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Journal articles on the topic 'Consensus forecasting'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Chen, Tin-Chih Toly, Yu-Cheng Wang, and Chin-Hau Huang. "An Evolving Partial Consensus Fuzzy Collaborative Forecasting Approach." Mathematics 8, no. 4 (2020): 554. http://dx.doi.org/10.3390/math8040554.

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Current fuzzy collaborative forecasting methods have rarely considered how to determine the appropriate number of experts to optimize forecasting performance. Therefore, this study proposes an evolving partial-consensus fuzzy collaborative forecasting approach to address this issue. In the proposed approach, experts apply various fuzzy forecasting methods to forecast the same target, and the partial consensus fuzzy intersection operator, rather than the prevalent fuzzy intersection operator, is applied to aggregate the fuzzy forecasts by experts. Meaningful information can be determined by obs

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2

Lackman, Conway, and Charles Brandon. "Consensus Forecasting Using Relative Error Weights." Marketing Intelligence & Planning 12, no. 1 (1994): 37–41. http://dx.doi.org/10.1108/02634509410052649.

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Woodcock, Frank, and Chermelle Engel. "Operational Consensus Forecasts." Weather and Forecasting 20, no. 1 (2005): 101–11. http://dx.doi.org/10.1175/waf-831.1.

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Abstract The objective consensus forecasting (OCF) system is an automated operational forecasting system that adapts to underlying numerical model upgrades within 30 days and generally outperforms direct model output (DMO) and model output statistics (MOS) forecasts. It employs routinely available DMO and MOS guidance combined after bias correction using a mean absolute error (MAE)-weighted average algorithm. OCF generates twice-daily forecasts of screen-level temperature maxima and minima, ground-level temperature minima, evaporation, sunshine hours, and rainfall and its probability for day 0

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4

Petreski, Marjan, Blagica Petreski, Despina Tumanoska, et al. "The Size and Effects of Emigration and Remittances in the Western Balkans. A Forecasting Based on a Delphi Process." Südosteuropa 65, no. 4 (2018): 679–95. http://dx.doi.org/10.1515/soeu-2017-0044.

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Abstract This paper aims at forecasting the size and effects of remittances and emigration in Macedonia, Albania, Serbia, and Kosovo, using a qualitative forecasting method, a Delphi questionnaire. The authors examined consensus building within and between two groups of respondents: ten experts and twenty remittance receivers per country, in three subsequent rounds–two on the same group and a third cross-round. Consensual results suggest that remittances in the projected five-year period will increase in Macedonia and Serbia, and will reduce in Albania and Kosovo. With less consensus, the resu

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5

Gregory, Allan W., and James Yetman. "The evolution of consensus in macroeconomic forecasting." International Journal of Forecasting 20, no. 3 (2004): 461–73. http://dx.doi.org/10.1016/s0169-2070(03)00064-5.

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6

Moutinho, Luiz, and Stephen F. Witt. "Forecasting the Tourism Environment Using a Consensus Approach." Journal of Travel Research 33, no. 4 (1995): 46–50. http://dx.doi.org/10.1177/004728759503300407.

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Sampson, Charles R., James L. Franklin, John A. Knaff, and Mark DeMaria. "Experiments with a Simple Tropical Cyclone Intensity Consensus." Weather and Forecasting 23, no. 2 (2008): 304–12. http://dx.doi.org/10.1175/2007waf2007028.1.

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Abstract Consensus forecasts (forecasts created by combining output from individual forecasts) have become an integral part of operational tropical cyclone track forecasting. Consensus aids, which generally have lower average errors than individual models, benefit from the skill and independence of the consensus members, both of which are present in track forecasting, but are limited in intensity forecasting. This study conducts experiments with intensity forecast aids on 4 yr of data (2003–06). First, the skill of the models is assessed; then simple consensus computations are constructed for

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8

Modrak, Vladimir, and Petre Bosun. "Using the Delphi Method in Forecasting Tourism Activity." International Letters of Social and Humanistic Sciences 25 (March 2014): 66–72. http://dx.doi.org/10.18052/www.scipress.com/ilshs.25.66.

