Engineering Applications of Artificial Intelligence, 2010
Automatic discrimination of speech and music is an important tool in many multimedia applications... more Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a two-stage cascaded classification scheme. The cascaded classification scheme is composed of a statistical pattern recognition classifier followed by a genetic fuzzy system. For the first stage of the classification scheme, other widely used classifiers, such as neural networks and support vector machines, have also been considered in order to assess the robustness of the proposed classification scheme. Comparison with well-proven signal features is also performed. In this work, the most commonly used genetic learning algorithms (Michigan and Pittsburgh) have been evaluated in the proposed two-stage classification scheme. The genetic fuzzy system gives rise to an improvement of about 4% in the classification accuracy rate. Experimental results show the good performance of the proposed approach with a classification accuracy rate of about 97% for the best trial.
Engineering Applications of Artificial Intelligence, 2010
Grid computing is increasingly emerging as a promising platform for large-scale problems solving ... more Grid computing is increasingly emerging as a promising platform for large-scale problems solving in science, engineering and technology. Nevertheless, a major effort is still required to harness the high potential performance of such computational framework and in this sense, an important challenge is to develop new strategies that efficiently address scheduling on the distributed, heterogeneous and shared environment of grids. Fuzzy rule-based systems (FRBSs) models are dynamic and are currently attracting the interest of scheduling research community to obtain near-optimal solutions on grids. However, FRBSs performance is strongly related to the quality of their knowledge bases and thus, with the knowledge acquisition process. Due to the inherent dynamic nature and the typical complex search spaces of grids, automatically finding a high-quality knowledge base that accurately describes the fuzzy system is extremely relevant. In this work, we propose a scheduling system for grids considering a novel learning strategy inspired by Michigan and Pittsburgh approaches that applies genetic algorithms (GAs) to evolve the fuzzy rule bases and improves the classical learning strategies in terms of computational effort and convergence behaviour. In addition, experimental results show that the proposed schema significantly outperforms other extensively used scheduling strategies.
One of the issues increasingly being raised in international forums for engineering education qua... more One of the issues increasingly being raised in international forums for engineering education quality assurance is that of accreditation. This paper will notice that professional services are still subjected to specific regulations in some countries, either by the government itself, or by private self-regulating organizations, that obstruct the professional activities of foreign professionals. By virtue of globalization and free-trade agreements,
International Work-Conference on Artificial and NaturalNeural Networks, 2009
In the last few years, the Grid community has been growing very rapidly and many new components h... more In the last few years, the Grid community has been growing very rapidly and many new components have been proposed. In this sense, the scheduler represents a very relevant element that influences decisively on the grid system performance. The scheduling task of a set of heterogeneous, dynamically changing resources is a complex problem. Several scheduling systems have already been implemented; however, they still provide only “ad hoc” solutions to manage scheduling resources in a grid system. This paper presents a fuzzy scheduler obtained by means of evolving a previous fuzzy scheduler using Pittsburgh approach. This new evolutionary fuzzy scheduler improves the performance of the classical scheduling system.
International Conference on Computational Intelligence forModelling, Control and Automation, 2008
... Linares, Jaén. SPAIN {ajsantia, ajyuste, jemunoz, sgalan, maqueira, sbruque}@ujaen.es Abstrac... more ... Linares, Jaén. SPAIN {ajsantia, ajyuste, jemunoz, sgalan, maqueira, sbruque}@ujaen.es Abstract ... These simulation techniques are useful to compare our fuzzy logic algorithm with others schedulers used in prior literature, like Random or Round Robin (RR) with no cost. ...
European Society for Fuzzy Logic and Technology, 1999
The single evaluation of the rules of a knowledge base has a special significance in Fuzzy-Geneti... more The single evaluation of the rules of a knowledge base has a special significance in Fuzzy-Genetic Systems, as these systems use such evaluation in selection processes. This paper describes a methodology to evaluate rules of a knowledge base. The single evaluation of each rule will be carried out from the global evaluation of the knowledge base to which it belongs. Finally, this paper includes those aspects that can improve the behaviour of the above methodology and proposes a rules classification depending on their single evaluation. This classification will allow to add new uses to the single evaluations of rules.
