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Journal articles on the topic 'Recruitment forecasting'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Scanlon, Jacob R., and Matthew S. Gerber. "Forecasting Violent Extremist Cyber Recruitment." IEEE Transactions on Information Forensics and Security 10, no. 11 (2015): 2461–70. http://dx.doi.org/10.1109/tifs.2015.2464775.

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Subbey, Sam, Jennifer A. Devine, Ute Schaarschmidt, and Richard D. M. Nash. "Modelling and forecasting stock–recruitment: current and future perspectives." ICES Journal of Marine Science 71, no. 8 (2014): 2307–22. http://dx.doi.org/10.1093/icesjms/fsu148.

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AbstractThis paper presents a brief review of the present state of knowledge in stock–recruitment forecasting, including process and current methodological challenges to predicting stock–recruitment. The discussion covers the apparent inability of models to accurately forecast recruitment even when environmental covariates are included as explanatory variables. The review shows that despite the incremental success in the past hundred years, substantial challenges remain if the process of modelling and forecasting stock–recruitment is to become relevant to fisheries science and management in th

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Ottersen, Geir, and Geir Huse. "Forecasting recruitment and stock biomass of Northeast Arctic cod using neural networks." Scientia Marina 67, S1 (2003): 325–35. http://dx.doi.org/10.3989/scimar.2003.67s1325.

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Van Beveren, Elisabeth, Hugues P. Benoît, and Daniel E. Duplisea. "Forecasting fish recruitment in age‐structured population models." Fish and Fisheries 22, no. 5 (2021): 941–54. http://dx.doi.org/10.1111/faf.12562.

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Schweigert, Jacob F., Douglas E. Hay, Thomas W. Therriault, Matthew Thompson, and Carl W. Haegele. "Recruitment forecasting using indices of young-of-the-year Pacific herring (Clupea pallasi) abundance in the Strait of Georgia (BC)." ICES Journal of Marine Science 66, no. 8 (2009): 1681–87. http://dx.doi.org/10.1093/icesjms/fsp182.

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Abstract Schweigert, J. F., Hay, D. E., Therriault, T. W., Thompson, M., and Haegele, C. W. 2009. Recruitment forecasting using indices of young-of-the-year Pacific herring (Clupea pallasi) abundance in the Strait of Georgia (BC). – ICES Journal of Marine Science, 66: 1681–1687. Within the Strait of Georgia (BC, Canada), recruitment of Pacific herring (Clupea pallasi) to the spawning stock at age 3 can be highly variable, and this component may compose a major portion of the spawning-stock biomass. Therefore, a reliable method of forecasting recruitment strength would be useful for determining

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Kimoto, A., T. Mouri, and T. Matsuishi. "Modelling stock–recruitment relationships to examine stock management policies." ICES Journal of Marine Science 64, no. 5 (2007): 870–77. http://dx.doi.org/10.1093/icesjms/fsm054.

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Abstract Kimoto, A., Mouri, T., and Matsuishi, T. 2007. Modelling stock–recruitment relationships to examine stock management policies. – ICES Journal of Marine Science, 64: 870–877. Simulation studies are used widely for fish stock management. In such studies, forecasting future recruitment, which can vary greatly between years, has become an essential part of evaluating management strategies. We propose a new forecasting algorithm to predict recruitment for short- or medium-term stochastic projections, using a stock–recruitment relationship. We address cases in which the spawning stock has d

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Kiaer, Christian, Stefan Neuenfeldt, and Mark R. Payne. "A framework for assessing the skill and value of operational recruitment forecasts." ICES Journal of Marine Science 78, no. 10 (2021): 3581–91. http://dx.doi.org/10.1093/icesjms/fsab202.