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Delphi method is used to obtain usually medium or long-term forecasts, which involves establishing a consensus from a panel of experts asked to make estimates about the evolution of the economical phenomenon. If it cannot be obtain the wished consensus, the opinions having a certain degree of divergence, it aims to reduce as much of this dispersion, without a direct influence on the panel of experts, using a framework in which their expert feedback drive to the conclusion of the study. Of course there are some advantages and disadvantages of this method and these are presented in the article c

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9

Calitz, C. B., and E. V. D. M. Smit. "Die kombinering van ekonomiese vooruitskattings in die Suid-Afrikaanse konteks." South African Journal of Business Management 20, no. 4 (1989): 178–83. http://dx.doi.org/10.4102/sajbm.v20i4.960.

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In the literature on forecasting, consensus has been reached about improved forecasting accuracy brought about by the combination of two or more forecasts for a given variable. No consensus, however, exists about the exact way in which the various forecasts in the combination should be weighed. The evidence points towards simple weighing schemes. The present study utilizes South African macro-economic forecasts published by seven forecasters on eight variables to evaluate the benefits to be gained from combining forecasts and to evaluate the relative accuracy of a number of combination schemes

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Smirnov, S. V., N. V. Kondrashov, and A. S. Kachur. "Macroeconomic forecasting and macroeconomic forecasts." Voprosy Ekonomiki, no. 2 (February 6, 2024): 23–48. http://dx.doi.org/10.32609/0042-8736-2024-2-23-48.

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The specificity of macroeconomic forecasts is determined not so much by the list of predicted indicators or by mathematical tools used, but by the unavoidable human factor, which often generates great difference between forecasts made by various professionals. In Russian-language literature, this psychological aspect of macroeconomic forecasting has not received any attention; our work is designed to fill this gap. As a source of statistical data we used the forecasts extracted from the quarterly Poll of Professional Forecasters (PPF), which began in the first quarter of 2000. An analysis of r

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11

Folmer, Eelke O., Justus E. E. van Beusekom, Tobias Dolch, et al. "Consensus forecasting of intertidal seagrass habitat in the Wadden Sea." Journal of Applied Ecology 53, no. 6 (2016): 1800–1813. http://dx.doi.org/10.1111/1365-2664.12681.

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12

Zhu, Yiqun, Shuxian Sun, Chunyu Liu, Xinyi Tian, Jingyi He, and Shuai Xiao. "PoQ-Consensus Based Private Electricity Consumption Forecasting via Federated Learning." Computer Modeling in Engineering & Sciences 136, no. 3 (2023): 3285–97. http://dx.doi.org/10.32604/cmes.2023.026691.

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13

Duru, Augustine, and David M. Reeb. "International Diversification and Analysts' Forecast Accuracy and Bias." Accounting Review 77, no. 2 (2002): 415–33. http://dx.doi.org/10.2308/accr.2002.77.2.415.

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We investigate the association between corporate international diversification and the accuracy and bias of consensus analysts' earnings forecasts. We find that greater corporate international diversification is associated with less accurate and more optimistic forecasts. Our results suggest that international diversification reflects unique dimensions of forecasting difficulty that are not captured in previously identified determinants. This evidence suggests that as firms become more geographically diversified, forecasting their earnings becomes more complex.

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14

Chen, Tin-Chih Toly, and Hsin-Chieh Wu. "Forecasting the unit cost of a DRAM product using a layered partial-consensus fuzzy collaborative forecasting approach." Complex & Intelligent Systems 6, no. 3 (2020): 479–92. http://dx.doi.org/10.1007/s40747-020-00146-3.

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15

Krupkina, A. S., O. S. Vinogradova, E. A. Orlova, and E. N. Ershova. "Forecasting Russia’s GDP through the production method." Moscow University Economics Bulletin, no. 5 (October 3, 2022): 62–81. http://dx.doi.org/10.38050/01300105202254.

