dal3006,github

resista_1d

An application to address 1D geoelectric inversion using hybrid geostatistics

resistancefft

Sliding FFT for Resistance/Voltage vs. B-field measurements. Developed to find AB & Shubnikov de Haas oscillations.

resistics

Robust magnetotelluric processing code for Python 3

rm3100

Geomagnetic sensor. with the raspberry pi spi interface communication.

rnn-notebooks

RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)

rnn_stock_data

Comparing LSTM, GRU, Bidirectional LSTM and Bidirectional GRU on some stock data

sa_tool_python

Structural Analysis tool for Fault Diagnosis

This project aims to simulate the behavior of one-dimensional MHD (Magnetohydrodynamics) models, i.e., reduced MHD models with scalar velocity and magnetic fields. We are mainly interested in the interaction between the velocity field and the magnetic field.

sciann

Deep learning for Engineers - Physics Informed Deep Learning

scorr

Fast and flexible two- and three-point correlation analysis for time series using spectral methods.

scram

Probabilistic Risk Analysis Tool (fault tree analysis, event tree analysis, etc.)

seasonality-fourier-analysis

Analyzing seasonality with Fourier transforms

secoda

Anomaly detection with SECODA for the R environment. SECODA is a general-purpose unsupervised non-parametric anomaly detection algorithm for datasets containing numerical and/or categorical attributes.

sensor-data-time-series-classification-forecasting-clustering-anomaly-detection-explainability

In this repository you may find data and code used for a machine learning project in sensor data done in collaboration with my colleagues Lorenzo Ferri and Roberta Pappolla at the University of Pisa.

sensor-fault-detection

Sensor Fault Detection | Time Series Analysis

sentimental_analysis_gru_bidirectional_lstm

Sentimental analysis using GRU , Bidirectional LSTM and Multiple Bidirectional LSTMs

sequence-to-sequence-classification-using-lstm

To find out when was the time that the fault occurs and make predictions to find out early faults,you can use a LSTM network to classify each time step of sequence data

sequence-transformer-for-long-term-sequence-forecasting

Replace Linear MultiHeadAttention mechanism with GConv

shayane_project

Characterzing the problem of two magnetic surveys acquired in different years and thus with different Geomagnetic Field

short-term-load-forecasting-using-ensemble-modelling-and-optimization-for-demand-response

forecasting and optimization - Coded in Python

siddharthanuthakki.github.io

Dst Index Visualization in D3.js

signal_analysis

1)Statistical Analysis; 2)Frequency Analysis; 3)Power Spectrum Density Analysis; 4)Wavelet Analysis; 5)AutoCorrelation;

signal_processing_ml_power_grids

This is a project involving using signal processing and machine learning analysis techniques in order to analyze signal data from power grid systems and classify whether or not the signals are good or bad (with bad signals corresponding to signals that generate partial discharges and lead to faults/power outages).

signalfaultpredictor

Perform Log analysis to Predict service faults on Australia's largest telecommunica network

signals-and-systems

Signals and Systems - Continuous-time and discrete-time signal analysis including Fourier series and discrete-time and discrete Fourier transforms; sampling; discrete-time linear system analysis with emphasis on FIR and IIR systems: impulse response, frequency response, and system function.

signals-and-systems-lecture

Continuous- and Discrete-Time Signals and Systems - Theory and Computational Examples

simple-eda-in-python-

A little exercise in cleaning and visualising some descriptive statistics using pandas, numpy, matplotlib, seaborn, heatmaps..

simulation-of-ieee-9-bus-system

This project was for the course "Power Generation, Transmission and Distribution" for the semester Fall 2020. The simulation was performed on the software "PSSE Xplore". The load flow analysis and the short circuit analysis for bolted faults was performed.

skforecast

Time series forecasting with scikit-learn models

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