Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851616
A. G. Contreras, M. Ceberio
Many real-life situations require that a match between quantities, behaviors, etc. be found. That is the case, for instance, when scientists try to find a fit between two sets of data, or a set of observations and a given model. Often such situations require that the minimum (or maximum) of a computed difference be found. These situations can be modeled as optimization problems. There exist multiple flavors of optimization problems: constrained and unconstrained (whether we are looking for the minimum - or maximum - of a function over the entire search space or only within the subspace of elements that satisfy some given constraints); local and global (whether we are looking solutions for the minimum within a neighborhood or among the whole search space); continuous, discrete, and mixed (whether the parameters of the problem at hand take their values all in discrete domains, all in continuous domains, or in a mix of these). In this article, we focus on continuous unconstrained global optimization and algorithms to solve such problems. Without loss of generality, we will discuss minimization. There exist many algorithms to address such problems. Most are based on interval computations for they provide a way to conduct a fully covering search in continuous domains where enumeration of alternatives is impossible. In this article, we propose to look at a specific type of algorithm: known as speculation, which consists in betting on which value is going to be the minimum we are looking for. More specifically, we propose to improve our speculative approach using different strategies. We present and discuss the results of a series of experiments comparing the performance of the speculative algorithm with the proposed strategies.
{"title":"Comparison of strategies for solving global optimization problems using speculation and interval computations","authors":"A. G. Contreras, M. Ceberio","doi":"10.1109/NAFIPS.2016.7851616","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851616","url":null,"abstract":"Many real-life situations require that a match between quantities, behaviors, etc. be found. That is the case, for instance, when scientists try to find a fit between two sets of data, or a set of observations and a given model. Often such situations require that the minimum (or maximum) of a computed difference be found. These situations can be modeled as optimization problems. There exist multiple flavors of optimization problems: constrained and unconstrained (whether we are looking for the minimum - or maximum - of a function over the entire search space or only within the subspace of elements that satisfy some given constraints); local and global (whether we are looking solutions for the minimum within a neighborhood or among the whole search space); continuous, discrete, and mixed (whether the parameters of the problem at hand take their values all in discrete domains, all in continuous domains, or in a mix of these). In this article, we focus on continuous unconstrained global optimization and algorithms to solve such problems. Without loss of generality, we will discuss minimization. There exist many algorithms to address such problems. Most are based on interval computations for they provide a way to conduct a fully covering search in continuous domains where enumeration of alternatives is impossible. In this article, we propose to look at a specific type of algorithm: known as speculation, which consists in betting on which value is going to be the minimum we are looking for. More specifically, we propose to improve our speculative approach using different strategies. We present and discuss the results of a series of experiments comparing the performance of the speculative algorithm with the proposed strategies.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125259906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851586
Fabio Blanco-Mesa, J. M. Lindahl
The aim of the paper is to develop new aggregation operators using Bonferroni means, ordered weighted averaging (OWA) operators and some distance measures. We introduce the Bonferroni-Hamming weighted distance, Bonferroni OWA distance, and Bonferroni distances with OWA operators and weighted averages. The main advantages of using these operators are that they allow considering different aggregations contexts, multiple-comparison between each argument and distance measures in the same formulation.
{"title":"Bonferroni distances with OWA operators","authors":"Fabio Blanco-Mesa, J. M. Lindahl","doi":"10.1109/NAFIPS.2016.7851586","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851586","url":null,"abstract":"The aim of the paper is to develop new aggregation operators using Bonferroni means, ordered weighted averaging (OWA) operators and some distance measures. We introduce the Bonferroni-Hamming weighted distance, Bonferroni OWA distance, and Bonferroni distances with OWA operators and weighted averages. The main advantages of using these operators are that they allow considering different aggregations contexts, multiple-comparison between each argument and distance measures in the same formulation.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114585142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851614
Sarah Greenfield, F. Chiclana, S. Dick
Interval-valued complex fuzzy logic is able to handle scenarios where both seasonality and uncertainty feature. The interval-valued complex fuzzy set is defined, and the interval-valued complex fuzzy inferencing system outlined. Highly pertinent to complex fuzzy logic operations is the concept of rotational invariance, which is an intuitive and desirable characteristic. Interval-valued complex fuzzy logic is driven by interval-valued join and meet operations. Four pairs of alternative algorithms for these operations are specified; three pairs possesses the attribute of rotational invariance, whereas the other pair lacks this characteristic.