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The paper analyses the variables covering real, financial and external sectors of the economy alongside various sectoral, price and survey indicators. We have obtained forecast values of gross value added by industry and an aggregated estimate of Russia’s productionbased GDP. Drawing on dynamic factor model (DFM) as the main approach, we obtained quarterly point forecasts for production-based Russian GDP and for individual sectors for 2011-21. The forecast accuracy is compared to Bayesian vector autoregression (BVAR),s imple benchmarks based on aggregated and disaggregated GDP modeling and con

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16

Vidanage, Thushari N., Fabrizio Carmignani, and Tarlok Singh. "Predictability of Return Volatility Across Different Emerging Capital Markets: Evidence from Asia." South Asian Journal of Macroeconomics and Public Finance 6, no. 2 (2017): 157–77. http://dx.doi.org/10.1177/2277978717727172.

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The importance of return volatility forecasts in policy formation and investment decision-making in emerging countries is growing considerably. However, from an operational perspective, there is no consensus in the literature on which econometric model has the best forecasting performance. To shed new light on this issue, this article compares forecasting models for a selected group of emerging Asian economies: India, Malaysia, Pakistan, Sri Lanka, Singapore and Thailand. Model’s performance is tested using both in-sample and out-of-sample forecasting methods. It is found that a relatively sim

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Bekele, J. B., and O. E. Taylor. "Forecasting the Price of Cryptocurrency using an Integrated Consensus Mining System." International Journal of Computer Sciences and Engineering 11, no. 8 (2023): 9–14. https://doi.org/10.26438/ijcse/v11i8.914.

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18

Zickafoose, Alexis, Peng Lu, and Mathew Baker. "Forecasting Food Innovations with a Delphi Study." Foods 11, no. 22 (2022): 3723. http://dx.doi.org/10.3390/foods11223723.

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Food innovations can create novel nutritious food, improve agricultural sustainability, and increase the agri-food industry’s market profits. Our study proposes a consensus definition of food innovations and forecasts food innovations that will be available to consumers in the next five years by using a Delphi study. Thirteen experts aged 35 to 85 from the US and the UK researching or working in agriculture and nutrition, public health, the agri-food industry, or food policy participated in three rounds of this Delphi study. The experts were chosen using the snowball sampling method. This stud

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Chen, Toly. "A Fuzzy-Neural Approach with Collaboration Mechanisms for Semiconductor Yield Forecasting." International Journal of Intelligent Information Technologies 6, no. 3 (2010): 17–33. http://dx.doi.org/10.4018/jiit.2010070102.

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Yield forecasting is critical to a semiconductor manufacturing factory. To further enhance the effectiveness of semiconductor yield forecasting, a fuzzy-neural approach with collaboration mechanisms is proposed in this study. The proposed methodology is modified from Chen and Lin’s approach by incorporating two collaboration mechanisms: favoring mechanism and disfavoring mechanism. The former helps to achieve the consensus among multiple experts to avoid the missing of actual yield, while the latter shrinks the search region to increase the probability of finding out actual yield. To evaluate

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Ding, Jun, Wei Chong Choo, and Ng Keng Yap. "Achieving organizational consensus for the JD-R competency model: A judgmental forecasting system for engaging leadership." International Journal of ADVANCED AND APPLIED SCIENCES 12, no. 3 (2025): 143–61. https://doi.org/10.21833/ijaas.2025.03.015.

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This study develops an online support system tool based on the Job Demands-Resources (JD-R) model and Engaging Leadership theory to facilitate organizational consensus in evaluating and addressing job characteristics. Using a qualitative research design, including document analysis and the online Delphi method, it constructs a JD-R competency model within the framework of occupational health psychology. The study proposes the classical Delphi method to establish consensus and, in cases of disagreement, employs the Policy Delphi method to explore underlying differences. By integrating these met

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Mwangi, E., F. Wetterhall, E. Dutra, F. Di Giuseppe, and F. Pappenberger. "Forecasting droughts in East Africa." Hydrology and Earth System Sciences 18, no. 2 (2014): 611–20. http://dx.doi.org/10.5194/hess-18-611-2014.

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Abstract. The humanitarian crises caused by the recent droughts (2008–2009 and 2010–2011) in East Africa have illustrated that the ability to make accurate drought forecasts with sufficient lead time is essential. The use of dynamical model precipitation forecasts in combination with drought indices, such as the Standardized Precipitation Index (SPI), can potentially lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF

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22

Tushar Dasgupta. "Demand Planning and Forecasting: Technical Foundations for Supply Chain Excellence." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 3480–90. https://doi.org/10.32628/cseit25112812.

