatives in 2005. This study highlighted the limitations associated with forecasting of fatal alcohol poisonings rate using extrapolation of time series. Adoption of new antialcohol initiatives in 2005 appeared as an intervention witch effected the trends in fatal alcohol poisonings rate. This suggests that different kinds of social interventions hamper reliable forecasting of fatal alcohol poisonings rate.
APA, Harvard, Vancouver, ISO, and other styles
43

Pizarro Milian, Roger, and Scott Davies. "Forecasting the impacts of the “future of work” on universities: a sociological perspective." On the Horizon 28, no. 1 (February 22, 2020): 63–71. http://dx.doi.org/10.1108/oth-11-2019-0080.

Full text
Abstract:
Purpose The purpose of this study is to analyse the prospective impact of the future of work on universities. Design/methodology/approach Several brief case studies of heralded disruptors of higher education (HE) – including digital badges, for-profit universities and massive open online courses – are reviewed to illustrate inertial forces in the system. Findings The results indicate that several social forces will protect most universities from significant disruption, with the impetus for change being felt mostly in the periphery of the system. Originality/value The argument presented in this study serves as a corrective to claims that looming changes in the nature of work will radically disrupt universities. It calls for more nuanced theorizing about the interaction between technical and institutional forces in HE.
APA, Harvard, Vancouver, ISO, and other styles
44

Safi, Samir K. "On Predicting Growth Factor Data of Covid-19 Epidemic Using Hybrid Arima-Ann Model." British Journal of Multidisciplinary and Advanced Studies 4, no. 5 (October 22, 2023): 127–35. http://dx.doi.org/10.37745/bjmas.2022.0335.

Full text
Abstract:
The Autoregressive Integrated Moving Average (ARIMA) model cannot capture the nonlinear patterns exhibited by the 2019 coronavirus (COVID-19) in terms of daily growth factor. As a result, Artificial Neural Networks (ANNs) and Hybrid ARIMA-ANN models have been successfully applied to resolve problems with nonlinear estimation. We compare the forecasting performance of these models using real, worldwide, daily COVID-19 data. The best forecasting model selected was compared using the forecasting assessment criterion known as mean absolute error. The main finding results show that the ANN model is more efficient than the ARIMA and Hybrid ARIMA-ANN models. The main finding from the ANN model analysis indicates that the magnitude of the increase in growth factor over time is rising in general while the percentage change in the growth factor is declining. This may be the result of the social distancing, safety, and cautionary measures mandated by governments worldwide.
APA, Harvard, Vancouver, ISO, and other styles
45

HORST, ULRICH, and CHRISTIAN ROTHE. "QUEUING, SOCIAL INTERACTIONS, AND THE MICROSTRUCTURE OF FINANCIAL MARKETS." Macroeconomic Dynamics 12, no. 2 (April 2008): 211–33. http://dx.doi.org/10.1017/s1365100507070010.

Full text
Abstract:
We consider an agent-based model of financial markets with asynchronous order arrival in continuous time. Buying and selling orders arrive in accordance with a Poisson dynamics where the order rates depend both on past prices and on the mood of the market. The agents form their demand for an asset on the basis of their forecasts of future prices and their forecasting rules may change over time as a result of the influence of other traders. Among the possible rules are “chartist” or extrapolatory rules. We prove that when chartists are in the market, and with choice of scaling, the dynamics of asset prices can be approximated by an ordinary delay differential equation. The fluctuations around the first-order approximation follow an Ornstein–Uhlenbeck dynamics with delay in a random environment of investor sentiment.
APA, Harvard, Vancouver, ISO, and other styles
46

Jorgensen, Joseph, Richard Mccleary, and Steven Mcnabb. "Social Indicators in Native Village Alaska1." Human Organization 44, no. 1 (March 1, 1985): 2–17. http://dx.doi.org/10.17730/humo.44.1.61r44v7782262307.

Full text
Abstract:
Social indicators-constructs to assess, and to measure changes to socio-economic conditions of life for contemporary societies-are analyzed for eight Aleutian and northwestern Alaskan villages whose native residents derive their sustenance from hunting, gathering, and fishing. Because of federal, state, and oil corporation actions, these villages and others like them are changing rapidly and dramatically. The analysis proposes a structure for the changes that are occurring, and measurable factors that will "indicate" future changes. Two competing models to explain social change are evaluated-"Western Industrial" and "Underdevelopment"-although both are modified to account for the Alaskan arctic and subarctic and the importance of subsistence economies in those areas. The method employed, commonly referred to as "triangulation," comprises several methodologies, several research designs, and several data sets: autoregressive time series analysis of archival data, multivariate analysis of protocol (interview) data, and contextual and anecdotal analysis of ethnographic observations. Each method has strengths and weaknesses with the strengths of one helping to compensate for the weaknesses of another. Conclusions drawn from the analyses of these several data sets allow us to posit a set of indicators while offering several concluding hypotheses throughout our exposition. Among our conclusions is that if naturally-occurring species on which village life depends are so disrupted by man-made or man-influenced events that they cannot sustain native subsistence and commercial pursuits, the underdevelopment model, shaped to accommodate the uniqueness of the arctic, will be fulfilled. The concluding hypotheses can be tested for validity in restudies, a monitoring system is implied, and a forecasting methodology to assess impacts is suggested. Thus, the study represents a new methodology for social impact assessments (SIA).
APA, Harvard, Vancouver, ISO, and other styles
47

Stewart, Ian, Dustin Arendt, Eric Bell, and Svitlana Volkova. "Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (May 3, 2017): 672–75. http://dx.doi.org/10.1609/icwsm.v11i1.14938.

