Expert Systems最新文献

{"title":"Zone Oriented Binary Multi-Objective Charged System Search Based Feature Selection Approach for Multi-Label Classification","authors":"Pradip Dhal,&nbsp;Chandrashekhar Azad","doi":"10.1111/exsy.13803","DOIUrl":"https://doi.org/10.1111/exsy.13803","url":null,"abstract":"<div>\u0000 \u0000 <p>Multi-label learning is used in situations when each instance has many labels. Due to the high-dimensional feature space and noise in multi-label datasets, multi-label learning algorithms face substantial problems. Researchers have researched multi-label FS techniques to minimise data dimensionality in multi-label classification (MLC) problems. Global optimization approaches, such as evolutionary algorithm (EA) optimizers, scale well to high-dimensional problems. This paper proposes a hybrid multi-objective FS approach based on the charged system search (CSS) and grey wolf optimization (GWO) methods for the MLC problem. The first objective is to minimise the hamming loss (HLoss) value, and the second objective is to minimise the features from the feature set. A novel concept feature zone based on informative and non-informative features has been added here. Here, we have added the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) approach to the objective function in the FS approach. Here, we have added the new velocity equation for the updated charge particles in the CSS algorithm. The GWO property has been added to the new velocity equation to improve the exploration and exploiting property in the CSS algorithm. For experimental verification, we have utilised six publically accessible multi-label datasets: <i>CAL500</i>, <i>Emotions</i>, <i>Medical</i>, <i>Enron</i>, <i>Scene</i>, and the <i>Yeast</i>. The findings show that the proposed approach gets the best value regarding various performance metrics. The proposed method achieves optimal Jaccard Score (JC) and HLoss values of 0.4408 and 0.0645 for <i>CAL500</i>, 0.8169 and 0.0719 for <i>Emotions</i>, 0.9486 and 0.0019 for <i>Medical</i>, 0.5950 and 0.0205 for <i>Enron</i>, 0.7391 and 0.0495 for <i>Scene</i>, and 0.6452 and 0.0766 for <i>Yeast</i> datasets. In particular, according to empirical data on a popular six-label benchmark multi-label datasets, the proposed method obtains competitive performance when labels are constrained.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: Intelligent Cognitive Evaluation of Ice and Snow Sports Training by Fuzzy Comprehensive Evaluation from the Perspective of Supply Chain Management","authors":"","doi":"10.1111/exsy.13818","DOIUrl":"https://doi.org/10.1111/exsy.13818","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>P. Hu</span> and <span>P. Zhang</span>, “ <span>Intelligent Cognitive Evaluation of Ice and Snow Sports Training by Fuzzy Comprehensive Evaluation from the Perspective of Supply Chain Management</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e13212. https://doi.org/10.1111/exsy.13212.\u0000 </p><p>The above article, published online on 08 December 2022, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found logical inconsistencies between the topic of the article and the conclusions reached in this article. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13818","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: Measuring Systemic and Systematic Risk in the Financial Markets Using Artificial Intelligence","authors":"","doi":"10.1111/exsy.13816","DOIUrl":"https://doi.org/10.1111/exsy.13816","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>M. M. Kamruzzaman</span>, <span>O. Alruwaili</span>, and <span>D. Aldaghmani</span>, “ <span>Measuring Systemic and Systematic Risk in the Financial Markets Using Artificial Intelligence</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e12971. https://doi.org/10.1111/exsy.12971.\u0000 </p><p>The above article, published online on 10 March 2022, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found there was significant unattributed textual overlap between this article and online course documents available on an online learning platform. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13816","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Analysis of Optimized Path Selection for Management Mode of Coastal Regional Circular Economy Based on Fuzzy Decision Algorithm","authors":"","doi":"10.1111/exsy.13817","DOIUrl":"https://doi.org/10.1111/exsy.13817","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>W. Wei</span>, <span>D. Xiao</span>, and <span>W. Liu</span>, “ <span>The Analysis of Optimized Path Selection for Management Mode of Coastal Regional Circular Economy Based on Fuzzy Decision Algorithm</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e12985. https://doi.org/10.1111/exsy.12985.\u0000 </p><p>The above article, published online on 04 March 2022, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found significant flaws and logical inconsistencies in the article. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13817","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Design of Intelligent Fuzzy Cognitive System of Music Emotion by Product Supply Chain Management","authors":"","doi":"10.1111/exsy.13821","DOIUrl":"https://doi.org/10.1111/exsy.13821","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>F. Li</span>, <span>R. Jiang</span>, and <span>J. Li</span>, “ <span>The Design of Intelligent Fuzzy Cognitive System of Music Emotion by Product Supply Chain Management</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e13265. https://doi.org/10.1111/exsy.13265.\u0000 </p><p>The above article, published online on 23 February 2023, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found logical inconsistencies between the topic of the article, the model design, and the conclusions reached in the article. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13821","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Analysis of Green Advertisement Communication Strategy Based on Deep Factorization Machine Deep Learning Model Under Supply Chain Management","authors":"","doi":"10.1111/exsy.13819","DOIUrl":"https://doi.org/10.1111/exsy.13819","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>X. Yu</span>, <span>Y. Zhu</span>, <span>C. Jia</span>, <span>W. Lu</span>, and <span>H. Xu</span>, “ <span>The Analysis of Green Advertisement Communication Strategy Based on Deep Factorization Machine Deep Learning Model Under Supply Chain Management</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e13258. https://doi.org/10.1111/exsy.13258.