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Demand planning and forecasting represent critical capabilities in modern supply chain management, enabling organizations to anticipate customer needs while optimizing inventory investments and operational resources. This article explores the technical foundations of effective demand planning, including statistical frameworks, computational requirements, and advanced methodologies. Starting with baseline forecasting approaches, the discussion progresses through consensus planning architectures, hierarchical aggregation systems, and cross-functional integration mechanisms. The article then exam

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Kleňha, Jan. "Improving national strategic foresight with the use of forecasting tournaments and its implications for the study of international relations." Stosunki Międzynarodowe – International Relations 2 (January 21, 2022): 4. http://dx.doi.org/10.12688/stomiedintrelat.17424.1.

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Improving national strategic foresight can help the formation of more robust and informed policies, including foreign policy. Predicated upon the theory behind peer-prediction elicitation methods such as Reciprocal Scoring, we combined two foresight methods - Forecasting tournaments and a Delphi method - into a design in which a forecasting tournament predicted the results of a Delphi. Experts in a Delphi could take into account the arguments of participants from a prior forecasting tournament and thus make better-informed decisions. This methodological article aims to validate the feasibility

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HUANG, WEI, K. K. LAI, Y. NAKAMORI, and SHOUYANG WANG. "FORECASTING FOREIGN EXCHANGE RATES WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW." International Journal of Information Technology & Decision Making 03, no. 01 (2004): 145–65. http://dx.doi.org/10.1142/s0219622004000969.

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Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. Artificial neural networks (ANNs) have been widely used as a promising alternative approach for a forecasting task because of several distinguished features. Research efforts on ANNs for forecasting exchange rates are considerable. In this paper, we attempt to provide a survey of research in this area. Several design factors significantly impact the accuracy of neural network forecasts. These factors include the selection of input

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Niranjan, Hiranmayi, and Badrinath PR. "Exploring Advances in SC Forecasting Methods: A Conceptual Review." International Journal of Science, Engineering and Management 9, no. 3 (2022): 1–6. http://dx.doi.org/10.36647/ijsem/09.03.a001.

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The basis of Supply Chain Management (SCM) starts with accurate demand forecasting as harmonizing demand and supply is at the genesis of any operational plan. These forecasts determine every aspect of an organization from resource allocation to finished product distribution planning. Undeniably, if the demand forecasts are faulty this will have a negative impact on the Supply Chain (SC) therefore on the profits of the organization. This paper designs a conceptual review for factors involved in recent forecasting methodologies. Although the existing research has analyzed many theoretical perspe

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Khan, V. M. "Overview of current and expected seasonal climatic anomalies for the winter 2021/2022 with their possible impact on the economy, as estimated by the meteorological services of the CIS countries." Hydrometeorological research and forecasting 4 (December 16, 2021): 163–76. http://dx.doi.org/10.37162/2618-9631-2021-4-163-176.

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Based on assessments of the meteorological services of the CIS countries, the skill scores of the consensus forecast for the territory of Northern Eurasia for the summer of 2021 are presented. The results of monitoring circulation patterns in the stratosphere and troposphere over the past summer season are discussed. Climate monitoring and seasonal forecasting results for the current situation are presented. A probabilistic consensus forecast for air temperature and precipitation is presented for the upcoming winter season 2021/2022 in Northern Eurasia. Possible consequences of the impact of t

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Engel, Chermelle, and Elizabeth E. Ebert. "Gridded Operational Consensus Forecasts of 2-m Temperature over Australia." Weather and Forecasting 27, no. 2 (2012): 301–22. http://dx.doi.org/10.1175/waf-d-11-00069.1.

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Abstract This paper describes an extension of an operational consensus forecasting (OCF) scheme from site forecasts to gridded forecasts. OCF is a multimodel consensus scheme including bias correction and weighting. Bias correction and weighting are done on a scale common to almost all multimodel inputs (1.25°), which are then downscaled using a statistical approach to an approximately 5-km-resolution grid. Local and international numerical weather prediction model inputs are found to have coarse scale biases that respond to simple bias correction, with the weighted average consensus at 1.25°

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Thomas, Lloyd B. "Survey Measures of Expected U.S. Inflation." Journal of Economic Perspectives 13, no. 4 (1999): 125–44. http://dx.doi.org/10.1257/jep.13.4.125.

