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adm1

Matlab and Simulink implementations of different simplifications of a mass-based Anaerobic Digestion Model No. 1 (ADM1)

adm1-1-python

python codes for IWA ADM1

anaerobicdigestion

The purpose of this app is to optimize the model parameters in order to increase the profitability of the bioreactor. The user will be able to adjust initial bacteria concentrations, reactor temperature (both static and dynamic), etc., and see a visual representation of the outcome. Note that not all adjustable parameters will have an effect on every plot. As soon as the user loads the app, the model is compiled and run using the current parameter settings. As the user adjusts these parameters, the plots and tables will update according to the new settings once the "Re-simulate" button has been clicked (This button is on each of the table and plot tabs). The tabs on the left then allow the user to navigate the simulated reactor output and read more about the process. You can also specify the time in which to truncate the data and evaluate the output, though the minimum value is currently 100 h. The reactor that follows the anaerobic digestor is capable of removing small quantities left over. Ideally you would set a minimum acceptable concentration, and optimize parameters to decrease the time required to reduce the contaminants to that concentration, though this not been implemented due to the lack of observational data.

atoti-dv-solar

atoti notebooks gallery

biogas

:exclamation: This is a read-only mirror of the CRAN R package repository. biogas — Process Biogas Data and Predict Biogas Production

biogasml

Machine learning and operations research applied to industrial biogas data

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

dirty_cat

Machine learning on dirty tabular data

git-course

iotbpm

Executive Order Corp – AI-IoTBPM server is IoT Internet of Things Drools-BPM (Business Process Management) engine for IoT Device Orchestration and IoT device ontology (AI-IoT device awareness, state of being, knowledge of real-world objects, events, situations, and abstract concepts). Executive Order Corp - AI-IoTBPM MQTT Telemetry Transport Machine-to-Machine(M2M) / Internet of Things (IoT) AI-IoTBPM :: Executive Order AI-IoTBPM Tron Sensor Processor MQTT AI-IoTBPM Client using EOSpy AI-IoTBPM Drools-jBPM.

jadm1_bsm

A Java implementation of the Anaerobic Digestion Model No 1 (ADM1) that can be validated using the BSM2 Matlab code.

machinelearningsamples-deeplearningforpredictivemaintenance

MachineLearningSamples-DeepLearningforPredictiveMaintenance

open-meteo

Free Weather Forecast API for non-commercial use

pca-with-varimax-rotation

predictive-maintenance

Datasets for Predictive Maintenance

pyadm1

PyADM1: a Python implementation of Anaerobic Digestion Model number 1

pytorch_geometric_temporal

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

rl-testbed-for-energyplus

Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus

ros2_torch_trt

ROS 2 packages for PyTorch and TensorRT for real-time classification and object detection on Jetson Platforms

solar-energy-analytics

A set of data-driven solutions for solar energy challenges.

stgcn

The PyTorch version of STGCN.

stgcn-ijcai-18

Spatio-Temporal Graph Convolutional Networks

stgcn-keras

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting implementation with keras

stgcn-pytorch

Paper:Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting . Implementation of spatio-temporal graph convolutional network with PyTorch

suitecrm

SuiteCRM - Open source CRM for the world

titanic

Kaggle's famous Titanic competition.