International Work-Conference on the Interplay Between Natural and Artificial Computation, 2009
Descriptors are a powerful tool in digital image analysis. Performance of tasks such as image mat... more Descriptors are a powerful tool in digital image analysis. Performance of tasks such as image matching and object recognition is strongly dependent on the visual descriptors that are used. The dimension of the descriptor has a direct impact on the time the analysis take, and less dimensions are desirable for fast matching. In this paper we use a type of region called curvilinear region. This approach is based on Marr’s visual theory. Marr supposed that every object can be divided in its constituent parts, being this parts cylinders. So, we suppose also that in every image there must be curvilinear regions that are easy to detect. We propose a very short descriptor to use with these curvilinear regions in order to classify these regions for higher visual tasks.
International Symposium on Evolving Fuzzy Systems, 2006
Automatic speech/music discrimination has become a research topic of interest in the last years. ... more Automatic speech/music discrimination has become a research topic of interest in the last years. This paper presents a new approach for speech/music discrimination, which is based on an expert system that incorporates fuzzy rules into its knowledge base. The proposed scheme consists of three stages: 1) features extraction, 2) audio signal classification, and 3) selection of the best audio coder every 23 ms. The fuzzy expert system improves the accuracy rate of a GMM classifier when included into the classification stage. In order to select the best audio coder, the expert system takes information of the current and past frames into account. It is important to emphasize that the low computational cost of the proposed approach makes it feasible for real time applications
Automatic discrimination of speech and music is an important tool in many multimedia applications... more Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a set of features derived from fundamental frequency (F0) estimation. Comparison between the proposed set of features and some commonly used timbral features is performed, aiming to assess the good discriminatory power of the proposed F0-based feature set. The classification scheme is composed of a classical Statistical Pattern Recognition classifier followed by a Fuzzy Rules Based System. Comparison with other well-proven classification schemes is also performed. Experimental results reveal that our speech/music discriminator is robust enough, making it suitable for a wide variety of multimedia applications.
One of foremost problems in stand-alone photovoltaic systems consists on the election of a strate... more One of foremost problems in stand-alone photovoltaic systems consists on the election of a strategy for charge controllers. The charge controllers main function is the accumulation system protection, and this leads to an extension of the batteries lifetime, thus reducing, the long term economic cost of the installation. This document describes a Fuzzy Logic based charge controller.
European Society for Fuzzy Logic and Technology, 2001
Abstract Charge regulators of the batteries are one of the,parts,most,critical in,stand-alone pho... more Abstract Charge regulators of the batteries are one of the,parts,most,critical in,stand-alone photovoltaic systems. The economic,cost of the complete installation, for a long period of time, depends on their correct operation. This document,presents,a Fuzzy,Logic Controller for the,charge,regulation,in stand-alone,photovoltaic,systems.,The optimisation, in energy management, obtained with this controller improves,the life-time of the batteries, the operation of the photovoltaic system and the total cost,
□ Automatic discrimination of speech and music is an important tool in many multimedia applicatio... more □ Automatic discrimination of speech and music is an important tool in many multimedia applications. This article presents an evolutionary, fuzzy, rules-based speech/music discrimination approach for intelligent audio coding, which exploits only one simple feature, called ...
Engineering Applications of Artificial Intelligence, 2008
This paper introduces a binary particle swarm optimization-based method to accomplish optimal loc... more This paper introduces a binary particle swarm optimization-based method to accomplish optimal location of biomass-fuelled systems for distributed power generation. The approach also provides the supply area for the biomass plant and takes technical constraints into account. This issue can be formulated as a nonlinear optimization problem. In rural or radial distribution networks the main technical constraint is the impact on the voltage profile. Biomass is one of the most promising renewable energy sources in Europe, but more research is required to prove that power generation from biomass is both technically and economically viable. Forest residues are here considered as biomass source, and the fitness function to be optimized is the profitability index. A fair comparison between the proposed algorithm and genetic algorithms (GAs) is performed. For such goal, convergence curves of the average profitability index versus number of iterations are computed. The proposed algorithm reaches a better solution than GAs when considering similar computational cost (similar number of evaluations).
