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Deep learning with small and big data of symmetric volatility information for predicting daily accuracy improvement of JKII prices

Ledhem, Mohammed Ayoub - In: Journal of capital markets studies 6 (2022) 2, pp. 130-147

Purpose The purpose of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information. Design/methodology/approach This paper uses the nonlinear autoregressive exogenous...

Persistent link: https://www.econbiz.de/10013413441

Integrated explainable deep learning prediction of harmful algal blooms

Lee, Donghyun; Kim, Mingyun; Lee, Beomhui; Chae, Sangwon; … - In: Technological forecasting & social change : an … 185 (2022), pp. 1-11

Persistent link: https://www.econbiz.de/10014233744

Predictive end-to-end enterprise process network monitoring

Oberdorf, Felix; Schaschek, Myriam; Weinzierl, Sven; … - In: Business & information systems engineering 65 (2023) 1, pp. 49-64

Persistent link: https://www.econbiz.de/10014228189

The performance of time series forecasting based on classical and machine learning methods for S&P 500 index

Uzzal, Maudud Hassan; Ślepaczuk, Robert - 2023

Persistent link: https://www.econbiz.de/10014305886

An open-source framework to implement Kalman Filter bus arrival predictions

Crudden, Sean Óg; Berrebi, Simon - In: Networks and spatial economics : a journal of … 23 (2023) 2, pp. 429-443

Persistent link: https://www.econbiz.de/10014335054

Configuration and implementation of a daily artificial neural network-based forecasting system using real supermarket data

Slimani, Ilham; El Farissi, Ilhame; Achchab, Said - In: International journal of logistics systems and management 28 (2017) 2, pp. 144-163

Persistent link: https://www.econbiz.de/10011856121

Neuro-fuzzy approach in business applications : a decade survey

Rajab, Sharifa; Sharma, Vinod - In: International journal of business information systems : … 26 (2017) 4, pp. 451-487

Persistent link: https://www.econbiz.de/10011856652

Statistical, machine learning and deep learning forecasting methods : comparisons and ways forward

Makridakis, Spyros G.; Spiliotis, Evangelos; … - In: Journal of the Operational Research Society 74 (2023) 3, pp. 840-859

Persistent link: https://www.econbiz.de/10014332223

A review of explainable artificial intelligence in supply chain management using neurosymbolic approaches

Kosasih, Edward Elson; Papadakis, Emmanuel; Baryannis, … - In: International journal of production research 62 (2024) 4, pp. 1510-1540

Persistent link: https://www.econbiz.de/10014458567

Application of artificial intelligence in stock market forecasting : a critique, review, and research agenda

Chopra, Ritika; Sharma, Gagan Deep - In: Journal of risk and financial management : JRFM 14 (2021) 11, pp. 1-34

The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing...

Persistent link: https://www.econbiz.de/10012795264