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Abstract Forecasting variation in the recruitment to fish stocks is one of the most challenging and long-running problems in fisheries science and essentially remains unsolved today. Traditionally, recruitment forecasts are developed and evaluated based on explanatory and goodness-of-fit approaches that do not reflect their ability to predict beyond the data on which they were developed. Here, we propose a new generic framework that allows the skill and value of recruitment forecasts to be assessed in a manner that is relevant to their potential use in an operational setting. We assess forecas

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Mark, Payne, Egan Afra, MM Fässler Sascha, et al. "The rise and fall of the NE Atlantic blue whiting (Micromesistius poutassou)." Marine Biology Research 8, no. 5-6 (2012): 475–87. https://doi.org/10.1080/17451000.2011.639778.

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The Northeast Atlantic blue whiting (Micromesistius poutassou) stock has undergone striking changes in abundance in the last 15 years. The stock increased dramatically in the late 1990s due to a succession of eight unusually strong year classes and dropped again equally dramatically after 2005 when the recruitment collapsed to former levels. The North Atlantic subpolar gyre has previously been shown to have a strong influence on the behaviour of this stock: synchronous changes in the gyre and recruitment suggest a causal linkage and the possibility of forecasting recruitment. A range of mechan

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Laurel, Benjamin J., David Cote, Robert S. Gregory, Lauren Rogers, Halvor Knutsen, and Esben Moland Olsen. "Recruitment signals in juvenile cod surveys depend on thermal growth conditions." Canadian Journal of Fisheries and Aquatic Sciences 74, no. 4 (2017): 511–23. http://dx.doi.org/10.1139/cjfas-2016-0035.

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Coastal seine surveys contain some of the only direct measures of age-0 abundance for Atlantic cod (Gadus morhua) and Pacific cod (Gadus macrocephalus), yet their utility in forecasting future year-class strength has not been evaluated among regions. We analyzed coastal time series from the Gulf of Alaska, Newfoundland, and Norway to test the hypothesis that recruitment signals are stronger when assessed under thermal conditions that provide high juvenile growth potential. Weaker recruitment signals were associated with low growth potential from cold winters (Newfoundland) and recent warmer su

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Pierre, Maud, Tristan Rouyer, Sylvain Bonhommeau, and J. M. Fromentin. "Assessing causal links in fish stock–recruitment relationships." ICES Journal of Marine Science 75, no. 3 (2017): 903–11. http://dx.doi.org/10.1093/icesjms/fsx202.

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Abstract Understanding whether recruitment fluctuations in fish stock arise from stochastic forcing (e.g. environmental variations) rather than deterministic forces (e.g. intrinsic dynamics) is a long standing question with important applied consequences for fisheries ecology. In particular, the relationship between recruitment, spawning stock biomass and environmental factors is still poorly understood, even though this aspect is crucial for fisheries management. Fisheries data are often short, but arise from complex dynamical systems with a high degree of stochastic forcing, which are diffic

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Haltuch, Melissa A., Z. Teresa A’mar, Nicholas A. Bond, and Juan L. Valero. "Assessing the effects of climate change on US West Coast sablefish productivity and on the performance of alternative management strategies." ICES Journal of Marine Science 76, no. 6 (2019): 1524–42. http://dx.doi.org/10.1093/icesjms/fsz029.

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Abstract US West Coast sablefish are economically valuable, with landings of 11.8 million pounds valued at over $31 million during 2016, making assessing and understanding the impact of climate change on the California Current (CC) stock a priority for (1) forecasting future stock productivity, and (2) testing the robustness of management strategies to climate impacts. Sablefish recruitment is related to large-scale climate forcing indexed by regionally correlated sea level (SL) and zooplankton communities that pelagic young-of-the-year sablefish feed upon. This study forecasts trends in futur

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Chen, D. G., and D. M. Ware. "A neural network model for forecasting fish stock recruitment." Canadian Journal of Fisheries and Aquatic Sciences 56, no. 12 (1999): 2385–96. http://dx.doi.org/10.1139/f99-178.

