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The design of an intrusion detection system in MANET using the IGWO-ANN classification algorithm

Venketesh, R.; Sasikala, K. - In: International journal of networking and virtual … 31 (2024) 1, pp. 22-42

Persistent link: https://www.econbiz.de/10015066469

Predictive market making via machine learning

Haider, Abbas; Wang, Hui; Scotney, Bryan; Hawe, Glenn - In: Operations research forum 3 (2022) 1, pp. 1-21

Persistent link: https://www.econbiz.de/10012819335

State-dependent stock selection in index tracking : a machine learning approach

Bradrania, Reza; Pirayesh Neghab, Davood; Shafizadeh, … - In: Financial markets and portfolio management 36 (2022) 1, pp. 1-28

Persistent link: https://www.econbiz.de/10013175191

A deep learning approach for the dynamic dispatching of unreliable machines in re-entrant production systems

Wu, Cheng-Hung; Zhou, Fang-Yi; Tsai, Chi-Kang; Yu, … - In: International journal of production research 58 (2020) 9, pp. 2822-2840

Persistent link: https://www.econbiz.de/10012265273

Data-driven robust optimization using deep neural networks

Goerigk, Marc; Kurtz, Jannis - In: Computers & operations research : and their … 151 (2023), pp. 1-13

Persistent link: https://www.econbiz.de/10014234811

A modified random forest incremental interpretation method for explaining artificial and deep neural networks in cycle time prediction

Chen, Toly; Wang, Yu-Cheng - In: Decision analytics journal 7 (2023), pp. 1-11

Methods based on artificial neural network (ANN) or deep neural network (DNN) applications have been proposed to predict job cycle time effectively. However, the predicting mechanism of ANNs (or DNNs) is often difficult to understand and communicate. This problem has hindered their acceptability...

Persistent link: https://www.econbiz.de/10014436432