{"title":"Join and meet operations for interval-valued complex fuzzy logic","authors":"Sarah Greenfield, F. Chiclana, S. Dick","doi":"10.1109/NAFIPS.2016.7851614","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851614","url":null,"abstract":"Interval-valued complex fuzzy logic is able to handle scenarios where both seasonality and uncertainty feature. The interval-valued complex fuzzy set is defined, and the interval-valued complex fuzzy inferencing system outlined. Highly pertinent to complex fuzzy logic operations is the concept of rotational invariance, which is an intuitive and desirable characteristic. Interval-valued complex fuzzy logic is driven by interval-valued join and meet operations. Four pairs of alternative algorithms for these operations are specified; three pairs possesses the attribute of rotational invariance, whereas the other pair lacks this characteristic.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126796998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851601
M. J. Wierman
Fuzzy measures go by different names in different disciplines. They can be called games, fuzzy measures, lower probabilities, capacities or beliefs. A solution is a weight on the underlying set that is in some sense consistent with the fuzzy measure. This paper discusses some methods of solving them. It also adds an solution method that is not part of any of the standard canons.
{"title":"Solving games","authors":"M. J. Wierman","doi":"10.1109/NAFIPS.2016.7851601","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851601","url":null,"abstract":"Fuzzy measures go by different names in different disciplines. They can be called games, fuzzy measures, lower probabilities, capacities or beliefs. A solution is a weight on the underlying set that is in some sense consistent with the fuzzy measure. This paper discusses some methods of solving them. It also adds an solution method that is not part of any of the standard canons.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132775857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851585
Fabio Blanco-Mesa, J. M. Lindahl, A. M. G. Lafuente
Fuzzy decision-making consists in making decisions under complex and uncertain environments where the information can be assessed with fuzzy sets and systems. The aim of this study is to review the main contributions in this field by using a bibliometric approach. For doing so, the article uses a wide range of bibliometric indicators including the citations and the h-index. Moreover, it also uses the VOS viewer software in order to map the main trends in this area. The work considers the leading journals, articles, authors, institutions and countries. The results indicate that the Zadeh L.A. led the origins of fuzzy research and Ronald Yager is the most prominent author in FDM. The USA was the traditional leader in this field with the most significant researcher. However, during the last years, this field is receiving more attention by Asian authors that are starting to lead the field. This discipline has a strong potential and the expectations for the future is that it will continue to grow.
{"title":"A bibliometric analysis of fuzzy decision making research","authors":"Fabio Blanco-Mesa, J. M. Lindahl, A. M. G. Lafuente","doi":"10.1109/NAFIPS.2016.7851585","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851585","url":null,"abstract":"Fuzzy decision-making consists in making decisions under complex and uncertain environments where the information can be assessed with fuzzy sets and systems. The aim of this study is to review the main contributions in this field by using a bibliometric approach. For doing so, the article uses a wide range of bibliometric indicators including the citations and the h-index. Moreover, it also uses the VOS viewer software in order to map the main trends in this area. The work considers the leading journals, articles, authors, institutions and countries. The results indicate that the Zadeh L.A. led the origins of fuzzy research and Ronald Yager is the most prominent author in FDM. The USA was the traditional leader in this field with the most significant researcher. However, during the last years, this field is receiving more attention by Asian authors that are starting to lead the field. This discipline has a strong potential and the expectations for the future is that it will continue to grow.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132588002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851588
T. Whalen
Different decision algorithms make different assumptions about the structure of a decision maker's anticipations about states and outcomes. A proper fit between the algorithm and the actual information available is needed for good decision support.
{"title":"Caring about uncertainty","authors":"T. Whalen","doi":"10.1109/NAFIPS.2016.7851588","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851588","url":null,"abstract":"Different decision algorithms make different assumptions about the structure of a decision maker's anticipations about states and outcomes. A proper fit between the algorithm and the actual information available is needed for good decision support.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124971585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851610
Mohammad Raoufi, N. G. Seresht, A. Fayek
Simulation has long been used in the construction domain to model construction systems. Simulation techniques (e.g., discrete event simulation, system dynamics, and agent-based modeling) are well-equipped to handle complex systems; however, they fail to account for the subjective uncertainties present in many construction systems. Fuzzy logic, on the other hand, is a powerful tool for dealing with subjective uncertainty; therefore, integrating these two techniques is advantageous in modeling construction systems. In this paper, we present an overview of simulation techniques in construction. Then, we introduce the advancements that have been made by incorporating fuzzy logic with simulation techniques, and we propose methodologies for developing fuzzy simulation models. Finally, we discuss the process of choosing a suitable simulation technique for construction modeling. In addition to providing an overview of simulation techniques accessible to the construction domain, the main contribution of this paper is in introducing methods for integrating fuzzy logic with simulation techniques.
