Current trends in designing metaheuristic algorithms: applications to machine learning

For this work we have implemented three algorithms: algorithm A, for the estimation of the global alignment with k differences, based on dynamic programming; algorithm B, for

Specialized solutions use student score data and powerful artificial intelligence or machine learning algorithms to help improve results in a number of areas as well as to

Then, four measures based on color and motion are selected and examined in detail with different segmentation algorithms and standard test sequences for video object

We consider classical data structures like Binary Search Trees and Hash Tables, and compare their performance on two public datasets when Collaborative Filtering algorithms

More specifically, they had to assign a readability score for 3 different pairs of test cases: (1) interactive vs interactive, two tests whose readability differed significantly for

To create genetic graph-based clustering algorithms and heuristics to improve the robustness and solutions of classical partitional clustering algorithms, and to study its

Section 6 includes the improvement algorithms, such as Genetic algorithm, Tabu Search and Particle Swarm Optimization.. After that our representation and evaluation is

Three tuning algorithms, a classic optimization algorithm, genetic algorithm (GA), a metaheuristic optimization algorithm, Bacterial Foraging Technique based Particle