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The forecasting performance of widely accessible surveys of expected inflation are evaluated against naive and financial market benchmark forecasts. In the period of rising inflation (1960-80), the Michigan household consensus forecasts exhibited smaller errors than the Livingston Survey of economists and the benchmark forecasts. Unlike Livingston, the Michigan forecasts were unbiased. Since 1980, Livingston forecasts have been more accurate than Michigan, though unbiasedness is rejected in both cases. SPF forecasts, available since 1981, have been slightly superior to Livingston. In forecasti

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Roebber, Paul J. "Seeking Consensus: A New Approach." Monthly Weather Review 138, no. 12 (2010): 4402–15. http://dx.doi.org/10.1175/2010mwr3508.1.

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Abstract Simulated evolution is used to generate consensus forecasts of next-day minimum temperature for a site in Ohio. The evolved forecast algorithm logic is interpretable in terms of physics that might be accounted for by experienced forecasters, but the logic of the individual algorithms that form the consensus is unique. As a result, evolved program consensus forecasts produce substantial increases in forecast accuracy relative to forecast benchmarks such as model output statistics (MOS) and those from the National Weather Service (NWS). The best consensus produces a mean absolute error

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Cai, Zi Long, and Hong Chun Shu. "Long-Term Development Scale and Charging Load Forecasting of Electric Vehicle." Applied Mechanics and Materials 448-453 (October 2013): 3194–200. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.3194.

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Because of the energy crisis and environment deterioration, there is a general consensus about the development of new energy vehicle especially electric vehicle in the world. The development of electric vehicles has brought new challenges to the distribution network. The charging strategy, the location planning of electric vehicle charging stations and sizing, the coordination planning between electric vehicle and the distribution grid depends on the future development scale electric vehicles and charging load forecasting. Because there is a certain distance from commercial operation in china,

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Lombardi, Danielle R., Rebecca Bloch, and Miklos A. Vasarhelyi. "The Current State and Future of the Audit Profession." Current Issues in Auditing 9, no. 1 (2014): P10—P16. http://dx.doi.org/10.2308/ciia-50988.

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SUMMARY Audited financial statements are intended to be timely and useful in decision making. To remain a valuable and relevant service, auditing must find a way to evolve. This paper summarizes a recent study (“The Future of Audit,” Lombardi, Bloch, and Vasarhelyi [2014]), which conducts an interactive forecasting method to gain expert consensus on the current state of the auditing profession and on how the profession will evolve over the next decade. Expert consensus emerging from the study includes increasing automation of audit procedures, more predictive financial statements, continuous a

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Sampson, Charles R., James S. Goerss, John A. Knaff, Brian R. Strahl, Edward M. Fukada, and Efren A. Serra. "Tropical Cyclone Gale Wind Radii Estimates, Forecasts, and Error Forecasts for the Western North Pacific." Weather and Forecasting 33, no. 4 (2018): 1081–92. http://dx.doi.org/10.1175/waf-d-17-0153.1.

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Abstract In 2016, the Joint Typhoon Warning Center extended forecasts of gale-force and other wind radii to 5 days. That effort and a thrust to perform postseason analysis of gale-force wind radii for the “best tracks” (the quality controlled and documented tropical cyclone track and intensity estimates released after the season) have prompted requirements for new guidance to address the challenges of both. At the same time, operational tools to estimate and predict wind radii continue to evolve, now forming a quality suite of gale-force wind radii analysis and forecasting tools. This work pro

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Warren, Charles A., John A. Stern, Douglas R. Eddy, et al. "The Role of Event-Related Potentials in Human-Machine Applications." Proceedings of the Human Factors Society Annual Meeting 29, no. 10 (1985): 981–85. http://dx.doi.org/10.1177/154193128502901018.

