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scientific-process-optimization

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Optimize processes via ML-RSM and Pareto fronts.

Data & Analytics#visualization#pareto#process-optimization#ml-rsm#contour-map#multicobjective
Authornahisaho
Version1.0.0
Installs0

System Documentation

What problem does it solve?

ML-based optimization of process parameters using a combination of response surface methodology and Pareto optimization to identify optimal operating conditions and trade-offs across multiple objectives.

Core Features & Use Cases

  • ML-based 2D/3D response surface visualization (contour maps) to explore parameter effects
  • Process window visualization to reveal feasible regions under varying objectives
  • Pareto-front extraction and visualization to compare trade-offs between goals
  • Data-driven proposal of candidate operating conditions via grid-search-like exploration

Quick Start

Run the ML-RSM and Pareto optimization pipeline on your process data to identify optimal parameters and feasible regions.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: scientific-process-optimization
Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-process-optimization

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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