JWA implementation (supports all JWS algorithms)
Implementation of JSON Web Signatures
Multiprocessing genetic algorithm implementation library
Implementation of genetic algorithms for nodejs and browser
Detect the indentation of code
Sniff the encoding from a HTML byte stream
Efficient implementation of Levenshtein algorithm with locale-specific collator support.
Simple “Least Recently Used” (LRU) cache
Fast 2D concave hull algorithm in JavaScript (generates an outline of a point set)
The fastest and smallest JavaScript polygon triangulation library for your WebGL apps
The lightest signal library.
The fCoSE layout for Cytoscape.js by Bilkent with fast compound node placement
Parse a JSON string that has git merge conflicts, resolving if possible
An implementation of the Unicode Line Breaking Algorithm (UAX #14)
Hashing made simple. Get the hash of a buffer/string/stream/file.
A JS library for finding optimal label position inside a polygon
SHA1 wrapper for browsers that prefers `window.crypto.subtle`.
A point in polygon based on the paper Optimal Reliable Point-in-Polygon Test and Differential Coding Boolean Operations on Polygons
Martinez polygon clipping algorithm, does boolean operation on polygons (multipolygons, polygons with holes etc): intersection, union, difference, xor
Multiprocessing genetic algorithm implementation library extension
graph algorithm
Text hyphenation in Javascript.
Find the longest common subsequence.
oidc-token-hash validates (and generates) ID Token `_hash` claims such as `at_hash` or `c_hash`
A Generic Algorithm Library for Ruby Language
Simple genetic algorithm for functions minimization.
A simple gem to help in the creation of genetic algorithms
== DESCRIPTION: Charlie is a library for genetic algorithms (GA) and genetic programming (GP). == FEATURES: - Quickly develop GAs by combining several parts (genotype, selection, crossover, mutation) provided by the library. - Sensible defaults are provided with any genotype, so often you only need to define a fitness function. - Easily replace any of the parts by your own code. - Test different strategies in GA, and generate reports comparing them. Example report: http://charlie.rubyforge.org/example_report.html == INSTALL: * sudo gem install charlie == EXAMPLES: This example solves a TSP problem (also quiz #142): N=5 CITIES = (0...N).map{|i| (0...N).map{|j| [i,j] } }.inject{|a,b|a+b} class TSP < PermutationGenotype(CITIES.size) def fitness d=0 (genes + [genes[0]]).each_cons(2){|a,b| a,b=CITIES[a],CITIES[b] d += Math.sqrt( (a[0]-b[0])**2 + (a[1]-b[1])**2 ) } -d # lower distance -> higher fitness. end use EdgeRecombinationCrossover, InversionMutator end Population.new(TSP,20).evolve_on_console(50) This example finds a polynomial which approximates cos(x) class Cos < TreeGenotype([proc{3*rand-1.5},:x], [:-@], [:+,:*,:-]) def fitness -[0,0.33,0.66,1].map{|x| (eval_genes(:x=>x) - Math.cos(x)).abs }.max end use TournamentSelection(4) end Population.new(Cos).evolve_on_console(500)
Framework for genetic algorithm fast development
Genetica is a library to create and use Genetics Algorithms with Ruby.
Simple Framework of Genetic Algorithm
Providing an expressive DSL to illustrate genetic algorithm problems and sets of default methods.
Genetic Algorithm Pool Selection.
Evolve provides a simple and readable interface to make genetic algorithm optimization easy
Darwinning provides tools to build genetic algorithm solutions using a Gene, Organism, and Population structure.
Optimise anything that responds to 'fitness' and takes a hash
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