Pub Date : 2022-07-08DOI: 10.1007/978-3-031-16609-9_20
E. Fekhari, B. Iooss, Joseph Mur'e, L. Pronzato, M. Rendas
{"title":"Model Predictivity Assessment: Incremental Test-Set Selection and Accuracy Evaluation","authors":"E. Fekhari, B. Iooss, Joseph Mur'e, L. Pronzato, M. Rendas","doi":"10.1007/978-3-031-16609-9_20","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_20","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125066775","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}
This paper proposes a particle swarm optimizer to solve the variable weighting problem in subspace clustering of high-dimensional data. Many subspace clustering algorithms fail to yield good cluster quality because they do not employ an efficient search strategy. In this paper, we are interested in soft subspace clustering and design a suitable weighting k-means objective function, on which a change of variable weights is exponentially reflected. We transform the original constrained variable weighting problem into a problem with bound constraints using a potential solution coding method and we develop a particle swarm optimizer to minimize the objective function in order to obtain global optima to the variable weighting problem in clustering. Our experimental results on synthetic datasets show that the proposed algorithm greatly improves cluster quality. In addition, the result of the new algorithm is much less dependent on the initial cluster centroids.
{"title":"Particle swarm optimizer for variable weighting in clustering high-dimensional data","authors":"Yanping Lv, Shengrui Wang, Shaozi Li, Changle Zhou","doi":"10.1109/SIS.2009.4937842","DOIUrl":"https://doi.org/10.1109/SIS.2009.4937842","url":null,"abstract":"This paper proposes a particle swarm optimizer to solve the variable weighting problem in subspace clustering of high-dimensional data. Many subspace clustering algorithms fail to yield good cluster quality because they do not employ an efficient search strategy. In this paper, we are interested in soft subspace clustering and design a suitable weighting k-means objective function, on which a change of variable weights is exponentially reflected. We transform the original constrained variable weighting problem into a problem with bound constraints using a potential solution coding method and we develop a particle swarm optimizer to minimize the objective function in order to obtain global optima to the variable weighting problem in clustering. Our experimental results on synthetic datasets show that the proposed algorithm greatly improves cluster quality. In addition, the result of the new algorithm is much less dependent on the initial cluster centroids.","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128282828","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 : 2005-06-08DOI: 10.1109/SIS.2005.1501595
T. Pankiw
This review focuses on how honey bee responsiveness to sucrose is related to a correlated suite of foraging traits, called the honey bee foraging behavior syndrome. Behavior syndromes are reminiscent of human personalities. In general, the honey bee foraging syndrome is characterized as bees with low sucrose response thresholds begin foraging at younger ages than bees with high sucrose response thresholds. Sucrose response threshold in young pre-foraging aged bees predicts forage choice 2 to 3 weeks later. The relationship is such that bees with low sucrose response thresholds forage for resources with no or low sugar rewards such as water and pollen. Bees with higher sucrose response thresholds forage for nectar and return with nectar containing sugar concentrations that are positively correlated with individual sucrose response threshold. The honey bee provides one of the best studied cases of a natural behavioral syndrome from genes to behavior, having great potential for understanding social evolution, and the organization of a complex system.
{"title":"The honey bee foraging behavior syndrome: quantifying the response threshold model of division of labor","authors":"T. Pankiw","doi":"10.1109/SIS.2005.1501595","DOIUrl":"https://doi.org/10.1109/SIS.2005.1501595","url":null,"abstract":"This review focuses on how honey bee responsiveness to sucrose is related to a correlated suite of foraging traits, called the honey bee foraging behavior syndrome. Behavior syndromes are reminiscent of human personalities. In general, the honey bee foraging syndrome is characterized as bees with low sucrose response thresholds begin foraging at younger ages than bees with high sucrose response thresholds. Sucrose response threshold in young pre-foraging aged bees predicts forage choice 2 to 3 weeks later. The relationship is such that bees with low sucrose response thresholds forage for resources with no or low sugar rewards such as water and pollen. Bees with higher sucrose response thresholds forage for nectar and return with nectar containing sugar concentrations that are positively correlated with individual sucrose response threshold. The honey bee provides one of the best studied cases of a natural behavioral syndrome from genes to behavior, having great potential for understanding social evolution, and the organization of a complex system.","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134161415","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_23
F. Ambrosino, G. Giannini, A. Lepore, B. Palumbo, Gianluca Sposito
{"title":"Neural Network for the Statistical Process Control of HVAC Systems in Passenger Rail Vehicles","authors":"F. Ambrosino, G. Giannini, A. Lepore, B. Palumbo, Gianluca Sposito","doi":"10.1007/978-3-031-16609-9_23","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_23","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123048904","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_13
M. Flora, R. Renò
{"title":"Detecting States of Distress in Financial Markets: The Case of the Italian Sovereign Debt","authors":"M. Flora, R. Renò","doi":"10.1007/978-3-031-16609-9_13","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_13","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116196718","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_27
F. Piersimoni, Francesco Pantalone, R. Benedetti
{"title":"Spatially Balanced Indirect Sampling to Estimate the Coverage of the Agricultural Census","authors":"F. Piersimoni, Francesco Pantalone, R. Benedetti","doi":"10.1007/978-3-031-16609-9_27","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_27","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127423648","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_8
Fulvio Di Stefano, M. Gasparini
{"title":"Adaptive COVID-19 Screening of a Subpopulation","authors":"Fulvio Di Stefano, M. Gasparini","doi":"10.1007/978-3-031-16609-9_8","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_8","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116911896","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_3
C. D. Nuzzo, S. Ingrassia
{"title":"A Graphical Approach for the Selection of the Number of Clusters in the Spectral Clustering Algorithm","authors":"C. D. Nuzzo, S. Ingrassia","doi":"10.1007/978-3-031-16609-9_3","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_3","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116435603","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_25
T. Tuoto, Davide Di Cecco, A. Tancredi
{"title":"Population Size Estimation by Repeated Identifications of Units. A Bayesian Semi-parametric Mixture Model Approach","authors":"T. Tuoto, Davide Di Cecco, A. Tancredi","doi":"10.1007/978-3-031-16609-9_25","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_25","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129959899","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 : 1900-01-01DOI: 10.1007/978-3-031-16609-9_12
M. Pratesi
{"title":"Citizen Data and Citizen Science: A Challenge for Official Statistics","authors":"M. Pratesi","doi":"10.1007/978-3-031-16609-9_12","DOIUrl":"https://doi.org/10.1007/978-3-031-16609-9_12","url":null,"abstract":"","PeriodicalId":326240,"journal":{"name":"IEEE Symposium on Swarm Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130669482","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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