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hybrid

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This documents the training and evaluation of a Hybrid CNN-LSTM Attention model for time series classification in a dataset. The model combines convolutional neural networks (CNNs) for feature extraction, long short-term memory (LSTM) networks for sequential modeling, and attention mechanisms to focus on important parts of the sequence.

  • Updated Jan 14, 2025
  • Python

Machine Learning Model to detect hidden malwares and phase changing malwares.It predicts the date of the next probable attack of the malware and its extent.It deals with the change in network traffic flow.It is developed in Python in Jupyter notebook.

  • Updated Apr 30, 2020
  • Python

A Genetic Algorithm (GA) / Discrete Particle Swarm Optimization/ Hybrid (GA-PSO) for nuclear fuel optimization using ML surrogates (DNN, KNN, Random Forest, Ridge) and OpenMC. Optimizes fuel loading patterns for a target k-eff and minimal Power Peaking Factor (PPF).

  • Updated Oct 17, 2025
  • Python

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