Advances in Soft Computing: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Guadalajara, Mexico, October 22-27, 2018, Proceedings, Part I

by Ildar Batyrshin, Marïa de Lourdes Martïnez-Villaseïor, Hiram Eredïn Ponce Espinosa

Overview

The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018.

The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions.

The contributions are organized in topical as follows:

Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management.

Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.

Product Details

ISBN-13:	9783030044909
Publisher:	Springer International Publishing
Publication date:	01/03/2019
Series:	Lecture Notes in Computer Science , #11288
Edition description:	1st ed. 2018
Pages:	437
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Evolutionary and Nature-Inspired Intelligence.- A Genetic Algorithm to Solve Power System Expansion Planning With Renewable Energy.- Memetic Algorithm for constructing Covering Arrays of variable strength based on Global-best Harmony Search and Simulated Annealing.- An Adaptive Hybrid Evolutionary Approach for a Project Scheduling Problem that Maximizes the Effectiveness of Human Resources.- Best Paper award, first place: Universal Swarm Optimizer for Multi-Objective Functions.- Broadcasting and sharing of parameters in an IoT network by means of a Fractal of Hilbert using Swarm Intelligence.- Solid waste collection in Ciudad Universitaria-UNAM using a VRP approach and Max-Min Ant System algorithm.- Selection of Characteristics and Classification of Microarrays using Bioinspired Algorithms and Generalized Neuron.- Supervised and unsupervised neural networks: Experimental study for anomaly detection in electrical consumption.- Artificial neural networks and common spatial patterns for the recognition of motor information from EEG signals.- Classification of Motor Imagery EEG Signals with CSP filtering through Neural Networks Models.- Efficiency Analysis of article Tracking with Synthetic PIV using SOM.- Machine Learning.- Transforming Mixed Data Bases for Machine Learning: A Case Study.- Full model selection in huge datasets and for proxy models construction.- Single imputation methods applied to a global geothermal database.- Feature Selection for Automatic Classification of Gamma-ray and Background Hadron Events with Different Noise Levels.- Ranking based Unsupervised Feature Selection Methods: an Empirical Comparative Study in High Dimensional Datasets.- Dynamic Selection Feature Extractor for Trademark Retrieval.- Bayesian Chain Classifier with Feature Selection for Multi-label Classification.- A Time Complexity Analysis to the ParDTLT Parallel Algorithm for Decision Tree Induction.- Infrequent Item-to-item Recommendation via Random Fields.- An approachbased on contrast patterns for bot detection on web log files.- User recommendation in low degree networks with a learning-based approach.- Volcanic anomalies detection through Recursive Density Estimation.- A Rainfall Prediction Tool for Sustainable Agriculture Using Random Forest.- Kolb's Learning styles, learning activities and academic performance in a Massive Private Online Course.- Tremor Signal Analysis for Parkinson's Disease Detection Using Leap Motion Device.- Fuzzy Logic and Uncertainty Management.- Modeling Decisions for Project Scheduling Optimization Problem Based on Type-2 Fuzzy Numbers.- Differential Evolution algorithm using a dynamic crossover parameter with a high-speed interval type 2 fuzzy system.- Allocation Centers Problem on Fuzzy Graphs with Largest Vitality Degree.- Fuzzy Design of Nearest Prototype Classifier.- A Fuzzy Harmony Search algorithm for the optimization of a Benchmark set of functions.- An Innovative and Improved Mamdani Inference (IMI) Method.- AGeneral Method for Consistency Improving in Decision-Making Under Uncertainty.