Search Results for "genetic algorithm cloudsim" - Page 2
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Showing 161 open source projects for "genetic algorithm cloudsim"
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GAKNN is a data mining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
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GA-tools
general genetic algorithms optimization fortran 95 routines
High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array. Single objective and multi-objective maximization routines are present. Possible to incorporate own crossover and mutation operators exclusively or in addition to standard operators that are included by default. ... -
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MicroGP
A multi-purpose extensible self-adaptive evolutionary algorithm
MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4 -
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tsp-problem-ga-aco-comparisson
Genetic Algorithm and Ant Colony to solve the TSP problem
This project compares the classical implementation of Genetic Algorithm and Ant Colony Optimization, to solve a TSP problem. It's possible to define the number of cities to visit , and also interactively create new cities to visit in a 2D spatial panel. A total distance is given for AG and ACO solution at end. -
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary... -
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theoEA_Code
genetic algorithm for optimizing planar optical antennas
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Sched-SPM
A C++ schedule generator based on Genetic Algorithm and Hill Climbing
Sched-SPM is a C++ schedule generator for software project staffing and rescheduling based on Genetic Algorithm (GA) and Hill Climbing (HC). This preliminary tool is mainly for academic purpose. It is implemented with GALib (http://lancet.mit.edu/ga/), an open-source toolkit of Genetic Algorithms in various platforms including Unix and Windows. The input and output files of the software are required as XML format. The input file includes tasks' and employees' information according to predefined file format. ... -
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
...To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach. Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers. The classification performances achieved by the proposed method method on the chosen datasets are promising. -
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REDHORSE
Software suite for the analysis of haploid hybrids using NGS
...We therefore designed a software suite called REDHORSE that takes genomic alignments as input, extracts meaningful markers and generates MSAs that are the inputs to existing RD algorithms. In addition, REDHORSE implements a custom RD algorithm that makes use of sequence information and genomic positions to accurately detect crossovers. REDHORSE is portable and platform independent suite that provides efficient analysis of genetic crosses based on NGS data. -
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GeneticAlgorithms
Framework for using the Genetic Algorithms optimization heuristic.
GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later. -
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Java CoreWars Evolver
A Java based, pMars compatible, CoreWars simulator with GA
A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 8 is needed. See [Wiki:Tutorial] -
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Glycosylation Microviewer
An application create, simulate and adjust N-linked glycosylation.
...The model used in the application is based on two significant papers: 1.1997 Pablo Umana, James E.Bailey A Mathematical Model of N-linked Glycoform Biosynthesis. 2.2005 Frederick J.Krambeck, Michael J.Betenbaugh A Mathematical Model of N-linked Glycosylation. The application allow to simulate the network in dynamic form with various ODE solvers(Euler, Runge-Kutta etc). Genetic Algorithm is used to adjust the kinetic parameters of Michaelis-Menten equations in glycosylation reaction network. A dynamic plot is supplied to show the value of mole amout and mole fraction of various glycoform. Thanks to Alexey Balakin and Alessandro Presta. Alexey Balakin supply mathgl(https://sourceforge.net/projects/mathgl) that make the implementation of dynamic plot in this application easily. ... -
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Cyberphantom Alfa Colony
AI new tipe
This is an experimental project whose main objective is the creation of artificial intelligence (AI) new tipe. At the core of this idea is the use of special genetic algorithm that emulates the single-celled organism. The colony of such cybernetic organisms can give rise to a "reasonable" network that have a huge intellect and computing power. -
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gametes
Generate complex SNP models and heterogeneous datasets
Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) is an algorithm for the generation of complex single nucleotide polymorphism (SNP) models for simulated association studies. GAMETES is designed to generate epistatic models which we refer to as pure and strict, that constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. -
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Genetic Algorithms Engine - Blackjack
A genetic algortihm engine that evolves blackjack basic strategy.
This project is a genetic algorithm engine able to be reused for other projects with minimal additional programming. The genetic algorithm engine currently plays many blackjack hands for the fitness function and produces a result similar to blackjack basic strategy. To see it in action, download the zip file and run either: GABlackjack_Demo.exe (quick) or GABlackjack_Long.exe (slow, but it achieves better results). -
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Evolutionary Nursery
A simple genetic algorithm for numerical optimization
Evolutionary nursery is a result for my passion for developing genetic algorithms. I implemented this simple GA in 2008. This is especially intended for numerical optimization problems. -
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FamSeq
Variant calling on the basis of pedigree information
...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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SimpleFB_GA
a simple genetic algorithm written in FreeBasic
a FreeBasic-written Genetic Algorithm code is here deployed -
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NEAT Visualizer SFML
A NEAT Implementation and Visualization System
Evolves neural networks using the Neuro-Evolution of Augmenting Topologies (NEAT) technique. A separate visualization system uses another genetic algorithm to evolve images of the otherwise dimensionless networks so their structure can be observed. -
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VariantMaster
Extract causative variants for monogenic and sporadic genetic diseases
...To improve the identification of the variants from HTS, we developed VariantMaster, an original program that accurately and efficiently extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM) data to robustly estimate the conditional probability of segregation in a family, as well as the probability of it being de novo or somatic. In familial cases, various modes of inheritance are considered: X-linked, autosomal dominant, and recessive (homozygosity or compound heterozygosity). ... -
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niGA
Heterogenous Multiprocessor Scheduling Using Genetic Algorithms
Implementation of task scheduling using Genetics algorithm for heterogeneous parallel programming -
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Bin Packing with Genectic Algorithm
Bin Packing problem solved using Genectic Algorithm
This project contains a solution for a Bin Packing problem solved using Genectic Algorithms. The code in the project was created as a solution for a problem in a combinatorial optimization class at the Univeridade Federal do Rio Grande do Sul (UFRGS - Brasil) in 2007. -
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PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. -
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Evochumps
Evolving recursive artificial neural networks in a simulation.
...It has a built-in evolutionary algorith to let the brains evolve conditoned to selective pressure. The program's interface allows you to manipulate all kinds of parameters of both the simulation, the genetic algorithm, and each particular RNN in real time. -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
