The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques

The paper describes VEX-93 as a hybrid environment for developing knowledge-based and problem solver systems. It integrates methods and techniques from artificial intelligence, image and signal processing and data analysis, which can be mixed. Two hierarchical levels of reasoning contains an intelligent toolbox with one upper strategic inference engine and four lower ones containing specific reasoning models: truth-functional (rule-based), probabilistic (causal networks), fuzzy (rule-based) and case-based (frames). There are image/signal processing-analysis capabilities in the form of programming languages with more than one hundred primitive functions. User-made programs are embeddable within knowledge basis, allowing the combination of perception and reasoning. The data analyzer toolbox contains a collection of numerical classification, pattern recognition and ordination methods, with neural network tools and a data base query language at inference engines's disposal. VEX-93 is an open system able to communicate with external computer programs relevant to a particular application. Metaknowledge can be used for elaborate conclusions, and man-machine interaction includes, besides windows and graphical interfaces, acceptance of voice commands and production of speech output. The system was conceived for real-world applications in general domains, but an example of a concrete medical diagnostic support system at present under completion as a cuban-spanish project is mentioned. Present version of VEX-93 is a huge system composed by about one and half millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version

Fuzzy heterogeneous neurons for imprecise classification problems

In the classical neuron model, inputs are continuous real-valued quantities. However, in many important domains from the real world, objects are described by a mixture of continuous and discrete variables, usually containing missing information and uncertainty. In this paper, a general class of neuron models accepting heterogeneous inputs in the form of mixtures of continuous (crisp and/or fuzzy) and discrete quantities admitting missing data is presented. From these, several particular models can be derived as instances and different neural architectures constructed with them. Such models deal in a natural way with problems for which information is imprecise or even missing. Their possibilities in classification and diagnostic problems are here illustrated by experiments with data from a real-world domain in the field of environmental studies. These experiments show that such neurons can both learn and classify complex data very effectively in the presence of uncertain information.Peer ReviewedPostprint (author's final draft

Fuzzy heterogeneous neural networks for signal forecasting

Fuzzy heterogeneous neural networks are recently introduced models based on neurons accepting heterogeneous inputs (i.e. mixtures of numerical and non-numerical information possibly with missing data) with either crisp or imprecise character, which can be coupled with classical neurons. This paper compares the effectiveness of this kind of networks with time-delay and recurrent architectures that use classical neuron models and training algorithms in a signal forecasting problem, in the context of finding models of the central nervous system controllers.Peer ReviewedPostprint (author's final draft

Capital controls and spillover effects: evidence from Latin-American countries

The surge in capital inflows towards emerging countries after 2009 has revived the debate about capital controls. This paper analyzes some of the international implications of restrictions on capital inflows. Focusing on a sample of Latin-American countries, we use detailed balance of payments data and higher frequency data on portfolio bond and equity flows to investigate the potential spillover effects that capital controls imposed in one country may have on neighboring economies. Using various econometric approaches, we find that a rise in the Brazilian tax on portfolio bond inflows has been affecting other Latin-American economies through significant surges in portfolio funds invested either in fixed income or equity securities. The effect is usually short lasting and followed by rapid reductions in those inflows. Yet it can be large. According to our estimates, the increase in the Brazilian tax on portfolio bond inflows may account for the entire surge in bond inflows to Mexico between September and October 2010.capital flows, capital controls, spillovers, Latin America, VAR.

Optimal Monetary Policy Rules when the Current Account Matters

This paper explores the implications for optimal monetary policy rules of including a target for the current account (CA) among central bank (CB) objectives. Using a simple but realistic macroeconomic model of the Chilean economy and standard dynamic programming with forward looking variables, the paper finds optimal rules under alternative specifications of a CB quadratic loss-function. The results show that optimal policy reactions change substantially when there is an objective for the CA (besides inflation). Furthermore, once the CA enters the CB objective function, the relative importance of output vis-à-vis inflation variability is less crucial in determining optimal policy rules. Using a simple 2-equation model, the paper then investigates the implications for monetary policy of having an asymmetric objective with respect to the CA. Specifically, it considers the case in which negative deviations from target are considered to be relatively more costly. The results indicate that, in this non-quadratic set-up, monetary policy is clearly more aggressive against positive inflation shocks than in the symmetric case.

Modeling the input-output behaviour of wastewater treatment plants using soft computing techniques

Wastewater Treatment Plants (WWTPs) control and prediction under a wide range of operating conditions is an important goal in order to avoid breaking of environmental balance, keep the system in stable operating conditions and suitable decision-making. In this respect, the availability of models characterizing WWTP behaviour as a dynamic system, is a necessary first step. However, due to the high complexity of the WWTP processes and the heterogeneity, incompleteness and imprecision of WWTP data, finding suitable models poses substantial problems. In this paper, an approach via soft computing techniques is sought, in particular, by experimenting with fuzzy heterogeneous time-delay neural networks to characterize the time variation of outgoing variables. Experimental results show that these networks are able to characterize WWTP behaviour in a statistically satisfactory sense and also that they perform better than other well-established neural network mode.Peer ReviewedPostprint (published version

Boletín oficial de la provincia de León: Num. 4 (09/07/1924)

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2011-201

Using fuzzy heterogeneous neural networks to learn a model of the central nervous system control

Fuzzy heterogeneous networks based on similarity are recently introduced feed-forward neural network models composed by neurons of a general class whose inputs are mixtures of continuous (crisp and/or fuzzy) with discrete quantities, admitting also missing data. These networks have activation functions based on similarity relations between inputs and neuron weights. They can be coupled with classical neurons in hybrid network architectures, trained with genetic algorithms. This paper compares the e ectivity of this fuzzy heterogeneous model based on similarity with the classical feed-forward one (scalar-product driven and using crisp quantities) in a time-series prediction setting. The results obtained show a remarkable increasing performance when departing from the classical neuron and a comparable one when confronted with other current powerful techniques, such as the FIR methodology.Peer ReviewedPostprint (author's final draft

Boletín oficial de la provincia de León: Num. 57 (11/08/1922)

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2011-201

Boletín oficial de la provincia de León: Num. 4 (09/07/1924)

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2011-201