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A neural network model is developed to forecast the recruiting biomass of fish. The west coast of Vancouver Island, British Columbia, Pacific herring (Clupea pallasi) stock is selected as an example application based on data compiled from long-term ecosystem research and stock assessment programs. A fuzzy logic decision procedure was used to evaluate all possible neural networks. The output from the two "optimal" networks was compared with the output from a multiple regression analysis and a standard Ricker climate stock-recruitment model. The performance of the neural network models in reprod

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Gurtov, V. A., N. Yu Garifullina, and S. V. Sigova. "Forecasting recruitment needs of the Russian economy: Qualitative aspects." Studies on Russian Economic Development 27, no. 1 (2016): 68–75. http://dx.doi.org/10.1134/s1075700716010044.

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Mohan raj, R., R. Siva, and C. Anbalagan. "MACHINE LEARNING IN FINANCIAL FORECASTING: OPPORTUNITIES AND CHALLENGES." ASET Journal of Management Science 4, no. 2 (2025): 78–86. https://doi.org/10.47059/ajms/v4i2/09.

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AIM In contrast to conventional approaches, this study examines how AI-driven recruitment platforms affect organizational hiring expenses. The study uses a mixed-methods approach, integrating qualitative information from semi-structured interviews with quantitative datafromsurveys of recruiting managers and HR experts. In addition to examining the perceivedadvantages and difficulties of both recruitment strategies, this data is examined to evaluatecost parameters including time-to-hire, cost-per-hire, and administrative overhead.MATERIALSAND METHODS: To acquire thorough data on recruitment exp

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Walters, Carl J. "Value of Short-Term Forecasts of Recruitment Variation for Harvest Management." Canadian Journal of Fisheries and Aquatic Sciences 46, no. 11 (1989): 1969–76. http://dx.doi.org/10.1139/f89-247.

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The expected improvement in management performance due to using short-term forecasts can be assessed with stochastic dynamic programming. Numerical studies on test cases indicate that this improvement depends strongly on average productivity and on the flexibility of the inseason regulatory system that is used to adjust stock size estimates and target harvests within each year. For productive stocks that are managed with flexible inseason systems, such as larger Pacific salmon stocks, only modest improvements in average yield (5–10%) can be expected from improved forecasting. Very large (30–50

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Lee, Yong-Woo, Bernard A. Megrey, and S. Allen Macklin. "Evaluating the performance of Gulf of Alaska walleye pollock (Theragra chalcogramma) recruitment forecasting models using a Monte Carlo resampling strategy." Canadian Journal of Fisheries and Aquatic Sciences 66, no. 3 (2009): 367–81. http://dx.doi.org/10.1139/f08-203.

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Multiple linear regressions (MLRs), generalized additive models (GAMs), and artificial neural networks (ANNs) were compared as methods to forecast recruitment of Gulf of Alaska walleye pollock ( Theragra chalcogramma ). Each model, based on a conceptual model, was applied to a 41-year time series of recruitment, spawner biomass, and environmental covariates. A subset of the available time series, an in-sample data set consisting of 35 of the 41 data points, was used to fit an environment-dependent recruitment model. Influential covariates were identified through statistical variable selection

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Ostrovsky, V. I. "Methodological aspects of the stock-recruitment curve analysis." Izvestiya TINRO 201, no. 1 (2021): 219–59. http://dx.doi.org/10.26428/1606-9919-2021-201-219-259.

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Choosing of mathematical model for describing of the pacific salmon progeny dependence on the parents abundance is discussed. Results of different approximations are interpreted. The analysis could be useful for forecasting of the pacific salmon stocks by specialists without deep skills in numerical modeling (like the author).

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Palanggi, Andi, Edi Jusriadi, and Yusuf Alfian Rendra Anggoro. "Human Resource Procurement Strategy in Empowering Local Labor in Luwu District (Case Study of PT. Bumi Mineral Sulawesi)." Journal of Public Representative and Society Provision 5, no. 3 (2025): 502–11. https://doi.org/10.55885/jprsp.v5i3.591.