This paper deals with the application and comparison of several metaheuristic techniques to optim... more This paper deals with the application and comparison of several metaheuristic techniques to optimize the placement and supply area of biomass-fueled power plants. Both, trajectory and population-based methods are applied for our goal. In particular, two well-known trajectory method, such as Simulated Annealing (SA) and Tabu Search (TS), and two commonly used population-based methods, such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are hereby considered. In addition, a new binary PSO algorithm has been proposed, which incorporates an inertia weight factor, like the classical continuous approach. The fitness function for the metaheuristics is the profitability index, defined as the ratio between the net present value and the initial investment. In this work, forest residues are considered as biomass source, and the problem constraints are: the generation system must be located inside the supply area, and its maximum electric power is 5 MW. The comparative results obtained by all considered metaheuristics are discussed. Random walk has also been assessed for the problem we deal with.
This paper introduces a method to minimize distributed PSO algorithm execution time in a grid com... more This paper introduces a method to minimize distributed PSO algorithm execution time in a grid computer environment, based on a reduction in the information interchanged among the demes involved in the process of finding the best global fitness solution. Demes usually interchange the best global fitness solution they found at each iteration. Instead of this, we propose to interchange information only after an specified number of iterations are concluded. By applying this technique, it is possible to get a very significant execution time decrease without any loss of solution quality.
Engineering Applications of Artificial Intelligence, 2007
Stock market prediction is important and of great interest because successful prediction of stock... more Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm is capable of accurately predicting stock market return. We attempt to model and predict the return on stock price index of the Istanbul Stock Exchange (ISE) with ANFIS. We use six macroeconomic variables and three indices as input variables. The experimental results reveal that the model successfully forecasts the monthly return of ISE National 100 Index with an accuracy rate of 98.3%. ANFIS provides a promising alternative for stock market prediction. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock price index return.
International Journal of Advanced Manufacturing Technology, 2000
Computer vision has arisen as one of the most important application areas in manufacturing proces... more Computer vision has arisen as one of the most important application areas in manufacturing processes. This work shows a new real-time texture analysis for medium-density fiberboard with melamine paper, using edge detection techniques and threshold detection methods. To minimize the time of identification of defects, the images of fiberboard are sent to a grid system. In a first phase, several tests are carried out using different image resolutions and sizes. In a second phase, to optimize the system, with the best resolution obtained and using a grid system, our aim is to minimize the time of detection of possible defects without jeopardizing the performance of the quality control system. Results show that, using accurate resolutions, the error detection process is quicker and the defect identification rate significantly improves.
Information Processing and Management of Uncertainty, 2010
Grid computing has arisen as the next-generation infrastructure for high demand computational app... more Grid computing has arisen as the next-generation infrastructure for high demand computational applications founded on the collaboration and coordination of a large set of distributed resources. The need to satisfy both users and network administrators QoS demands in such highly changing environments requires the consideration of adaptive scheduling strategies dealing with inherent dynamism and uncertainty. In this paper, a meta-scheduler based on Fuzzy Rule-Based Systems is proposed for scheduling in grid computing. Moreover, a new learning strategy inspired by stochastic optimization algorithm Differential Evolution (DE), is incorporated for the evolution of expert system knowledge or rules bases. Simulation results show that knowledge acquisition process is improved in terms of convergence behaviour and final result in comparison to other evolutionary strategy, genetic Pittsburgh approach. Also, the fuzzy meta-scheduler performance is compared to other extended scheduling strategy, EASY-Backfilling in diverse criteria such as flowtime, tardiness and machine usage.
... This work introduces a new method for the fuzzy rule evolution that forms an expert system kn... more ... This work introduces a new method for the fuzzy rule evolution that forms an expert system knowledge: the Knowledge Acquisition with a Swarm Intelligence Approach (KASIA). ... The suggested learning strategy, KASIA, is introduced in Section III. ...
