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Update of approximations in ordered information systems under variations of attribute and object set 属性和对象集变化下有序信息系统中近似值的更新
Advances in computational intelligence Pub Date : 2022-01-26 DOI: 10.1007/s43674-021-00011-x
Yan Li, Xiaoxue Wu, Qiang Hua
{"title":"Update of approximations in ordered information systems under variations of attribute and object set","authors":"Yan Li,&nbsp;Xiaoxue Wu,&nbsp;Qiang Hua","doi":"10.1007/s43674-021-00011-x","DOIUrl":"10.1007/s43674-021-00011-x","url":null,"abstract":"<div><p>Many collected data from real world applications often evolve when new attributes or objects are inserted or old ones are removed. The set approximations of ordered information systems (OIS) need to be updated from time to time for further data reduction, analysis, or decision-making. Incremental approaches are feasible and efficient techniques for updating approaches when any variation occurs. In this paper, considering OIS for multi-criteria classification problems, we discuss the principles of incrementally updating approximations in dominance relation based method in four different types of dynamic environments which combine the changes of both attribute set and object set. In each dynamic environment, the corresponding updating principles and algorithm are given with detail proofs. The experimental results and analysis on UCI data sets show that the proposed incremental approach outperforms the non-incremental method and the integration of current incremental algorithms in the implementation efficiency.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50515405","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}
引用次数: 0
Vibration analysis for fault detection in wind turbines using machine learning techniques 基于机器学习技术的风力发电机故障检测振动分析
Advances in computational intelligence Pub Date : 2022-01-10 DOI: 10.1007/s43674-021-00029-1
Javier Vives
{"title":"Vibration analysis for fault detection in wind turbines using machine learning techniques","authors":"Javier Vives","doi":"10.1007/s43674-021-00029-1","DOIUrl":"10.1007/s43674-021-00029-1","url":null,"abstract":"<div><p>The implementation of machine learning techniques allows to prevent in advance the degeneration of any component present in a wind turbine, as well as the detection and diagnosis of sudden failures. This methodology allows automatic and autonomous learning to predict, detect and diagnose electrical and mechanical failures in wind turbines. Four different failure states have been simulated due to bearing vibrations in wind turbines, comparing traditional techniques, such as frequency analysis, as well as the implementation of AI, using the KNN and SVM methodology. This contribution evaluates different methodologies for monitoring, supervision and fault diagnosis based on the implementation of machine learning algorithms adapted to the different components and faults of the wind turbine. Implementing these techniques, allows to anticipate a breakdown, reduce downtime and costs, especially if they are offshore.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50468143","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}
引用次数: 5
From linear to non-linear: investigating the effects of right-rail results on complex SERPs 从线性到非线性：研究右轨结果对复杂SERP的影响
Advances in computational intelligence Pub Date : 2022-01-10 DOI: 10.1007/s43674-021-00028-2
Yunqiu Shao, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma
{"title":"From linear to non-linear: investigating the effects of right-rail results on complex SERPs","authors":"Yunqiu Shao,&nbsp;Jiaxin Mao,&nbsp;Yiqun Liu,&nbsp;Min Zhang,&nbsp;Shaoping Ma","doi":"10.1007/s43674-021-00028-2","DOIUrl":"10.1007/s43674-021-00028-2","url":null,"abstract":"<div><p>Modern search engine result pages (SERPs) become increasingly complex with heterogeneous information aggregated from various sources. In many cases, these SERPs also display results in the right rail besides the traditional left-rail result lists, which change the linear result list to a non-linear panel and might influence user search behavior patterns. While user behavior on the traditional ranked result list has been well studied in existing works, it still lacks a thorough investigation of the effects caused by the right-rail results, especially on complex SERPs. To shed light on this research question, we conducted a user study, which collected participants’ eye movements, detailed interaction behavioral logs, and feedback information. Based on the collected data, we analyze the influence of right-rail results on users’ examination patterns, search behavior, perceived workload, and satisfaction. We further construct a user model to predict users’ examination behavior on non-linear SERPs. Our work contributes to understanding the effects of the right-rail results on users’ interaction patterns, benefiting other related research, such as the evaluation and UI optimization of search systems.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50468144","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}
