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When developing learning algorithms for ensemble neural networks it is of fundamental importance to use a sampling method. In this paper a comparative analysis is made, between a sampling data method based on the mean square error for the training of ensemble neural networks and cross validation sampling method.
In this paper we present a method for face recognition combining modular neural networks and two interval type-2 fuzzy inference systems (FIS 2) for face recognition. The first FIS 2 is used for edges detection in the training data, and the second one to find the ideal parameters for the Sugeno integral as a decision operator. Fuzzy logic is shown to be a tool that can help improve the results of...
The adaptive sequencing of learning objects defines the order in which topics (and didactic resources) in a course will be presented to learners, considering for this their previous knowledge and their particular goals. Once a sequence is proposed each topic can be supported by different didactic materials, the system must select those that are appropriate for the learner's particular needs. The challenge...
The human evolutionary model is an intelligent global optimization method conceived to perform single and multiple objective optimization, this general method is still in development, especially the multi objective (MO) part is being improved. The single objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example differential evolution (DE),...
A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together...
Decision making requires multiple perspectives of different people as one single decision maker may have not enough knowledge to well solve a problem alone. This is particularly true when the decision environment becomes more complex. More organizational decisions are made now in groups than ever before. Group decision making is thus a process of arriving at a judgment or a solution for a decision...
This paper presents the influence of the process of migration between populations in GENO-FLOU, which is an environment of learning of fuzzy knowledge bases by genetic algorithms. Initially the algorithm did not use the process of migration. For the learning, the algorithm uses a hybrid coding, binary for the base of rules and real for the data base. This hybrid coding used with a set of specialized...
We present a novel approach used in conjunction with Sugeno and Yasukawa qualitative modeling algorithm. Its main feature is a reduction of the output space before the output data are clustered. The data used in this paper come from nine diesel engine trucks, and for each diesel engine 13 sensor variables are measured. The objective is to develop a fuzzy model for predicting the remaining lifetime...
There are an increasing number of large labeled and unlabeled data sets available. Clustering algorithms are the best suited for helping one make sense out of unlabeled data. However, scaling iterative clustering algorithms to large amounts of data has been a challenge. The computation time can be very great and for data sets that will not fit in even the largest memory, only carefully chosen subsets...
In the discipline of computer security, the field of trust management design is dedicated to the design of trusted systems, in particular trusted networks. One common trusted mechanism used these days is the multi-level security (MLS) mechanism, that allows simultaneous access to systems by users with different levels of security clearance in an interconnected network. Vulnerability arises when an...
This paper presents the design of a novel fuzzy control structure to improve stability of vehicles with semi-active suspension system. The proposed fuzzy controller adjusts the damping coefficient to stabilize the sprung mass and hence reduce the tendency of vehicle to rollover. A full car model with eight degrees of freedom is adopted that includes the vertical, roll, yaw, and pitch motions as well...
We originated theory of fuzzy discrete event systems (FDES) by generalizing the conventional discrete event systems so that vagueness and imprecision concerning the states and/or event transitions are more effectively dealt with. Through our experience in applying the FDES theory to HIV/AIDS prescription decision making, it become evident to us that an extended FDES theory is needed to cover diverse...
The main propose of this article is to design an intelligent neural-fuzzy controller for hybrid motorcycle. A self-tuning PID tracking controller based on RBF neural network with Fuzzy current limiter is proposed to maneuver the motor and save some energy in hybrid mode. The outer motor control loop is designed to track down the speed fluctuations by Neural-PID controller. Besides, one inner loop...
We study two deferent concepts of semicontinuity of fuzzy mappings by establishing characterizations of these fuzzy mappings. Relationships between semicontinuity and continuity of fuzzy mappings are explored. Some basic properties of these fuzzy mappings are presented and proved.
Generally, the state-space averaged model, which is an approximate model, is employed to synthesize the PWM (pulse-width-modulated) DC-DC converters. Instead, an algorithm based on orthogonal-functions approach (OFA) only involving algebraic computation is proposed in this paper to precisely solve the discontinuous dynamic equations of the PWM DC-DC converters. On the other hand, to accommodate the...
Intensive farming practices in North America create ideal conditions for disease outbreaks in cattle feedlots. A disease outbreak causes economic loss to the farmer, through the reduced weight gain of sick cattle and the spread of the infection to other cattle. Livestock disease management is a loss-reduction process, where sick cattle are quarantined and treated as early as possible. Disease detection...
This paper is situated in the area of possibilistic databases. Any possibilistic database has a canonical interpretation as a set of more or less possible regular databases, also called worlds. In order to manipulate such databases in a safe and efficient way, a constrained framework has been previously proposed, where a restricted number of querying operations are permitted (selection, union, projection...
This paper describes an application of fuzzy logic for corrected measured point determination in coordinate metrology. The correction method works on a series of indicated points obtained by contact scanning of the measured surface with a spherical tip probe. The outline of the probe ball defines an arc for each measured point, each such arc being delimited by the points of intersection with the preceeding...
In this paper, we present REXWERE, a software tool designed and implemented in order to extract knowledge from Web usage data in the form of recommendation fuzzy rules useful to provide personalized link suggestions to the visitor of a Web site. REXWERE employs a hybrid approach that combines fuzzy reasoning and neural learning within a working scheme made of several steps. Firstly, a fuzzy clustering...
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