Clustering tools for the Lifecycle Screening of Emerging Technology (LiSET) framework
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Updated
Jun 1, 2018 - Python
Clustering tools for the Lifecycle Screening of Emerging Technology (LiSET) framework
Scripts and own generated data developed for the article: Miranda Xicotencatl, B., Kleijn, R., van Nielen, S., Donati, F., Sprecher B. & Tukker, A. (2023). Data implementation matters: Effect of software choice and LCI database evolution on a comparative LCA study of permanent magnets.
A Generalized Suffix Tree for any Python iterable using Ukkonen's algorithm, with Lowest Common Ancestor retrieval.
A 3D embodied carbon optimisation tool in VIKTOR, powered by 2050 Materials' API
A program for Life Cycle Assessment (LCA) calculations of supply chain waste and material footprints
A tool to calculate a building project's impacts on biodiversity over the entire life cycle. The tool was developed as part of the "Doughnut for Urban Development" project and manual. For more information, visit https://www.home.earth/doughnut
Sparse coding in PyTorch via the Locally Competitive Algorithm (LCA)
Life cycle inventory (LCI) schema
Assessment of environmental impact of energy systems by integrating data from LCA, MuSIASEM
Format converter for LCI datasets
A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
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