IEEE International Conference on Fuzzy Systems, 2007
Automatic speech/music discrimination is an important tool used in many multimedia applications, ... more Automatic speech/music discrimination is an important tool used in many multimedia applications, becoming a research topic of interest in the last years. This paper presents our last works in the speech/music discrimination field, aiming to improve the coding efficiency of standard audio coders (i.e. MP3, AAC) when speech and music signals are involved. In order to discriminate between speech and
Engineering Applications of Artificial Intelligence, 2010
Automatic discrimination of speech and music is an important tool in many multimedia applications... more Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a two-stage cascaded classification scheme. The cascaded classification scheme is composed of a statistical pattern recognition classifier followed by a genetic fuzzy system. For the first stage of the classification scheme, other widely used classifiers, such as neural networks and support vector machines, have also been considered in order to assess the robustness of the proposed classification scheme. Comparison with well-proven signal features is also performed. In this work, the most commonly used genetic learning algorithms (Michigan and Pittsburgh) have been evaluated in the proposed two-stage classification scheme. The genetic fuzzy system gives rise to an improvement of about 4% in the classification accuracy rate. Experimental results show the good performance of the proposed approach with a classification accuracy rate of about 97% for the best trial.
Engineering Applications of Artificial Intelligence, 2010
Grid computing is increasingly emerging as a promising platform for large-scale problems solving ... more Grid computing is increasingly emerging as a promising platform for large-scale problems solving in science, engineering and technology. Nevertheless, a major effort is still required to harness the high potential performance of such computational framework and in this sense, an important challenge is to develop new strategies that efficiently address scheduling on the distributed, heterogeneous and shared environment of grids. Fuzzy rule-based systems (FRBSs) models are dynamic and are currently attracting the interest of scheduling research community to obtain near-optimal solutions on grids. However, FRBSs performance is strongly related to the quality of their knowledge bases and thus, with the knowledge acquisition process. Due to the inherent dynamic nature and the typical complex search spaces of grids, automatically finding a high-quality knowledge base that accurately describes the fuzzy system is extremely relevant. In this work, we propose a scheduling system for grids considering a novel learning strategy inspired by Michigan and Pittsburgh approaches that applies genetic algorithms (GAs) to evolve the fuzzy rule bases and improves the classical learning strategies in terms of computational effort and convergence behaviour. In addition, experimental results show that the proposed schema significantly outperforms other extensively used scheduling strategies.
One of the issues increasingly being raised in international forums for engineering education qua... more One of the issues increasingly being raised in international forums for engineering education quality assurance is that of accreditation. This paper will notice that professional services are still subjected to specific regulations in some countries, either by the government itself, or by private self-regulating organizations, that obstruct the professional activities of foreign professionals. By virtue of globalization and free-trade agreements,
International Work-Conference on Artificial and NaturalNeural Networks, 2009
In the last few years, the Grid community has been growing very rapidly and many new components h... more In the last few years, the Grid community has been growing very rapidly and many new components have been proposed. In this sense, the scheduler represents a very relevant element that influences decisively on the grid system performance. The scheduling task of a set of heterogeneous, dynamically changing resources is a complex problem. Several scheduling systems have already been implemented; however, they still provide only “ad hoc” solutions to manage scheduling resources in a grid system. This paper presents a fuzzy scheduler obtained by means of evolving a previous fuzzy scheduler using Pittsburgh approach. This new evolutionary fuzzy scheduler improves the performance of the classical scheduling system.
International Conference on Computational Intelligence forModelling, Control and Automation, 2008
... Linares, Jaén. SPAIN {ajsantia, ajyuste, jemunoz, sgalan, maqueira, sbruque}@ujaen.es Abstrac... more ... Linares, Jaén. SPAIN {ajsantia, ajyuste, jemunoz, sgalan, maqueira, sbruque}@ujaen.es Abstract ... These simulation techniques are useful to compare our fuzzy logic algorithm with others schedulers used in prior literature, like Random or Round Robin (RR) with no cost. ...
European Society for Fuzzy Logic and Technology, 1999
The single evaluation of the rules of a knowledge base has a special significance in Fuzzy-Geneti... more The single evaluation of the rules of a knowledge base has a special significance in Fuzzy-Genetic Systems, as these systems use such evaluation in selection processes. This paper describes a methodology to evaluate rules of a knowledge base. The single evaluation of each rule will be carried out from the global evaluation of the knowledge base to which it belongs. Finally, this paper includes those aspects that can improve the behaviour of the above methodology and proposes a rules classification depending on their single evaluation. This classification will allow to add new uses to the single evaluations of rules.