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This study aims to analyze the strategy of human resource procurement through forecasting needs and recruitment and selection carried out by PT. Bumi Mineral Sulawesi. This type of research is descriptive with a qualitative approach using case studies. The informants in this study amounted to 8 people. The data collection techniques used were Observation, interviews, documentary techniques and field note techniques. Data analysis in this study was Data condensing, data display and drawing conclusions. The results of the study showed that in the process of forecasting workforce needs at PT. BMS

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Stocker, M., and D. J. Noakes. "Evaluating Forecasting Procedures for Predicting Pacific Herring (Clupea harengus pallasi) Recruitment in British Columbia." Canadian Journal of Fisheries and Aquatic Sciences 45, no. 6 (1988): 928–35. http://dx.doi.org/10.1139/f88-114.

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The ability of four forecasting methods to generate one-step-ahead forecasts of Pacific herring (Clupea harengus pillasi) recruitment is considered in this paper. Recruitment time series for five coastal stocks and various environmental time series are employed in the analyses. Information up to and including time t is employed to estimate the parameters of each model used to forecast recruitment in year t + 1. Parameter estimates are then updated after each time step with a total of seven one-step-ahead forecasts being generated by each model for each stock. The forecast errors are compared u

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RUPP, DAVID E., THOMAS C. WAINWRIGHT, PETER W. LAWSON, and WILLIAM T. PETERSON. "Marine environment-based forecasting of coho salmon (Oncorhynchus kisutch) adult recruitment." Fisheries Oceanography 21, no. 1 (2011): 1–19. http://dx.doi.org/10.1111/j.1365-2419.2011.00605.x.

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OSAZEVBARU, Henry, OKWUISE U. Young, and AKPOMIEMIE, Peter. "HUMAN RESOURCES PLANNING AND ORGANIZATIONAL PERFORMANCE: TELECOMS IN FOCUS." International Journal of Management & Entrepreneurship Research 5, no. 8 (2023): 554–75. http://dx.doi.org/10.51594/ijmer.v5i8.519.

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The study examined the relationship between human resource planning and the organizational performance of telecom companies in Delta State. The objectives of the study were to; ascertain the relationship between workforce forecasting and organizational performance; determine the relationship between recruitment and selection and organizational performance; examine the relationship between employee training and development and organizational performance and determine the relationship between employee retention and organizational performance. The study employed a cross-sectional research design.

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Kao, Ming-Chih J., Charles C. Koo, Kazuko Shem, Jerry A. Wright, and Lily Yang. "Poster 79 Health Research Economics of Patient Recruitment: Probabilistic Modeling of Multicenter Clinical Trial Recruitment for Cost Forecasting." PM&R 3 (September 2011): S167. http://dx.doi.org/10.1016/j.pmrj.2011.08.033.

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23

Crecco, Victor, Thomas Savoy, and Walter Whitworth. "Effects of Density-Dependent and Climatic Factors on American shad, Alosa sapidissima, Recruitment: A Predictive Approach." Canadian Journal of Fisheries and Aquatic Sciences 43, no. 2 (1986): 457–63. http://dx.doi.org/10.1139/f86-056.

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We developed environment-dependent stock–recruitment models for American shad, Alosa sapidissima, in the Connecticut River to forecast recruitment variability and measure density-dependent effects. These models were fitted to the 1966–78 stock–recruitment estimates and to May and June river flow, water temperature, and rainfall data shown previously to affect American shad year-class strength. We also attempted to validate the models by forecasting the 1979–84 year-classes based on juvenile indices, parent stock size, and hydrographic data for these years. The stock–recruitment models without

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McDonald, Joshua L., Edward D. White, Raymond R. Hill, and Christian Pardo. "Forecasting US Army enlistment contract production in complex geographical marketing areas." Journal of Defense Analytics and Logistics 1, no. 1 (2017): 69–87. http://dx.doi.org/10.1108/jdal-03-2017-0001.

