Titlebook: Nature-Inspired Computation and Machine Learning; 13th Mexican Interna Alexander Gelbukh,Félix Castro Espinoza,Sofía N. G Conference procee

异端邪说2

协迫

A Multi-objective Genetic Algorithm for the Software Project Scheduling Problemmulti-objective genetic algorithm for solving benchmark instances of this model. Results show that our proposed genetic algorithm performs similarly to two recent approaches and that it finds better multi-objective solutions when they are compared to those found by a well-known multi-objective optimizer.

抒情短诗

Incorporate

不要不诚实

A Hierarchical Reinforcement Learning Based Artificial Intelligence for Non-Player Characters in Vidental results show that this implementation improves naturalness from the user’s point of view. In addition, the proposed MaxQ-Q based algorithm in NPCs allow to programmers a robust way to give artificial intelligence to them.

spinal-stenosis

Customer Churn Prediction in Telecommunication Industry: With and without Counter-Examplems. Furthermore, by applying the proposed techniques (i.e. Rough sets as one-class and multi-class classifiers) on publicly available dataset, the results show that rough set as a multi - class classifier provides more accurate results for binary/multi-class classification problems.

sorbitol

Extension of the Method of Musical Composition for the Treatment of Multi-objective Optimization Proputational experiments performed on the ZDT and DTLZ test suite highlight the promising performances obtained by the resulting MO-MMC algorithm, when compared with the NSGA-II, MOEA/D and two swarm intelligence based techniques.

一瞥

florid

An Effective Method for MOGAs Initialization to Solve the Multi-Objective Next Release Problem-II, and the experimental results have shown that it is consistently superior to the random initialization method and the extreme solutions method, considering the convergence speed and the quality of the Pareto front, that was measured using the Spread and Hypervolume indexes.

轻率的你

Predictive Models Applied to Heavy Duty Equipment Managementped using support vector machine with historical data obtained on a daily basis during 2013 from one heavy mining equipment of an important copper mine site in Chile. One-step-ahead predictions of the predicted variables confirmed good performance of the dynamic models.