Data Science and Knowledge Engineering for Sensing Decision Support最新文献

{"title":"AI 2.0: Augmented Intelligence","authors":"P. Lisboa","doi":"10.1142/9789813273238_0003","DOIUrl":"https://doi.org/10.1142/9789813273238_0003","url":null,"abstract":"Computational intelligence (CI) models are often evaluated on the basis of predictive performance, lacking appropriate consideration of other aspects which might make a claim to the intelligence of the model and which can be critical for their use by a subject expert who is not a CI expert. Yet appearances can be deceiving, especially with summary performance measures e.g. AUROC. This is especially the case for non-linear models given their ability to exploit any weaknesses in the data, for instance structural artefacts which can add confounding effects. In addition, many applied CI models work well for well classified cases but cannot explain predictions for borderline cases. In other words, they confirm to expert users what they already know but do not add insights to the data in the difficult cases for which CI is most needed. There is a drive for the use of CI to complement rather than automate decision making This is fundamental to make CI useful in practice and has been termed Augmented Intelligence, or AI 2.0. The talk will illustrate some of the pitfalls in the design and validation of databased models. It will then describe how rules can be efficiently derived from neural networks so openi ng the black-box. An alternative and popular way of presenting and using complex models e.g. to clinicians, is the use of nomograms. They will be derived from SVMs so extending this graphical approach to non-linear models. Finally, the concept of case-based reasoning will be explored using information geometry to calculate similarity metrics directly to identify patients-like-mine with reference to specific clinical queries e.g. diagnosis or prognosis. This comprises a statistically principled intelligent query system for case-based reasoning, enabling a subject expert to diagnose probabilistic classifiers with respect to patient cohorts where there are significantly more or fewer cases of interest, separating them from mixed groups for whom more information is certain to be required. This provides a direct route to interpretation and a way for subject experts to access generic non-linear models as a smart approach to data retrieval, complementing the numerical outputs.","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132047092","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}

{"title":"State-of-the-art evolutionary algorithms for dynamic multiobjective optimization","authors":"G. Yen","doi":"10.1142/9789813273238_0002","DOIUrl":"https://doi.org/10.1142/9789813273238_0002","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130134580","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}

{"title":"Interval-valued Pythagorean fuzzy interaction aggregation operators and their application in multiple attribute decision making","authors":"Wei Yang, Yongfeng Pang","doi":"10.1142/9789813273238_0023","DOIUrl":"https://doi.org/10.1142/9789813273238_0023","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115106826","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}

{"title":"Evaluation of smart cities with integrated hesitant fuzzy linguistic AHP–COPRAS method","authors":"Esin Mukul, Merve Güler, G. Büyüközkan","doi":"10.1142/9789813273238_0149","DOIUrl":"https://doi.org/10.1142/9789813273238_0149","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133819400","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}

{"title":"Garment fit evaluation using artificial intellegence technology","authors":"Kaixuan Liu, H. Dai, Yanbo Yanbo, Yongmei Deng, Yongchi Xu, Yue Wang, Xueqing Zhao, Tao Xue","doi":"10.1142/9789813273238_0186","DOIUrl":"https://doi.org/10.1142/9789813273238_0186","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134311296","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}

{"title":"Improvements of categorical propositions on quantification and systemization","authors":"Yinsheng Zhang","doi":"10.1142/9789813273238_0103","DOIUrl":"https://doi.org/10.1142/9789813273238_0103","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133030017","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}

{"title":"Goodwin model via p-fuzzy system","authors":"D. Sánchez, L. C. Barros, E. Esmi, A. Miebach","doi":"10.1142/9789813273238_0124","DOIUrl":"https://doi.org/10.1142/9789813273238_0124","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133125769","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}

{"title":"Term frequency occurrences on web pages for textual information retrieval","authors":"Karthika Sivapathasundaram, Xiaochun Cheng, M. Petridis","doi":"10.1142/9789813273238_0075","DOIUrl":"https://doi.org/10.1142/9789813273238_0075","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133137696","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}

{"title":"Ensemble Evidential Editing k-NNs through rough set reducts","authors":"Asma Trabelsi, Zied Elouedi, E. Lefevre","doi":"10.1142/9789813273238_0083","DOIUrl":"https://doi.org/10.1142/9789813273238_0083","url":null,"abstract":"Ensemble classifier is one among the machine learning hot topics and it has been successfully applied in many practical applications. Since the construction of an optimal ensemble remains an open and complex problem, several heuristics for constructing good ensembles have been introduced for several years now. One alternative consists of integrating rough set reducts into ensemble systems. To the best of our knowledge, almost existing methods neglect knowledge imperfection, knowing that several real world databases suffer from some kinds of uncertainty and incompleteness. In this paper, we develop an ensemble Evidential Editing k-Nearest Neighbors classfier (EEk-NN) through rough set reducts for addressing data with evidential attributes. Experimentations in some real databases have been carried out with the aim of comparing our proposal to another existing approach.","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"453 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129349140","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}

{"title":"Compound trajectory optimization methodology for parafoil delivery system based on quantum genetic algorithm","authors":"Hao Sun, Qinglin Sun, Shunzhen Luo, Zengqiang Chen, Wannan Wu, Jin Tao","doi":"10.1142/9789813273238_0115","DOIUrl":"https://doi.org/10.1142/9789813273238_0115","url":null,"abstract":"","PeriodicalId":259425,"journal":{"name":"Data Science and Knowledge Engineering for Sensing Decision Support","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122242421","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}