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Purpose The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker. Research limitations/implications This work will successfully inform the US Army recruiting leadership on how this improved methodology will improv

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Perälä, Tommi A., Douglas P. Swain, and Anna Kuparinen. "Examining nonstationarity in the recruitment dynamics of fishes using Bayesian change point analysis." Canadian Journal of Fisheries and Aquatic Sciences 74, no. 5 (2017): 751–65. http://dx.doi.org/10.1139/cjfas-2016-0177.

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Marine ecosystems can undergo regime shifts, which result in nonstationarity in the dynamics of the fish populations inhabiting them. The assumption of time-invariant parameters in stock–recruitment models can lead to severe errors when forecasting renewal ability of stocks that experience shifts in their recruitment dynamics. We present a novel method for fitting stock–recruitment models using the Bayesian online change point detection algorithm, which is able to cope with sudden changes in the model parameters. We validate our method using simulations and apply it to empirical data of four d

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Bénézech, Mathilde, Hilaire Drouineau, Anthony Acou, et al. "Testing novel methods for short-term forecasting of European glass eel recruitment." Fisheries Research 271 (March 2024): 106915. http://dx.doi.org/10.1016/j.fishres.2023.106915.

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Megrey, Bernard A., Yong-Woo Lee, and S. Allen Macklin. "Comparative analysis of statistical tools to identify recruitment–environment relationships and forecast recruitment strength." ICES Journal of Marine Science 62, no. 7 (2005): 1256–69. http://dx.doi.org/10.1016/j.icesjms.2005.05.018.

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Abstract Many of the factors affecting recruitment in marine populations are still poorly understood, complicating the prediction of strong year classes. Despite numerous attempts, the complexity of the problem often seems beyond the capabilities of traditional statistical analysis paradigms. This study examines the utility of four statistical procedures to identify relationships between recruitment and the environment. Because we can never really know the parameters or underlying relationships of actual data, we chose to use simulated data with known properties and different levels of measure

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Bailey, KM, T. Zhang, Ks Chan, SM Porter, and AB Dougherty. "Near real-time forecasting of recruitment from larval surveys: application to Alaska pollock." Marine Ecology Progress Series 452 (April 25, 2012): 205–17. http://dx.doi.org/10.3354/meps09614.

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Okamura, Hiroshi, Shoko Morita, and Hiroshi Kuroda. "Forecasting fish recruitment using machine learning methods: A case study of arabesque greenling." Fisheries Research 278 (October 2024): 107096. http://dx.doi.org/10.1016/j.fishres.2024.107096.

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Fernandes, Jose A., Jose A. Lozano, Iñaki Inza, Xabier Irigoien, Aritz Pérez, and Juan D. Rodríguez. "Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting." Environmental Modelling & Software 40 (February 2013): 245–54. http://dx.doi.org/10.1016/j.envsoft.2012.10.001.

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Le Pape, Olivier, Youen Vermard, Jérome Guitton, et al. "The use and performance of survey-based pre-recruit abundance indices for possible inclusion in stock assessments of coastal-dependent species." ICES Journal of Marine Science 77, no. 5 (2020): 1953–65. http://dx.doi.org/10.1093/icesjms/fsaa051.

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Abstract We reviewed the use of survey-based pre-recruit abundance indices in short-term recruitment forecasts for fish species relying on coastal habitats at the juvenile stage and that are assessed by ICES. We collated information from stock assessment reports and from a questionnaire filled out by the stock assessors. Among the 78 stocks with juvenile coastal dependence, 49 use short-term forecasts in stock assessment. Survey-based pre-recruit abundance indices were available for 35 of these stocks, but only 14 were used to forecast recruitment. The questionnaire indicated that the limited

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Pal, Supriya, and Mohammed Amine Chabane. "Inclusion of Artificial Intelligence in the Recruitment Process in the Indian Corporate Sector." Liberal Studies 3, no. 2 (2018): 245–58. https://doi.org/10.5281/zenodo.3592693.