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This paper has four aims: to provide a brief introduction to the topic; to indicate the consensus of the contributors concerning the nature and direction of the discussion; to characterize the contributors' attempts at understanding and forecasting some trends in event-related potential (ERP) research and applications, and, finally, to convey some degree of criticality regarding the papers to be presented.

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Durrant, Tom H., Frank Woodcock, and Diana J. M. Greenslade. "Consensus Forecasts of Modeled Wave Parameters." Weather and Forecasting 24, no. 2 (2009): 492–503. http://dx.doi.org/10.1175/2008waf2222143.1.

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Abstract The use of numerical guidance has become integral to the process of modern weather forecasting. Using various techniques, postprocessing of numerical model output has been shown to mitigate some of the deficiencies of these models, producing more accurate forecasts. The operational consensus forecast scheme uses past performance to bias-correct and combine numerical forecasts to produce an improved forecast at locations where recent observations are available. This technique was applied to forecasts of significant wave height (Hs), peak period (Tp), and 10-m wind speed (U10) from 10 n

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Khan, V. M. "Outcomes of the 27th session of the North Eurasian Climate Outlook Forum combined with the UN ESCAP workshop." Hydrometeorological research and forecasting 4 (December 20, 2024): 163–78. https://doi.org/10.37162/2618-9631-2024-4-163-178.

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The North Eurasian Climate Centre held the 27th session of the North Eurasian Climate Outlook Forum (NEACOF-27) combined with a workshop under the auspices of the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), as a parallel section within the 8th All-Russian Joint Meteorological and Hydrological Congress. The joint event served as an important platform for the exchange of knowledge and experience in the field of climate research, seasonal forecasting and adaptation to climate change, which emphasized its importance for regional cooperation. During the forum, a

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Salamouris, Ioannis S., and Yaz Gulnur Muradoglu. "Estimating analyst's forecast accuracy using behavioural measures (Herding) in the United Kingdom." Managerial Finance 36, no. 3 (2010): 234–56. http://dx.doi.org/10.1108/03074351011019564.

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PurposeThe purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.Design/methodology/approachTwo alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible bia

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Khan, V. M., R. M. Vilfand, V. A. Tishchenko, et al. "Outcomes of 25th session of the North Eurasian Climate Outlook Forum combined with the project inception regional workshop under the auspices of the UN ESCAP: Enhancing knowledge and capacity to build resilience to slow-onset disasters in Central Asia / Khan V.M., Vilfand R.M., Tishchenko V.A., Sumerova K.A., Emelina S.V., Nabokova E.V., Kaverina E.S.,. Kulikova I.A, Kruglova E.N., Tolstykh M.A. // Hydrometeorological Research and Forecasting, 2023, no. 4 (390), pp. 154-169." Hydrometeorological research and forecasting 4 (December 15, 2023): 154–69. http://dx.doi.org/10.37162/2618-9631-2023-4-154-169.

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The North Eurasian Climate Center held the 25th session of the North Eurasian Climate Outlook Forum (NEACOF-25) combined with the project inception regional workshop under the auspices of the UN Economic and Social Commission for Asia and the Pacific (ESCAP). In total, 143 participants from 12 countries were registered at the event, 60 of them took part in the forum in person. During NEACOF-25, a consensus forecast of air temperature and precipitation anomalies for the territory of Northern Eurasia for the winter of 2023/2024 was presented. The NEACOF-25 consensus forecast is in agreement with

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Khan, V. M., R. M. Vilfand, V. A. Tishchenko, et al. "Outcomes of 25th session of the North Eurasian Climate Outlook Forum combined with the project inception regional workshop under the auspices of the UN ESCAP: Enhancing knowledge and capacity to build resilience to slow-onset disasters in Central Asia / Khan V.M., Vilfand R.M., Tishchenko V.A., Sumerova K.A., Emelina S.V., Nabokova E.V., Kaverina E.S.,. Kulikova I.A, Kruglova E.N., Tolstykh M.A. // Hydrometeorological Research and Forecasting, 2023, no. 4 (390), pp. 154-169." Hydrometeorological research and forecasting 4 (December 15, 2023): 154–69. http://dx.doi.org/10.37162/2618-9631-2023-4-154-169.

