Wyniki wyszukiwania - BazTech

Ograniczanie wyników

3 2020

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Single spiking neuron multi-objective optimization for pattern classification

Juarez-Santini Carlos, Ornelas-Rodriguez Manuel, Soria-Alcaraz Jorge Alberto, Rojas-Domínguez Alfonso, Puga-Soberanes Hector J., Espinal Andrés, Rostro-Gonzalez Horacio

Journal of Automation Mobile Robotics and Intelligent Systems

2020

Vol. 14, No. 1

73--80

As neuron models become more plausible, fewer computing units may be required to solve some problems; such as static pattern classification. Herein, this problem is solved by using a single spiking neuron with rate coding scheme. The spiking neuron is trained by a variant of Multi-objective Particle Swarm Optimization algorithm known as OMOPSO. There were carried out two kind of experiments: the first one deals with neuron trained by maximizing the inter distance of mean firing rates among classes and minimizing standard deviation of the intra firing rate of each class; the second one deals with dimension reduction of input vector besides of neuron training. The results of two kind of experiments are statistically analyzed and compared again a Mono-objective optimization version which uses a fitness function as a weighted sum of objectives.

Exploring random permutations effects on the mapping process for grammatical evolution

Zúñiga Blanca Verónica, Carpio Juan Martín, Sotelo-Figueroa Marco Aurelio, Espinal Andrés, Purata-Sifuentes Omar Jair, Ornelas Manuel, Soria-Alcaraz Jorge Alberto, Rojas Alfonso

Journal of Automation Mobile Robotics and Intelligent Systems

2020

Vol. 14, No. 1

65--72

Grammatical Evolution (GE) is a form of Genetic Programming (GP) based on Context-Free Grammar (CF Grammar). Due to the use of grammars, GE is capable of creating syntactically correct solutions. GE uses a genotype encoding and is necessary to apply a Mapping Process (MP) to obtain the phenotype representation. There exist some well-known MPs in the state-of-art like Breadth-First (BF), Depth-First (DF), among others. These MPs select the codons from the genotype in a sequential manner to do the mapping. The present work proposes a variation in the selection order for genotype’s codons; to achieve that, it is applied a random permutation for the genotype’s codons order-taking in the mapping. The proposal’s results were compared using a statistical test with the results obtained by the traditional BF and DF using the Symbolic Regression Problem (SRP) as a benchmark.

Application of agglomerative and partitional algorithms for the study of the phenomenon of the collaborative economy within the tourism industry

Pérez-Rocha Juan Manuel, Soria-Alcaraz Jorge Alberto, Guerrero-Rodriguez Rafael, Purata-Sifuentes Omar Jair, Espinal Andrés, Sotelo-Figueroa Marco Aurelio

Journal of Automation Mobile Robotics and Intelligent Systems

2020

Vol. 14, No. 1

81--86

This research discusses the application of two different clustering algorithms (agglomerative and partitional) to a set of data derived from the phenomenon of the collaborative economy in the tourism industry known as Airbnb. In order to analyze this phenomenon, the algorithms are known as “hierarchical Tree” and “K-Means” were used with the objective of gaining a better understanding of the spatial configuration and current functioning of this complimentary lodging offer. The city of Guanajuato, Mexico was selected as the case for convenience purposes and the main touristic attractions were used as parameters to conduct the analysis. Cluster techniques were applied to both algorithms and the results were statistically compared.