引用次数: 2
Advances in Computational Intelligence: 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, October 24–29, 2022, Proceedings, Part I 计算智能的进展:第21届墨西哥国际人工智能会议，MICAI 2022，蒙特雷，墨西哥，2022年10月24日至29日，会议录，第一部分
Advances in computational intelligence Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-19493-1
{"title":"Advances in Computational Intelligence: 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, October 24–29, 2022, Proceedings, Part I","authors":"","doi":"10.1007/978-3-031-19493-1","DOIUrl":"https://doi.org/10.1007/978-3-031-19493-1","url":null,"abstract":"","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87132071","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}
引用次数: 1
Advances in Computational Intelligence: 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, October 24–29, 2022, Proceedings, Part II 计算智能的进展:第21届墨西哥国际人工智能会议，MICAI 2022，蒙特雷，墨西哥，2022年10月24日至29日，会议录，第二部分
Advances in computational intelligence Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-19496-2
{"title":"Advances in Computational Intelligence: 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, October 24–29, 2022, Proceedings, Part II","authors":"","doi":"10.1007/978-3-031-19496-2","DOIUrl":"https://doi.org/10.1007/978-3-031-19496-2","url":null,"abstract":"","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89961185","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}
引用次数: 0
A support vector approach based on penalty function method 一种基于罚函数法的支持向量方法
Advances in computational intelligence Pub Date : 2021-12-17 DOI: 10.1007/s43674-021-00026-4
Songfeng Zheng
{"title":"A support vector approach based on penalty function method","authors":"Songfeng Zheng","doi":"10.1007/s43674-021-00026-4","DOIUrl":"10.1007/s43674-021-00026-4","url":null,"abstract":"<div><p>Support vector machine (SVM) models are usually trained by solving the dual of a quadratic programming, which is time consuming. Using the idea of penalty function method from optimization theory, this paper combines the objective function and the constraints in the dual, obtaining an unconstrained optimization problem, which could be solved by a generalized Newton method, yielding an approximate solution to the original model. Extensive experiments on pattern classification were conducted, and compared to the quadratic programming-based models, the proposed approach is much more computationally efficient (tens to hundreds of times faster) and yields similar performance in terms of receiver operating characteristic curve. Furthermore, the proposed method and quadratic programming-based models extract almost the same set of support vectors.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43674-021-00026-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50488923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Solutions of Yang Baxter equation of symplectic Jordan superalgebras 辛Jordan超代数的Yang-Baxter方程的解
Advances in computational intelligence Pub Date : 2021-12-17 DOI: 10.1007/s43674-021-00017-5
Amir Baklouti, Warda Bensalah, Khaled Al-Motairi
{"title":"Solutions of Yang Baxter equation of symplectic Jordan superalgebras","authors":"Amir Baklouti,&nbsp;Warda Bensalah,&nbsp;Khaled Al-Motairi","doi":"10.1007/s43674-021-00017-5","DOIUrl":"10.1007/s43674-021-00017-5","url":null,"abstract":"<div><p>We establish in this paper the equivalence between the existence of a solution of the Yang Baxter equation of a Jordan superalgebras and that of symplectic form on Jordan superalgebras.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50488898","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}
引用次数: 0
An eigenvector approach for obtaining scale and orientation invariant classification in convolutional neural networks 卷积神经网络中获得尺度和方向不变分类的特征向量方法
Advances in computational intelligence Pub Date : 2021-12-17 DOI: 10.1007/s43674-021-00023-7