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The North Eurasian Climate Center held the 25th session of the North Eurasian Climate Outlook Forum (NEACOF-25) combined with the project inception regional workshop under the auspices of the UN Economic and Social Commission for Asia and the Pacific (ESCAP). In total, 143 participants from 12 countries were registered at the event, 60 of them took part in the forum in person. During NEACOF-25, a consensus forecast of air temperature and precipitation anomalies for the territory of Northern Eurasia for the winter of 2023/2024 was presented. The NEACOF-25 consensus forecast is in agreement with

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Salamanis, Athanasios I., Georgia Xanthopoulou, Napoleon Bezas, et al. "Benchmark Comparison of Analytical, Data-Based and Hybrid Models for Multi-Step Short-Term Photovoltaic Power Generation Forecasting." Energies 13, no. 22 (2020): 5978. http://dx.doi.org/10.3390/en13225978.

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Accurately forecasting power generation in photovoltaic (PV) installations is a challenging task, due to the volatile and highly intermittent nature of solar-based renewable energy sources. In recent years, several PV power generation forecasting models have been proposed in the relevant literature. However, there is no consensus regarding which models perform better in which cases. Moreover, literature lacks of works presenting detailed experimental evaluations of different types of models on the same data and forecasting conditions. This paper attempts to fill in this gap by presenting a com

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Yao, Yanyun, Xiutian Zheng, and Huimin Wang. "Predictability of China’s Stock Market Returns Based on Combination of Distribution Forecasting Models." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 4 (2020): 477–87. http://dx.doi.org/10.20965/jaciii.2020.p0477.

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No consensus exists in the literature on whether stock prices can be predicted, with most existing studies employing point forecasting to predict returns. By contrast, this study adopts the new perspective of distribution forecasting to investigate the predictability of the stock market using the model combination strategy. Specifically, the Shanghai Composite Index and the Shenzhen Component Index are selected as research objects. Seven models – GARCH-norm, GARCH-sstd, EGARCH-sstd, EGARCH-sstd-M, one-component Beta-t-EGARCH, two-component Beta-t-EGARCH, and the EWMA-based nonparametric model

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Aras, Serkan, and Emrah Gülay. "A new consensus between the mean and median combination methods to improve forecasting accuracy." Serbian Journal of Management 12, no. 2 (2017): 217–36. http://dx.doi.org/10.5937/sjm12-13091.

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Zhang, Lei, Shirong Liu, Pengsen Sun, et al. "Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties." PLOS ONE 10, no. 3 (2015): e0120056. http://dx.doi.org/10.1371/journal.pone.0120056.

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Vassallo, Daniel, Raghavendra Krishnamurthy, Thomas Sherman, and Harindra J. S. Fernando. "Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting." Energies 13, no. 20 (2020): 5488. http://dx.doi.org/10.3390/en13205488.

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Although the random forest (RF) model is a powerful machine learning tool that has been utilized in many wind speed/power forecasting studies, there has been no consensus on optimal RF modeling strategies. This study investigates three basic questions which aim to assist in the discernment and quantification of the effects of individual model properties, namely: (1) using a standalone RF model versus using RF as a correction mechanism for the persistence approach, (2) utilizing a recursive versus direct multi-step forecasting strategy, and (3) training data availability on model forecasting ac

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Bloomfield, Robert, and Jeffrey Hales. "An Experimental Investigation of the Positive and Negative Effects of Mutual Observation." Accounting Review 84, no. 2 (2009): 331–54. http://dx.doi.org/10.2308/accr.2009.84.2.331.

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ABSTRACT: We use two experiments to test predictions about the positive and negative impacts of allowing analysts to revise their forecasts in light of the consensus forecasts. We find that such mutual observation not only facilitates information aggregation, but also induces free riding, which offsets the benefits of information aggregation unless incentives for accuracy are high. In our second experiment, we find that participants acting as investors anticipate these effects in the consensus and adjust their own forecasts accordingly. Our study demonstrates that the positive and negative eff

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Sampson, Charles R., James S. Goerss, and Harry C. Weber. "Operational Performance of a New Barotropic Model (WBAR) in the Western North Pacific Basin." Weather and Forecasting 21, no. 4 (2006): 656–62. http://dx.doi.org/10.1175/waf939.1.

