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Fast generation of implied volatility surface : optimize the traditional numerical analysis and machine learning

Yen, Jerome; Chen, Bangren; Wu, KangZahng; Yen, Joseph - In: International journal of financial engineering 8 (2021) 2, pp. 1-24

Persistent link: https://www.econbiz.de/10012662246

Model selection for long-term load forecasting under uncertainty

Thangjam, Aditya; Jaipuria, Sanjita; Dadabada, Pradeep Kumar - 2024

Persistent link: https://www.econbiz.de/10015371694

Interests as predictors of performance : an omitted and underappreciated variable

Nye, Christopher D.; Butt, Saba M.; Bradburn, Jacob; … - In: Journal of vocational behavior 108 (2018), pp. 178-189

Persistent link: https://www.econbiz.de/10011936163

Forecasting methods and principles : evidence-based checklists

Armstrong, J. Scott; Green, Kesten C. - In: Journal of global scholars of marketing science : … 28 (2018) 2, pp. 103-159

Persistent link: https://www.econbiz.de/10011891407

Variable slope forecasting methods and COVID-19 risk

Leightner, Jonathan Edward; Inoue, Tomoo; Micheaux, … - In: Journal of risk and financial management : JRFM 14 (2021) 10, pp. 1-22

There are many real-world situations in which complex interacting forces are best described by a series of equations. Traditional regression approaches to these situations involve modeling and estimating each individual equation (producing estimates of "partial derivatives") and then solving the...

Persistent link: https://www.econbiz.de/10012628841

Meta-prediction models for bullwhip effect prediction of a supply chain using regression analysis

Navee Chiadamrong; Nont Sarnrak - In: International journal of information systems and supply … 14 (2021) 4, pp. 36-71

Persistent link: https://www.econbiz.de/10012648137

A hybrid machine learning approach to hotel sales rank prediction

Srivastava, Praveen Ranjan; Eachempati, Prajwal; … - In: Journal of the Operational Research Society 74 (2023) 6, pp. 1407-1423

Persistent link: https://www.econbiz.de/10014335387

Prediction of Academic Performance of Students Using Multiple Regression

Saxena, Mamta; Gupta, Sachin - 2022

competition at a higher level. Students are diverted towards doing higher courses offered by numerous institutes, universities … day. Various measures are taken by educators and stakeholders to reduce the intensity of failure of students. Educational … data mining is a new term coined in the sector of education to predict the performance of students in academics and to …

Persistent link: https://www.econbiz.de/10014241393

Machine learning and deep learning-based students’ grade prediction

Korchi, Adil; Messaoudi, Fayçal; Abatal, Ahmed; … - In: Operations research forum 4 (2023) 4, pp. 1-21

Persistent link: https://www.econbiz.de/10014425792

A comparison of logistic regression, neural networks, and classification trees predicting success of actuarial students

Schumacher, Phyllis; Olinsky, Alan; Quinn, John T.; … - In: Journal of education for business 85 (2010) 5, pp. 258-263

Persistent link: https://www.econbiz.de/10003989668