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Implementation of Artificial Neuro-Fuzzy Systems (ANFIS) models for leak detection in water distribution networks. The repository includes models trained on large-scale leak detection datasets with techniques like SGD and MBGD, along with preprocessing for time-series data, feature selection, and handling class imbalance.

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ANFIS-LeakDetection

Implementation of Artificial Neuro-Fuzzy Systems (ANFIS) models for leak detection in water distribution networks. The repository includes models trained on large-scale leak detection datasets using optimization techniques of gradient descent, stochastic gradient descent and mini-batch gradient descent, along with preprocessing pipeline for time-series data, feature selection and extracting, and handling class imbalance. Additional machine learning models were used for baseline comparison.

Dataset used is compiled from LeakDB dataset, available at github.com/KIOS-Research/LeakDB; which is a benchmark simulated dataset for leak detection in water distribution networks, created using the Water Network Tool for Re-silience (WNTR). Cited as: Vrachimis, S. G., Kyriakou, M. S., Eliades, D. G. and Polycarpou, M. M. (2018). LeakDB: A benchmark dataset for leakage diagnosis in water distribution networks. In Proc. of WDSA / CCWI Joint Conference (Vol. 1).

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Implementation of Artificial Neuro-Fuzzy Systems (ANFIS) models for leak detection in water distribution networks. The repository includes models trained on large-scale leak detection datasets with techniques like SGD and MBGD, along with preprocessing for time-series data, feature selection, and handling class imbalance.

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