Full text
Abstract:
Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. This work addresses several important tasks of visualizing and predicting short term text representation shift, i.e. the change in a word's contextual semantics. We study the relationship between short-term concept drift and representation shift on a large social media corpus — VKontakte collected during the Russia-Ukraine crisis in 2014 — 2015. We visualize short-term representation shift for example keywords and build predictive models to forecast short-term shifts in meaning from previous meaning as well as from concept drift. We show that short-term representation shift can be accurately predicted up to several weeks in advance and that visualization provides insight into meaning change. Our approach can be used to explore and characterize specific aspects of the streaming corpus during crisis events and potentially improve other downstream classification tasks including real-time event forecasting in social media.
APA, Harvard, Vancouver, ISO, and other styles
48

Ghobadi, Fatemeh, and Doosun Kang. "Multi-Step Ahead Probabilistic Forecasting of Daily Streamflow Using Bayesian Deep Learning: A Multiple Case Study." Water 14, no. 22 (November 14, 2022): 3672. http://dx.doi.org/10.3390/w14223672.

Full text
Abstract:
In recent decades, natural calamities such as drought and flood have caused widespread economic and social damage. Climate change and rapid urbanization contribute to the occurrence of natural disasters. In addition, their destructive impact has been altered, posing significant challenges to the efficiency, equity, and sustainability of water resources allocation and management. Uncertainty estimation in hydrology is essential for water resources management. By quantifying the associated uncertainty of reliable hydrological forecasting, an efficient water resources management plan is obtained. Moreover, reliable forecasting provides significant future information to assist risk assessment. Currently, the majority of hydrological forecasts utilize deterministic approaches. Nevertheless, deterministic forecasting models cannot account for the intrinsic uncertainty of forecasted values. Using the Bayesian deep learning approach, this study developed a probabilistic forecasting model that covers the pertinent subproblem of univariate time series models for multi-step ahead daily streamflow forecasting to quantify epistemic and aleatory uncertainty. The new model implements Bayesian sampling in the Long short-term memory (LSTM) neural network by using variational inference to approximate the posterior distribution. The proposed method is verified with three case studies in the USA and three forecasting horizons. LSTM as a point forecasting neural network model and three probabilistic forecasting models, such as LSTM-BNN, BNN, and LSTM with Monte Carlo (MC) dropout (LSTM-MC), were applied for comparison with the proposed model. The results show that the proposed Bayesian long short-term memory (BLSTM) outperforms the other models in terms of forecasting reliability, sharpness, and overall performance. The results reveal that all probabilistic forecasting models outperformed the deterministic model with a lower RMSE value. Furthermore, the uncertainty estimation results show that BLSTM can handle data with higher variation and peak, particularly for long-term multi-step ahead streamflow forecasting, compared to other models.
APA, Harvard, Vancouver, ISO, and other styles
49

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 (January 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 urban flood forecasting systems for flood disaster prevention authorities and the urban public. This paper reviewed the state-of-the-art models of real-time forecasting systems for urban flash floods. The real-time system basically consists of the following subsystems, i.e., rainfall forecasting, drainage system modelling, and inundation area mapping. This paper summarized the recent radar data utilization methods for rainfall forecasting, physical-process-based hydraulic models for flood inundation prediction, and data-driven artificial intelligence (AI) models for the real-time forecasting system. This paper also dealt with available technologies for modelling, e.g., digital surface models (DSMs) for the finer urban terrain of drainage systems. The review indicated that an obstacle to using process-based hydraulic models was the limited computational resources and shorter lead time for real-time forecasting in many urban areas in tropical Southeast Asia. The review further discussed the prospects of data-driven AI models for real-time forecasting systems.
APA, Harvard, Vancouver, ISO, and other styles
50

Kaplan, David, and Rani George. "Evaluating Latent Variable Growth Models Through Ex Post Simulation." Journal of Educational and Behavioral Statistics 23, no. 3 (September 1998): 216–35. http://dx.doi.org/10.3102/10769986023003216.

Full text
Abstract:
This article considers the use of ex post (historical) simulation statistics as a means of evaluating latent variable growth models. Ex post simulation involves using the estimated parameters of a latent variable growth model to track the known historical values of an outcome of interest. Such methods of evaluating temporal models were developed primarily in applied economic forecasting and have been known for some time. This paper applies a variety of simulation quality statistics to latent variable growth models. In particular, Theil’s (1966) inequality coefficient, bias proportion, variance proportion, and covariance proportion are used to gauge the simulation adequacy of growth models. An application to the study of change in science achievement using data from the Longitudinal Study of American Youth is provided to illustrate the methodology. The results illustrate the importance of using these measures as adjuncts to more traditional forms of model evaluation, especially if one is considering the use of these models for subsequent forecasting or other policy purposes.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'Social change – Forecasting' for other source types:
Books
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!

To the bibliography