International Work-Conference on the Interplay Between Natural and Artificial Computation, 2009
Descriptors are a powerful tool in digital image analysis. Performance of tasks such as image mat... more Descriptors are a powerful tool in digital image analysis. Performance of tasks such as image matching and object recognition is strongly dependent on the visual descriptors that are used. The dimension of the descriptor has a direct impact on the time the analysis take, and less dimensions are desirable for fast matching. In this paper we use a type of region called curvilinear region. This approach is based on Marr’s visual theory. Marr supposed that every object can be divided in its constituent parts, being this parts cylinders. So, we suppose also that in every image there must be curvilinear regions that are easy to detect. We propose a very short descriptor to use with these curvilinear regions in order to classify these regions for higher visual tasks.
International Symposium on Evolving Fuzzy Systems, 2006
Automatic speech/music discrimination has become a research topic of interest in the last years. ... more Automatic speech/music discrimination has become a research topic of interest in the last years. This paper presents a new approach for speech/music discrimination, which is based on an expert system that incorporates fuzzy rules into its knowledge base. The proposed scheme consists of three stages: 1) features extraction, 2) audio signal classification, and 3) selection of the best audio coder every 23 ms. The fuzzy expert system improves the accuracy rate of a GMM classifier when included into the classification stage. In order to select the best audio coder, the expert system takes information of the current and past frames into account. It is important to emphasize that the low computational cost of the proposed approach makes it feasible for real time applications
Automatic discrimination of speech and music is an important tool in many multimedia applications... more Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a set of features derived from fundamental frequency (F0) estimation. Comparison between the proposed set of features and some commonly used timbral features is performed, aiming to assess the good discriminatory power of the proposed F0-based feature set. The classification scheme is composed of a classical Statistical Pattern Recognition classifier followed by a Fuzzy Rules Based System. Comparison with other well-proven classification schemes is also performed. Experimental results reveal that our speech/music discriminator is robust enough, making it suitable for a wide variety of multimedia applications.
One of foremost problems in stand-alone photovoltaic systems consists on the election of a strate... more One of foremost problems in stand-alone photovoltaic systems consists on the election of a strategy for charge controllers. The charge controllers main function is the accumulation system protection, and this leads to an extension of the batteries lifetime, thus reducing, the long term economic cost of the installation. This document describes a Fuzzy Logic based charge controller.
European Society for Fuzzy Logic and Technology, 2001
Abstract Charge regulators of the batteries are one of the,parts,most,critical in,stand-alone pho... more Abstract Charge regulators of the batteries are one of the,parts,most,critical in,stand-alone photovoltaic systems. The economic,cost of the complete installation, for a long period of time, depends on their correct operation. This document,presents,a Fuzzy,Logic Controller for the,charge,regulation,in stand-alone,photovoltaic,systems.,The optimisation, in energy management, obtained with this controller improves,the life-time of the batteries, the operation of the photovoltaic system and the total cost,
□ Automatic discrimination of speech and music is an important tool in many multimedia applicatio... more □ Automatic discrimination of speech and music is an important tool in many multimedia applications. This article presents an evolutionary, fuzzy, rules-based speech/music discrimination approach for intelligent audio coding, which exploits only one simple feature, called ...
Engineering Applications of Artificial Intelligence, 2008
This paper introduces a binary particle swarm optimization-based method to accomplish optimal loc... more This paper introduces a binary particle swarm optimization-based method to accomplish optimal location of biomass-fuelled systems for distributed power generation. The approach also provides the supply area for the biomass plant and takes technical constraints into account. This issue can be formulated as a nonlinear optimization problem. In rural or radial distribution networks the main technical constraint is the impact on the voltage profile. Biomass is one of the most promising renewable energy sources in Europe, but more research is required to prove that power generation from biomass is both technically and economically viable. Forest residues are here considered as biomass source, and the fitness function to be optimized is the profitability index. A fair comparison between the proposed algorithm and genetic algorithms (GAs) is performed. For such goal, convergence curves of the average profitability index versus number of iterations are computed. The proposed algorithm reaches a better solution than GAs when considering similar computational cost (similar number of evaluations).