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Abstract The Weber barotropic model (WBAR) was originally developed using predefined 850–200-hPa analyses and forecasts from the NCEP Global Forecasting System. The WBAR tropical cyclone (TC) track forecast performance was found to be competitive with that of more complex numerical weather prediction models in the North Atlantic. As a result, WBAR was revised to incorporate the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecasts for use at the Joint Typhoon Warning Center (JTWC). The model was also modified to analyze its own storm-dependent deep-layer mean fi

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Cole, S. "World Bank Forecasts and Planning in the Third World." Environment and Planning A: Economy and Space 21, no. 2 (1989): 175–96. http://dx.doi.org/10.1068/a210175.

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The growth forecasts of the World Bank have become increasingly influential for the planning efforts of developing countries. However, after reviewing these forecasts this author concludes that the projections of the Bank for the economic growth rates both of the industrial and of the developing countries are systematically biased, and its estimates of the locomotive effect for developing countries are ambiguous. A similar pattern is reflected in the forecasts of the major United Nations agencies, in particular the Secretariat and UNCTAD. These forecasts are not readily explained by the data p

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Sánchez-Herrero, Sergio, Abtin Tondar, Elena Perez-Bernabeu, Laura Calvet, and Angel A. Juan. "Forecasting Survival Rates in Metastatic Colorectal Cancer Patients Undergoing Bevacizumab-Based Chemotherapy: A Machine Learning Approach." BioMedInformatics 4, no. 1 (2024): 733–53. http://dx.doi.org/10.3390/biomedinformatics4010041.

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Background: Antibiotics can play a pivotal role in the treatment of colorectal cancer (CRC) at various stages of the disease, both directly and indirectly. Identifying novel patterns of antibiotic effects or responses in CRC within extensive medical data poses a significant challenge that can be addressed through algorithmic approaches. Machine Learning (ML) emerges as a promising solution for predicting clinical outcomes using clinical and heterogeneous cancer data. In the pursuit of our objective, we employed ML techniques for predicting CRC mortality and antibiotic influence. Methods: We ut

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Goerss, James S., and Charles R. Sampson. "Prediction of Consensus Tropical Cyclone Intensity Forecast Error." Weather and Forecasting 29, no. 3 (2014): 750–62. http://dx.doi.org/10.1175/waf-d-13-00058.1.

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Abstract The extent to which the tropical cyclone (TC) intensity forecast error of IVCN and S5YY, consensus models routinely used by forecasters at the National Hurricane Center and the Joint Typhoon Warning Center, respectively, can be predicted is determined. A number of predictors of consensus intensity forecast error, which must be quantities that are available prior to the official forecast deadline, were examined for the Atlantic and eastern North Pacific basins for 2008–11 and the western North Pacific basin for 2012. Leading predictors were found to be forecast TC intensity and intensi

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Goerss, James S. "Prediction of Consensus Tropical Cyclone Track Forecast Error." Monthly Weather Review 135, no. 5 (2007): 1985–93. http://dx.doi.org/10.1175/mwr3390.1.

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Abstract The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, which must be quantities that are available prior to the official forecast deadline, were examined for the Atlantic basin in 2001–03. Leading predictors were found to be consensus model spread, defined to be the average distance of the member forecasts from the consensus forecast, and initial and forecast TC intensity. Using stepwise linear re

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Rahmawati, Rahmawati, and Soenarto Soenarto. "Use of the Delphy Technique: a case for the development of ecotourism in western Lombok." Jurnal Pendidikan Vokasi 9, no. 1 (2019): 92–104. http://dx.doi.org/10.21831/jpv.v9i1.23320.

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Delphi technique was developed in 1950 by researchers at the Rand Corporation led by Norman Delkey and Olaf Helmer and has since been used in hundreds of businesses forecasting in the public and private sectors. Delphi technique is a judgmental forecasting procedure for obtaining, exchanging, and developing an informed opinion about future events. Therefore, the Delphi technique is a systematic way to get a consensus of opinion among the experts who have related interests through a panel discussion. The objective of most Delphi is the reliable and creative exploration of ideas or the productio

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