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The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries = =. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop:
A multiplication algorithm is an algorithm (or method) to multiply two numbers. Depending on the size of the numbers, different algorithms are more efficient than others. Numerous algorithms are known and there has been much research into the t
Memetic algorithm (MA), often called hybrid genetic algorithm among others, is a population-based method in which solutions are also subject to local improvement phases. The idea of memetic algorithms comes from memes , which unlike genes, can adapt themselves.
Gene flow is the transfer of alleles from one population to another population through immigration of individuals. In population genetics, gene flow (also known as migration and allele flow) is the transfer of genetic material from one population to another. If the rate of gene flow is high enough, then two populations will have equivalent ...
Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population of programs. It applies the genetic operators selection according to a predefined fitness measure , mutation and crossover .
Genetic divergence will always accompany reproductive isolation, either due to novel adaptations via selection and/or due to genetic drift, and is the principal mechanism underlying speciation. On a molecular genetics level, genetic divergence is due to changes in a small number of genes in a species, resulting in speciation . [ 2 ]
Genetic drift, also known as random genetic drift, allelic drift or the Wright effect, [1] is the change in the frequency of an existing gene variant in a population due to random chance. [ 2 ] Genetic drift may cause gene variants to disappear completely and thereby reduce genetic variation . [ 3 ]
Holland's schema theorem, also called the fundamental theorem of genetic algorithms, [1] is an inequality that results from coarse-graining an equation for evolutionary dynamics. The Schema Theorem says that short, low-order schemata with above-average fitness increase exponentially in frequency in successive generations.
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