This paper deals with the application and comparison of several metaheuristic techniques to optim... more This paper deals with the application and comparison of several metaheuristic techniques to optimize the placement and supply area of biomass-fueled power plants. Both, trajectory and population-based methods are applied for our goal. In particular, two well-known trajectory method, such as Simulated Annealing (SA) and Tabu Search (TS), and two commonly used population-based methods, such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are hereby considered. In addition, a new binary PSO algorithm has been proposed, which incorporates an inertia weight factor, like the classical continuous approach. The fitness function for the metaheuristics is the profitability index, defined as the ratio between the net present value and the initial investment. In this work, forest residues are considered as biomass source, and the problem constraints are: the generation system must be located inside the supply area, and its maximum electric power is 5 MW. The comparative results obtained by all considered metaheuristics are discussed. Random walk has also been assessed for the problem we deal with.
This paper introduces a method to minimize distributed PSO algorithm execution time in a grid com... more This paper introduces a method to minimize distributed PSO algorithm execution time in a grid computer environment, based on a reduction in the information interchanged among the demes involved in the process of finding the best global fitness solution. Demes usually interchange the best global fitness solution they found at each iteration. Instead of this, we propose to interchange information only after an specified number of iterations are concluded. By applying this technique, it is possible to get a very significant execution time decrease without any loss of solution quality.
Engineering Applications of Artificial Intelligence, 2007
Stock market prediction is important and of great interest because successful prediction of stock... more Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm is capable of accurately predicting stock market return. We attempt to model and predict the return on stock price index of the Istanbul Stock Exchange (ISE) with ANFIS. We use six macroeconomic variables and three indices as input variables. The experimental results reveal that the model successfully forecasts the monthly return of ISE National 100 Index with an accuracy rate of 98.3%. ANFIS provides a promising alternative for stock market prediction. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock price index return.
International Journal of Advanced Manufacturing Technology, 2000
Computer vision has arisen as one of the most important application areas in manufacturing proces... more Computer vision has arisen as one of the most important application areas in manufacturing processes. This work shows a new real-time texture analysis for medium-density fiberboard with melamine paper, using edge detection techniques and threshold detection methods. To minimize the time of identification of defects, the images of fiberboard are sent to a grid system. In a first phase, several tests are carried out using different image resolutions and sizes. In a second phase, to optimize the system, with the best resolution obtained and using a grid system, our aim is to minimize the time of detection of possible defects without jeopardizing the performance of the quality control system. Results show that, using accurate resolutions, the error detection process is quicker and the defect identification rate significantly improves.
Information Processing and Management of Uncertainty, 2010
Grid computing has arisen as the next-generation infrastructure for high demand computational app... more Grid computing has arisen as the next-generation infrastructure for high demand computational applications founded on the collaboration and coordination of a large set of distributed resources. The need to satisfy both users and network administrators QoS demands in such highly changing environments requires the consideration of adaptive scheduling strategies dealing with inherent dynamism and uncertainty. In this paper, a meta-scheduler based on Fuzzy Rule-Based Systems is proposed for scheduling in grid computing. Moreover, a new learning strategy inspired by stochastic optimization algorithm Differential Evolution (DE), is incorporated for the evolution of expert system knowledge or rules bases. Simulation results show that knowledge acquisition process is improved in terms of convergence behaviour and final result in comparison to other evolutionary strategy, genetic Pittsburgh approach. Also, the fuzzy meta-scheduler performance is compared to other extended scheduling strategy, EASY-Backfilling in diverse criteria such as flowtime, tardiness and machine usage.
... This work introduces a new method for the fuzzy rule evolution that forms an expert system kn... more ... This work introduces a new method for the fuzzy rule evolution that forms an expert system knowledge: the Knowledge Acquisition with a Swarm Intelligence Approach (KASIA). ... The suggested learning strategy, KASIA, is introduced in Section III. ...
IEEE International Conference on Fuzzy Systems, 2007
Automatic speech/music discrimination is an important tool used in many multimedia applications, ... more Automatic speech/music discrimination is an important tool used in many multimedia applications, becoming a research topic of interest in the last years. This paper presents our last works in the speech/music discrimination field, aiming to improve the coding efficiency of standard audio coders (i.e. MP3, AAC) when speech and music signals are involved. In order to discriminate between speech and
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