Research on predictions of breast cancer grows in the scientific community, providing data studies patient surveys. Predictive models link areas medicine and artificial intelligence to collect improve disease assessments that affect a large part population, such as cancer. In this work, we used hybrid model based concepts neural networks fuzzy systems assist identification people with through rules. The can manipulate collected medical examinations identify patterns between healthy an...

Its constant technological evolution characterizes the contemporary world, and every day processes, once manual, become computerized. Data are stored in cyberspace, as a consequence, one must increase concern with security of this environment. Cyber-attacks represented by growing worldwide scale characterized significant challenges century. This article aims to propose computational system based on intelligent hybrid models, which through fuzzy rules allows construction expert systems...

Human papillomavirus (HPV) infection is related to frequent cases of cervical cancer and genital condyloma in humans. Up now, numerous methods have come into existence for the prevention treatment this disease. In context, paper aims help predict susceptibility patient forms using both cryotherapy immunotherapy. These studies facilitate choice medications, which can be painful embarrassing patients who warts on intimate parts. However, use intelligent models generates efficient results but...

The growth of the computerization processes and services has changed human relations and, as a consequence, have created new forms attacks frauds for users digital equipment. Because many people use computers, smartphones, e-mail to perform day-to-day tasks, various data traffic is susceptible attack. This can undermine competitiveness company that may breached strategic information. Therefore, security information management are fundamental factors companies keep due control their business...

The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including detection failures and anomalous behaviors. This paper discusses use an artificial intelligence model based on association between logic training to recognize anomalies transactions involved context computer cyberattacks. In addition verifying accuracy model, rules were obtained through knowledge from massive datasets form expert systems. acquired allow creation...

This paper proposes the use of intelligent hybrid systems based on concepts artificial neural networks and fuzzy to assist in identification children who have a problem that may impair their motor or cognitive development. Research seeking identify diseases are listed International Classification Functioning, Disability, Health (ICF-CY) targets this research. To disease studies, database was provided for researchers from all over world develop techniques aid creation specialist rules...

Predicting the time to build software is a very complex task for engineering managers.There are factors that can directly interfere with productivity of development team.Factors related complexity system be developed drastically change necessary completion works factories.This work proposes use hybrid based on artificial neural networks and fuzzy systems assist in construction an expert rules support prediction hours destined according elements present same.The set obtained by helps...

Breast cancer is one of the most affected diseases worldwide, with 1.38 million new cases and 458 thousand deaths from disease each year, according to World Health Organization.In this article, we use a hybrid artificial intelligence model based on concepts neural networks fuzzy systems improve predictive results expert capable working numerical datasets allowing in addition, an assertive prediction addition prediction, increase interpretability through network architecture, creating...

Extreme learning machines are very efficient tools to perform data classification, besides being a more effective solution the structures using backpropagation determine values at intermediate layers of model. One problem faced by ELM is over-fitting, which usually happens when amount neurons in hidden layer high. Several pruning methods for have been proposed, including statistical techniques and control correlation. This article provides simple way remove based on correlation coefficient...

This work has as main objective the development of a hybrid expert system in identification malware using artificial intelligence and fuzzy approach. Such attacks can harm businesses individuals by allowing essential data to be misrepresented. To perform rules extraction, model was subjected detection tests that were made available some public datasets verify efficiency approach; it compared binary classification with models neural networks network models. The results obtained simulations...

Smart models are responsible for solving complex problems within the routines of people and companies. The complexity their structures can be defined by methodologies used in definition parameters or architecture models. In three-layer fuzzy neural networks, number neurons is determined fuzzification techniques capable creating elements based on data submitted to training intelligent structures. choice method make model with many parameters. To create a more compact network architecture,...

This paper presents a novel learning algorithm for fuzzy logic neuron based on neural networks and systems able to generate accurate transparent models.The is ideas from Extreme Learning Machine, achieve low time complexity, regularization theory, resulting in sparse models.A compact set of incomplete rules can be extracted the network topology.Experiments considering regression problems are detailed.Results suggest proposed approach as promising alternative pattern recognition with good...

A customer's buying profile helps new products gain market share.The lack of an information base or expert systems can generate problems demands, production even distribution.This paper proposes the use intelligent hybrid model based on neural networks and fuzzy for construction to assist in predicting customer purchase option symbiotic kefir smoothie.The tests prove that approach assists product when evaluated together with other relevant factors opinion poll.