\u0000 </p><p>The above article, published online on 22 February 2023, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found logical inconsistencies between the topic of the article and the conclusions reached in this article. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13819","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Evaluation of Enterprise Supply Chain Intelligent Manufacturing System for Agricultural Interconnection Data Based on Machine Learning","authors":"","doi":"10.1111/exsy.13820","DOIUrl":"https://doi.org/10.1111/exsy.13820","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>C. Yu</span>, <span>L. Li</span>, <span>J. Li</span>, <span>P. Qin</span>, and <span>B. Zhang</span>, “ <span>The Evaluation of Enterprise Supply Chain Intelligent Manufacturing System for Agricultural Interconnection Data Based on Machine Learning</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e13259. https://doi.org/10.1111/exsy.13259.\u0000 </p><p>The above article, published online on 23 February 2023, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found a number of irrelevant or missing citations included in the published article which leaves some statements insufficiently supported. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Energy Storage and Optimal Dispatch Supply Chain for New Energy Grids Using Edge Computing and the Internet of Things","authors":"","doi":"10.1111/exsy.13822","DOIUrl":"https://doi.org/10.1111/exsy.13822","url":null,"abstract":"<p>\u0000 \u0000 <b>Retraction:</b> <span>J. Liu</span>, “ <span>The Energy Storage and Optimal Dispatch Supply Chain for New Energy Grids Using Edge Computing and the Internet of Things</span>,” <i>Expert Systems</i> <span>41</span>, no. <span>5</span> (<span>2024</span>): e13266. https://doi.org/10.1111/exsy.13266.\u0000 </p><p>The above article, published online on 01 March 2023, in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, David Camacho; and John Wiley &amp; Sons Ltd. Following an investigation by the publisher, the parties have concluded that this article was accepted solely on the basis of a compromised peer review process. In addition, the investigation found there was significant unattributed overlap between this article and a previously-published article (Dunnan et al. 2021 [https://doi.org/10.1088/1755-1315/687/1/012140]), including the re-use of the charts between Figure 5 in this article and Figures 2 and 3 in the previously-published article. Therefore, the article must be retracted. The authors did not respond to the notice regarding the retraction.</p>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.13822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Semantic Natural Scenery Retrieval System Through Novel Dominant Colour and Multi-Resolution Texture Feature Learning Model","authors":"L. K. Pavithra,&nbsp;P. Subbulakshmi,&nbsp;Nirmala Paramanandham,&nbsp;S. Vimal,&nbsp;Norah Saleh Alghamdi,&nbsp;Gaurav Dhiman","doi":"10.1111/exsy.13805","DOIUrl":"https://doi.org/10.1111/exsy.13805","url":null,"abstract":"<div>\u0000 \u0000 <p>A conventional content-based image retrieval system (CBIR) extracts image features from every pixel of the images, and its depiction of the feature is entirely different from human perception. Additionally, it takes a significant amount of time for retrieval. An optimal combination of appropriate image features is necessary to bridge the semantic gap between user queries and retrieval responses. Furthermore, users should require minimal interactions with the CBIR system to obtain accurate responses. Therefore, the proposed work focuses on extracting highly relevant feature information from a set of images in various natural image databases. Subsequently, a feature-based learning/classification model is introduced before similarity measure calculations, aiming to minimise retrieval time and the number of comparisons. The proposed work analyses the learning models based on the retrieval system's performance separately for the following features: (i) dominant colour, (ii) multi-resolution radial difference texture patterns, and a combination of both. The developed work is assessed with other techniques, and the results are reported. The results demonstrate that the implemented ensemble learning model-based CBIR outperforms the recent CBIR techniques.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PC-Based User Continuous Authentication in the Artificial Intelligence Method and System Using the User's Finger Stroke Characteristics","authors":"Heewoong Lee,&nbsp;Deok Gyu Lee,&nbsp;Kihyo Nam,&nbsp;Mun-Kweon Jeong","doi":"10.1111/exsy.13806","DOIUrl":"https://doi.org/10.1111/exsy.13806","url":null,"abstract":"<div>\u0000 \u0000 <p>Biometric technology, which performs continuous authentication based on user behaviour, has been developed in various ways depending on the type of device, input device, and sensor. Research on continuous authentication technology in PC-based systems with few sensors installed is based on data from physical devices that extract and analyse features from keyboard and mouse input patterns. Among these, previous studies on continuous authentication through keyboard input performed continuous authentication using the key hold delay time that occurs when one key is pressed, the key interval delay time that occurs due to the interaction between fingers, and the key press delay time. However, the keyboard-based continuous authentication model has limitations in increasing accuracy due to a small number of features. Therefore, in this paper, when a user inputs a sentence using a QWERTY keyboard in a PC system, the function is subdivided by reflecting the characteristics of each finger and used for continuous authentication. The features extracted by reflecting the characteristics of the finger were subdivided into a total of 151 latencies, and Support Vector Data Description (SVDD), decision tree and CNN were used as continuous authentication models. Experimental data was collected through the user's input of randomly displayed sentences, and features were created based on this. User keystroke behaviour was used to validate the continuous authentication in the artificial intelligence model. Validation metrics included thresholds for classification accuracy (ACC), ROC curves, false rejection rate (FRR), equal error rate (EER), and false acceptance rate (FAR). As a result of the experiment, it was found that continuous authentication including the user's finger input pattern was superior to the existing method.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"42 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}