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As the Indian corporate sector is moving towards digitization, one observes an immense potential for the utilization of artificial intelligence in the human resource department, especially in recruitment. This research paper will be analyzing the future applications of Artificial Intelligence (AI) in the recruitment process and also, how this technology can/will reshape the ‘human resources department’ (HRD) holistically. The analysis will also be done in order to explore the strength and weakness of the existing corporate sector, to be more precise, the HRD dynamics in accepting A

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Pritt, Jeremy J., Edward F. Roseman, and Timothy P. O'Brien. "Mechanisms driving recruitment variability in fish: comparisons between the Laurentian Great Lakes and marine systems." ICES Journal of Marine Science 71, no. 8 (2014): 2252–67. http://dx.doi.org/10.1093/icesjms/fsu080.

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Abstract In his seminal work, Hjort (in Fluctuations in the great fisheries of Northern Europe. Conseil Parmanent International Pour L'Exploration De La Mar. Rapports et Proces-Verbaux, 20: 1–228, 1914) observed that fish population levels fluctuated widely, year-class strength was set early in life, and egg production by adults could not alone explain variability in year-class strength. These observations laid the foundation for hypotheses on mechanisms driving recruitment variability in marine systems. More recently, researchers have sought to explain year-class strength of important fish in

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Ambala, Dr Srinivas. "PlaceMentor: An Intelligent Analytical Platform for College Placements." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46009.

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Abstract— The digitization of campus recruitment and placement systems is reshaping how educational institutions manage hiring processes. This research presents PlaceMentor, a Django-based analytical platform built to streamline and enhance college placement activities using data-driven techniques and modern web technologies. The platform enables administrators and placement officers to manage historical placement data, forecast recruitment trends using regression analysis, and extract in-demand skills through text processing. Notable features include resume parsing, clustering of students bas

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Balan, Oleksandr, Hennadii Moskalyk, Khrystyna Peredalo, Olena Hurman, Illia Samarchenko, and Frol Revin. "USING THE PATTERN METHOD FOR THE COMPREHENSIVE ORGANIZATION OF RECRUITMENT AND SELECTION OF PERSONNEL." International Journal of Advanced Research in Engineering and Technology (IJARET) 11, no. 4 (2020): 290–300. https://doi.org/10.5281/zenodo.13996889.

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This article presents the PATTERN system analysis technique used for scientific and technical analysis and forecasting the development and use of complex systems resources. The methodology is considered from the point of view of its application in the economic systems of strategic planning of the company in personnel matters of recruitment.The basic principles that are the key points in the formation of an effective staffing system in terms of the strategic goals of the company are stated. The algorithm of formation of the personnel policy of the company is considered, from the position of the

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Balan, Oleksandr, Hennadii Moskalyk, Khrystyna Peredalo, Olena Hurman, Illia Samarchenko, and Frol Revin. "USING THE PATTERN METHOD FOR THE COMPREHENSIVE ORGANIZATION OF RECRUITMENT AND SELECTION OF PERSONNEL." International Journal of Advanced Research in Engineering and Technology (IJARET) 11, no. 4 (2020): 290–300. https://doi.org/10.5281/zenodo.13996915.

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This article presents the PATTERN system analysis technique used for scientific and technical analysis and forecasting the development and use of complex systems resources. The methodology is considered from the point of view of its application in the economic systems of strategic planning of the company in personnel matters of recruitment.The basic principles that are the key points in the formation of an effective staffing system in terms of the strategic goals of the company are stated. The algorithm of formation of the personnel policy of the company is considered, from the position of the

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PAINTING, S. J., L. HUTCHINGS, J. A. HUGGETT, J. L. KORRÛBEL, A. J. RICHARDSON, and And H. M. VERHEYE. "Environmental and biological monitoring for forecasting anchovy recruitment in the southern Benguela upwelling region." Fisheries Oceanography 7, no. 3‐4 (1998): 364–74. http://dx.doi.org/10.1046/j.1365-2419.1998.00086.x.

