Liquid-Prep
Water usage optimizer
An end-to-end solution for optimizing water usage during droughts in agriculture.
Liquid Prep offers an end-to-end solution for farmers looking to optimize their water usage, especially during times of drought.
2 stars
5 watching
2 forks
last commit: almost 3 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
| A tool that extracts and optimizes high-level code snippets into LLVM IR using MLIR for high-level synthesis | 37 |
| A machine learning library for predicting and optimizing water exploration outcomes through hydrogeophysics and geophysics data analysis | 14 |
| An optimization plugin for Rollup that leverages Closure Compiler to minify and optimize JavaScript files. | 292 |
| A programming language designed to optimize computation by tracking side effects and enabling safe parallelism and caching with reactive invalidation. | 1,975 |
| Analyzes code performance and provides suggestions for optimization | 687 |
| A Redux reducer library that optimizes state management by memoizing and linking dependencies between reducers. | 163 |
| A tool to reduce the complexity of text prompts to minimize API costs and model computations. | 246 |
| Optimistically applies actions to update state before committing them to the system | 776 |
| An optimization framework for managing produced water and its beneficial reuse | 18 |
| Simulates the behavior of liquid in 2D environments using graphics rendering techniques. | 1 |
| A tool to help optimize content for search engines and social media platforms in Wagtail applications. | 66 |
| A tool to help developers understand and improve the optimization of their code | 136 |
| A tool that analyzes and suggests improvements to reduce the environmental impact of web applications through code optimization. | 154 |
| A Julia framework for creating large-scale linear optimization models of energy system capacity expansion with multiple periods | 70 |
| Analyzing water quality issues using data science and machine learning | 41 |