Performance of a Novel Chaotic Firefly Algorithm with Enhanced Exploration for Tackling Global Optimization Problems: Application for Dropout Regularization
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- Dušan S. Radivojević & Ivan M. Lazović & Nikola S. Mirkov & Uzahir R. Ramadani & Dušan P. Nikezić, 2023. "A Comparative Evaluation of Self-Attention Mechanism with ConvLSTM Model for Global Aerosol Time Series Forecasting," Mathematics, MDPI, vol. 11(7), pages 1-13, April.
- Luka Jovanovic & Dejan Jovanovic & Nebojsa Bacanin & Ana Jovancai Stakic & Milos Antonijevic & Hesham Magd & Ravi Thirumalaisamy & Miodrag Zivkovic, 2022. "Multi-Step Crude Oil Price Prediction Based on LSTM Approach Tuned by Salp Swarm Algorithm with Disputation Operator," Sustainability, MDPI, vol. 14(21), pages 1-29, November.
- Tao Xu & Zeng Gao & Yi Zhuang, 2023. "Fault Prediction of Control Clusters Based on an Improved Arithmetic Optimization Algorithm and BP Neural Network," Mathematics, MDPI, vol. 11(13), pages 1-28, June.
- Zaid Bin Mushtaq & Shoaib Mohd Nasti & Chaman Verma & Maria Simona Raboaca & Neerendra Kumar & Samiah Jan Nasti, 2022. "Super Resolution for Noisy Images Using Convolutional Neural Networks," Mathematics, MDPI, vol. 10(5), pages 1-18, February.
- Marco Boresta & Diego Maria Pinto & Giuseppe Stecca, 2024. "Bridging operations research and machine learning for service cost prediction in logistics and service industries," Annals of Operations Research, Springer, vol. 342(1), pages 113-139, November.
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Keywords
convolutional neural networks; dropout; regularization; metaheuristics; swarm intelligence; optimization; firefly algorithm;All these keywords.
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