Antonio Fernandez Gomez-skarmeta

About the use of fuzzy clustering techniques for fuzzy model identification

Abstract In this work we present an alternative approach to generate fuzzy rules with a functional consequent associated to the TSK fuzzy model. In our case, using fuzzy clustering algorithms that look for linear behaviours in the product space of the input-output data, we analyse different methods to generate the associated fuzzy rules using in some cases multidimensional reference fuzzy sets in the product space of the input variables and in other cases fuzzy sets in each of the different dimensions. In any case the rules being generated correspond to a TSK fuzzy model.

A fuzzy clustering-based rapid prototyping for fuzzy rule-based modeling

This paper presents different approaches to the problem of fuzzy rules extraction by using fuzzy clustering as the main tool. Within these approaches we describe six methods that represent different alternatives in the fuzzy modeling process and how they can be integrated with a genetic algorithms. These approaches attempt to obtain a first approximation to the fuzzy rules without any assumption about the structure of the data. Because the main objective is to obtain an approximation, the methods we propose must be as simple as possible, but also, they must have a great approximative capacity and in that way we work directly with fuzzy sets induced in the variables input space. The methods are applied to four examples and the errors obtained are specified in the different cases.

High-Integrity IMM-EKF-Based Road Vehicle Navigation With Low-Cost GPS/SBAS/INS

User requirements for the performance of Global Navigation Satellite System (GNSS)-based road applications have been significantly increasing in recent years. Safety systems based on vehicle localization, electronic fee-collection systems, and traveler information services are just a few examples of interesting applications requiring onboard equipment (OBE) capable of offering a high available accurate position, even in unfriendly environments with low satellite visibility such as built-up areas or tunnels and at low cost. In addition to that, users and service providers demand from the OBEs not only accurate continuous positioning but integrity information of the reliability of this position as well. Specifically, in life-critical applications, high-integrity monitored positioning is absolutely required. This paper presents a solution based on the fusion of GNSS and inertial sensors (a Global Positioning System/satellite-based augmentation system/inertial navigation system integrated system) running an extended Kalman filter combined with an interactive multimodel method (IMM-EKF). The solution developed in this paper supplies continuous positioning in marketable conditions and a meaningful trust level of the given solution. A set of tests performed in controlled and real scenarios proves the suitability of the proposed IMM-EKF implementation as compared with low-cost GNSS-based solutions, dead reckoning systems, single-model EKF, and other filtering approaches of the current literature.

Approximating optimal multicast trees in wireless multihop networks

We study the problem of computing minimal cost multicast trees in multi-hop wireless mesh networks. This problem is known as the Steiner tree problem, and it has been widely studied in fixed networks. However, we show in this paper that in multi-hop wireless mesh networks, a Steiner tree is no longer offering the lowest bandwidth consumption. So, we re-formulate the problem in terms of minimizing the number of transmissions. We show that the new problem is also NP-complete and propose heuristics to approximate such trees. Our simulations results show that the proposed heuristics offer a lower cost than Steiner trees over a variety of scenarios.

A Cooperative Approach to Traffic Congestion Detection With Complex Event Processing and VANET

Currently, distributed traffic information systems have come up as one of the most important approaches for detecting traffic flow problems on a road. For that purpose, they usually make use of the location information that vehicles share among them through periodical messages that are transmitted across a vehicular ad hoc network (VANET). This paper puts forward an event-driven architecture (EDA) as a novel mechanism to get insight into VANET messages to detect different levels of traffic jams; furthermore, it also takes into account environmental data that come from external data sources, such as weather conditions. The proposed EDA has been developed through the complex-event-processing technology. Simulation tests show that the proposed mechanism can detect traffic congestions, which involve different numbers of lanes and lengths with short delay.