Swetha Velluva Chathoth, Asish Kumar Mishra, Deepak Mishra, Subrahmanyam Gorthi R. K. Sai
{"title":"An eigenvector approach for obtaining scale and orientation invariant classification in convolutional neural networks","authors":"Swetha Velluva Chathoth,&nbsp;Asish Kumar Mishra,&nbsp;Deepak Mishra,&nbsp;Subrahmanyam Gorthi R. K. Sai","doi":"10.1007/s43674-021-00023-7","DOIUrl":"10.1007/s43674-021-00023-7","url":null,"abstract":"<div><p>The convolution neural networks are well known for their efficiency in detecting and classifying objects once adequately trained. Though they address shift in-variance up to a limit, appreciable rotation and scale in-variances are not guaranteed by many of the existing CNN architectures, making them sensitive towards input image or feature map rotation and scale variations. Many attempts have been made in the past to acquire rotation and scale in-variances in CNNs. In this paper, an efficient approach is proposed for incorporating rotation and scale in-variances in CNN-based classifications, based on eigenvectors and eigenvalues of the image covariance matrix. Without demanding any training data augmentation or CNN architectural change, the proposed method, <b>‘Scale and Orientation Corrected Networks (SOCN)’</b>, achieves better rotation and scale-invariant performances. <b>SOCN</b> proposes a scale and orientation correction step for images before baseline CNN training and testing. Being a generalized approach, <b>SOCN</b> can be combined with any baseline CNN to improve its rotational and scale in-variance performances. We demonstrate the proposed approach’s scale and orientation invariant classification ability with several real cases ranging from scale and orientation invariant character recognition to orientation invariant image classification, with different suitable baseline architectures. The proposed approach of <b>SOCN</b>, though is simple, outperforms the current state of the art scale and orientation invariant classifiers comparatively with minimal training and testing time.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43674-021-00023-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50488900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
BCK codes BCK代码
Advances in computational intelligence Pub Date : 2021-12-17 DOI: 10.1007/s43674-021-00018-4
Hashem Bordbar
{"title":"BCK codes","authors":"Hashem Bordbar","doi":"10.1007/s43674-021-00018-4","DOIUrl":"10.1007/s43674-021-00018-4","url":null,"abstract":"<div><p>In this paper, we initiate the study of the notion of the <i>BCK</i>-function on an arbitrary set <i>A</i>, and providing connections with <i>x</i>-functions and <i>x</i>-subsets for <span>(x in X)</span> where <i>X</i> is a <i>BCK</i>-algebra. Moreover, using the notion of order in a <i>BCK</i>-algebra, the <i>BCK</i>-code <i>C</i> is introduced and besides a new structure of order in <i>C</i> is investigated. Finally, we show that the structure of the <i>BCK</i>-algebra <i>X</i> and the <i>BCK</i>-code <i>C</i> which is generated by <i>X</i>, with their related orders are the same.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43674-021-00018-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50488925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Caristi type mappings and characterization of completeness of Archimedean type fuzzy metric spaces Caristi型映射与阿基米德型模糊度量空间完备性的刻画
Advances in computational intelligence Pub Date : 2021-12-17 DOI: 10.1007/s43674-021-00014-8
J. Martínez-Moreno, D. Gopal, Vladimir Rakočević, A. S. Ranadive, R. P. Pant
{"title":"Caristi type mappings and characterization of completeness of Archimedean type fuzzy metric spaces","authors":"J. Martínez-Moreno,&nbsp;D. Gopal,&nbsp;Vladimir Rakočević,&nbsp;A. S. Ranadive,&nbsp;R. P. Pant","doi":"10.1007/s43674-021-00014-8","DOIUrl":"10.1007/s43674-021-00014-8","url":null,"abstract":"<div><p>This paper deals with some issues of fixed point concerning Caristi type mappings introduced by Abbasi and Golshan (Kybernetika 52:929–942, 2016) in fuzzy metric spaces. We enlarge this class of mappings and prove completeness characterization of corresponding fuzzy metric space. The paper includes a comprehensive set of examples showing the generality of our results and an open question.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50488896","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}
引用次数: 1
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