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Brock, K., L. Billingham, L. Crack, S. Popat, and G. Middleton. "186: Forecasting patient recruitment for time-to-event analysis in National Lung Matrix Trial." Lung Cancer 87 (January 2015): S69. http://dx.doi.org/10.1016/s0169-5002(15)50180-3.

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Koenigstein, Stefan, Flemming T. Dahlke, Martina H. Stiasny, Daniela Storch, Catriona Clemmesen, and Hans-Otto Pörtner. "Forecasting future recruitment success for Atlantic cod in the warming and acidifying Barents Sea." Global Change Biology 24, no. 1 (2017): 526–35. http://dx.doi.org/10.1111/gcb.13848.

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Fernandes, Jose A., Xabier Irigoien, Jose A. Lozano, Iñaki Inza, Nerea Goikoetxea, and Aritz Pérez. "Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species." Ecological Informatics 25 (January 2015): 35–42. http://dx.doi.org/10.1016/j.ecoinf.2014.11.004.

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Torres-Faurrieta, Laura Karen, Michel J. Dreyfus-León, and David Rivas. "Recruitment forecasting of yellowfin tuna in the eastern Pacific Ocean with artificial neuronal networks." Ecological Informatics 36 (November 2016): 106–13. http://dx.doi.org/10.1016/j.ecoinf.2016.10.005.

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Haltuch, M. A., E. N. Brooks, J. Brodziak, et al. "Unraveling the recruitment problem: A review of environmentally-informed forecasting and management strategy evaluation." Fisheries Research 217 (September 2019): 198–216. http://dx.doi.org/10.1016/j.fishres.2018.12.016.

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Shcherbakova, S. A., and E. A. Shvets. "Unified recruitment system in public institutions using digital technologies." Bulletin of the State University of Education. Series: Economics, no. 1 (March 10, 2025): 104–23. https://doi.org/10.18384/2949-5024-2025-1-104-123.

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Aim. To substantiate and propose a mechanism for a unified recruitment system for obtaining positions of civil servants based on an objective and comprehensive assessment of their professional and personal qualities and forecasting further career growth.Methodology. The methodology is determined by the complex use of general scientific methods, qualitative and quantitative research methods, as well as the modeling method.Results. As a result of the research, the mechanism of a unified recruitment system in public institutions using digital technologies, including systems based on artificial in

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Gröger, Joachim P., and Michael J. Fogarty. "Broad-scale climate influences on cod (Gadus morhua) recruitment on Georges Bank." ICES Journal of Marine Science 68, no. 3 (2011): 592–602. http://dx.doi.org/10.1093/icesjms/fsq196.

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AbstractGröger, J. P., and Fogarty, M. J. 2011. Broad-scale climate influences on cod (Gadus morhua) recruitment on Georges Bank. – ICES Journal of Marine Science, 68: . Climatic influences on Georges Bank cod recruitment were investigated using the North Atlantic Oscillation (NAO) as an index of atmospheric variability and the Atlantic Multidecadal Oscillation (AMO) as an index of sea surface temperature. A quantitative approach based on a simple Cushing-type stock–recruitment model was developed and extended to include climate influences using the technique of generalized transfer functions

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Holt, Carrie A., and Randall M. Peterman. "Long-term trends in age-specific recruitment of sockeye salmon (Oncorhynchus nerka) in a changing environment." Canadian Journal of Fisheries and Aquatic Sciences 61, no. 12 (2004): 2455–70. http://dx.doi.org/10.1139/f04-193.

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Sibling age-class (sibling) models, which relate abundance of one age-class of adult sockeye salmon (Oncorhynchus nerka) to abundance of the previous age-class in the previous year, are commonly used to forecast abundance 1 year ahead. Standard sibling models assume constant parameters over time. However, many sockeye salmon populations have shown temporal changes in age-at-maturity. We therefore developed a new Kalman filter sibling model that allowed for time-varying parameters. We found considerable evidence for long-term trends in parameters of sibling models for 24 sockeye salmon stocks

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Morzycki, Alexander, Helene Retrouvey, Becher Alhalabi, et al. "The Canadian Plastic Surgery Workforce Analysis: Forecasting Future Need." Plastic Surgery 26, no. 4 (2018): 269–79. http://dx.doi.org/10.1177/2292550318800328.