Architecture and evaluation of a unified V2V and V2I communication system based on cellular networks

Vehicle communications are becoming the cornerstone in the future vehicle equipment. More specifically, vehicle to vehicle communications (V2V) are the main object of researching nowadays, because vehicle to infrastructure (V2I) approximations are already being developed as commercial solutions. Cellular networks (CN) are usually applied in V2I solutions, whereas ad hoc networks are practically the only technology considered in V2V communications. Due to fact that CN are currently a reality and the operators are continuously improving the network, this communication technology could be considered as a candidate to deal with V2V necessities as well. The present paper defends the applicability of CN in the V2V field, and presents a novel communication paradigm for vehicles which unifies both V2V and V2I paradigms into one system. A peer to peer network technology has been used over the CN basis to create a group-based communication infrastructure which enables the message propagation among vehicles and between the car and the road side infrastructure. The architecture has been implemented in both hardware and software terms, and multitude of field tests have been carried out, whose main performance results are shown in the paper.

An evolutionary algorithm for constrained multi-objective optimization

The paper follows the line of the design and evaluation of new evolutionary algorithms for constrained multi-objective optimization. The evolutionary algorithm proposed (ENORA) incorporates the Pareto concept of multi-objective optimization with a constraint handling technique and with a powerful diversity mechanism to obtain multiple nondominated solutions through the simple run of the algorithm. Constraint handling is carried out in an evolutionary way and using the min-max formulation, while the diversity technique is based on the partitioning of search space in a set of radial slots along which are positioned the successive populations generated by the algorithm. A set of test problems recently proposed for the evaluation of this kind of algorithm has been used in the evaluation of the algorithm presented. The results obtained with ENORA were very good and considerably better than those obtained with algorithms recently proposed by other authors.

Fuzzy modeling with hybrid systems

In this paper we present different approaches to the problem of fuzzy rules extraction by using a combination of fuzzy clustering and genetic algorithms as the main tools. This combination of techniques let us define a hybrid system by which we can have different approaches in a fuzzy modeling process. For example, we can obtain a first approximation to the fuzzy rules that describe the system behavior represented by a collection of raw data, without any assumption about the structure of the data using a fuzzy clustering technique, and subsequently, these rules can be tuned using a genetic algorithm. Alternatively, this genetic algorithm can be used in order to generate and tune the fuzzy rules directly from the data with or without some priori information. Finally, their performances are compared.

Internet connectivity for mobile ad hoc networks: solutions and challenges

The interconnection of mobile ad hoc networks to fixed IP networks is one of the topics receiving more attention within the MANET working group of the IETF as well as in many research projects funded by the European Union. Several solutions have recently been proposed, but at this time it is unclear which ones offer the best performance compared to the others. In addition to introducing the main challenges and design options that need to be considered, we perform a simulation-based evaluation aiming at providing some insight on the performance of these approaches. These simulation results have proven themselves valuable by showing that some of the most eye-catching features of the proposed approaches have practical performance issues which need to be enhanced.

Multi-objective evolutionary computation and fuzzy optimization

Abstract In fuzzy optimization it is desirable that all fuzzy solutions under consideration be attainable, so that the decision maker will be able to make “a posteriori” decisions according to current decision environments. No additional optimization runs will be needed when the decision environment changes or when the decision maker needs to evaluate several decisions to establish the most appropriate ones. In this sense, multi-objective optimization is similar to fuzzy optimization, since it is also desirable to capture the Pareto front composing the solution. The Pareto front in a multi-objective problem can be interpreted as the fuzzy solution for a fuzzy problem. Multi-objective evolutionary algorithms have been shown in the last few years to be powerful techniques in solving multi-objective optimization problems because they can search for multiple Pareto solutions in a single run of the algorithm. In this contribution, we first introduce a multi-objective approach for nonlinear constrained optimization problems with fuzzy costs and constraints, and then an “ad hoc” multi-objective evolutionary algorithm to solve the former problem. A case study of a fuzzy optimization problem arising in some import–export companies in the south of Spain is analyzed and the proposed solutions from the evolutionary algorithm considered here are given.