{"title":"Overview of fuzzy simulation techniques in construction engineering and management","authors":"Mohammad Raoufi, N. G. Seresht, A. Fayek","doi":"10.1109/NAFIPS.2016.7851610","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851610","url":null,"abstract":"Simulation has long been used in the construction domain to model construction systems. Simulation techniques (e.g., discrete event simulation, system dynamics, and agent-based modeling) are well-equipped to handle complex systems; however, they fail to account for the subjective uncertainties present in many construction systems. Fuzzy logic, on the other hand, is a powerful tool for dealing with subjective uncertainty; therefore, integrating these two techniques is advantageous in modeling construction systems. In this paper, we present an overview of simulation techniques in construction. Then, we introduce the advancements that have been made by incorporating fuzzy logic with simulation techniques, and we propose methodologies for developing fuzzy simulation models. Finally, we discuss the process of choosing a suitable simulation technique for construction modeling. In addition to providing an overview of simulation techniques accessible to the construction domain, the main contribution of this paper is in introducing methods for integrating fuzzy logic with simulation techniques.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851620
P. Olague, O. Kosheleva, V. Kreinovich
Resilient modulus is a mechanical characteristic describing the stiffness of a pavement. Its value depends on the moisture level. In pavement construction, it is important to be able, knowing the resilient modulus corresponding to one moisture level, to predict resilient modulus corresponding to other moisture levels. There exists an empirical formula for this prediction. In this paper, we provide a possible theoretical explanation for this empirical formula.
{"title":"How resilient modulus of a pavement depends on moisture level: Towards a theoretical justification of a practically important empirical formula","authors":"P. Olague, O. Kosheleva, V. Kreinovich","doi":"10.1109/NAFIPS.2016.7851620","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851620","url":null,"abstract":"Resilient modulus is a mechanical characteristic describing the stiffness of a pavement. Its value depends on the moisture level. In pavement construction, it is important to be able, knowing the resilient modulus corresponding to one moisture level, to predict resilient modulus corresponding to other moisture levels. There exists an empirical formula for this prediction. In this paper, we provide a possible theoretical explanation for this empirical formula.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120949369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851591
A. D. S. Farias, V. S. Costa, R. Santiago, B. Bedregal
The Generalized Mixture functions—GM, proposed by Pereira et al. [1], are a generalized form an important type of aggregation function, defined by Yager and called Ordered Weighted Averaging functions — OWA [4].
{"title":"The image reduction process based on Generalized Mixture functions","authors":"A. D. S. Farias, V. S. Costa, R. Santiago, B. Bedregal","doi":"10.1109/NAFIPS.2016.7851591","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851591","url":null,"abstract":"The Generalized Mixture functions—GM, proposed by Pereira et al. [1], are a generalized form an important type of aggregation function, defined by Yager and called Ordered Weighted Averaging functions — OWA [4].","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123054679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/NAFIPS.2016.7851602
Salem B. Bacha, B. Bede
In the present paper we propose, and investigate different constructive approaches to approximate Mamdani fuzzy systems, using Takagi-Sugeno systems. The Takagi- Sugeno fuzzy systems that we construct will be based on a piecewise linear approximation, an interpolation polynomial, and an approach based on cubic splines. Since using a Mamdani system with Center of Gravity defuzzification is computationally expensive, a Takagi-Sugeno system is a natural idea to reduce computation and keep high quality on the performance side. We extend these approaches to fuzzy rule bases with multiple antecedents. As application we construct a computing with words system using the proposed approach, and also we use the proposed approach in a video game.
{"title":"On Takagi Sugeno approximations of Mamdani fuzzy systems","authors":"Salem B. Bacha, B. Bede","doi":"10.1109/NAFIPS.2016.7851602","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851602","url":null,"abstract":"In the present paper we propose, and investigate different constructive approaches to approximate Mamdani fuzzy systems, using Takagi-Sugeno systems. The Takagi- Sugeno fuzzy systems that we construct will be based on a piecewise linear approximation, an interpolation polynomial, and an approach based on cubic splines. Since using a Mamdani system with Center of Gravity defuzzification is computationally expensive, a Takagi-Sugeno system is a natural idea to reduce computation and keep high quality on the performance side. We extend these approaches to fuzzy rule bases with multiple antecedents. As application we construct a computing with words system using the proposed approach, and also we use the proposed approach in a video game.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132582361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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