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Background: Projecting the demand for plastic surgeons has become increasingly important in a climate of scarce public resource within a single payer health-care system. The goal of this study is to provide a comprehensive workforce update and describe the perceptions of the workforce among Canadian Plastic Surgery residents and surgeons. Methods: Two questionnaires were developed by a national task force under the Canadian Plastic Surgery Research Collaborative. The surveys were distributed to residents and practicing surgeons, respectively. Results: Two-hundred fifteen (49%) surgeons respond

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Wang, Ao. "Advancing Organizational Effectiveness Through Strategic Workforce Planning and Technology Integration." Advances in Economics, Management and Political Sciences 121, no. 1 (2024): 107–12. http://dx.doi.org/10.54254/2754-1169/121/20242362.

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Abstract: This comprehensive examination delves into the pivotal roles of strategic workforce planning and technological advancements in bolstering organizational effectiveness. Spanning various critical dimensions such as human resource demand forecasting, strategic recruitment and selection, employee training and development, diversity and inclusivity, and the integration of technology in HR practices, the paper articulates a multi-faceted approach to optimizing workforce capabilities. By leveraging predictive analytics, organizations can forecast future employment needs, while AI-enhanced r

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Корнієнко, Інокентій, та Беата Барчі. "ОПТИМІЗАЦІЯ ПРОЦЕСУ НАБОРУ ПЕРСОНАЛУ ЗА ДОПОМОГОЮ МЕТОДІВ МОНТЕ-КАРЛО". Психологія: реальність і перспективи, № 24 (30 червня 2025): 49–57. https://doi.org/10.35619/prap_rv.vi24.434.

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The article explores the use of Monte Carlo simulations to improve recruitment processes under high uncertainty. The authors highlight challenges such as candidate availability, unpredictable timelines, varying acquisition costs and the inherent difficulty in forecasting candidate-role alignment. Traditional deterministic planning methods often fall short in such dynamic contexts, leading to missed targets, budget overruns and inefficient hiring. Monte Carlo methods are presented as a powerful tool for simulating probabilistic scenarios and managing risk. By repeatedly sampling values from def

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Tapio, Rachelle, and Dennis Tarepe. "Comparative Analysis of Random Forest and Hybrid ARIMA-random Forest Models for Student Enrollment Forecasting in Higher Education." Journal of Advances in Mathematics and Computer Science 40, no. 3 (2025): 124–36. https://doi.org/10.9734/jamcs/2025/v40i31982.

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Aims: This study evaluates the predictive accuracy of the Random Forest model and a Hybrid ARIMA-Random Forest model for forecasting student enrollment trends in higher education. Accurate forecasting is crucial for institutional planning, resource allocation, and decision-making. This study examines whether combining statistical time series forecasting (ARIMA) with machine learning (Random Forest) improves prediction accuracy. Study Design: A comparative forecasting study using historical enrollment data from 1949 to 2024. Place and Duration of Study: Conducted at a Higher Education Instituti

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Campbell, Alan. "The Lobster (Homarus americanus) Fishery off Lower Argyle Southwestern Nova Scotia." Canadian Journal of Fisheries and Aquatic Sciences 47, no. 6 (1990): 1177–84. http://dx.doi.org/10.1139/f90-137.

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Catch and effort data for the lobster (Homarus americanus) fishery of Lower Argyle, Nova Scotia, were obtained from sales slips on a weekly basis during 1978–87. Lobster size–frequency distributions were collected during at-sea sampling at the beginning and end of each fishing season. This fishery experienced a three-fold increase in landings (from 87.6 to 270 t) due to an increase in recruitment during the 10-yr study. The fishermen responded to the improved recruitment by increasing the total number of days fished per season by 41%. Overall mortality of recruited lobster (estimated from size

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