{"title":"RETRACTION","authors":"","doi":"10.1111/coin.70068","DOIUrl":"https://doi.org/10.1111/coin.70068","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>P. Sathishkumar</span>, <span>M. Gunasekaran</span>, “ <span>An Improved Vertical Fragmentation, Allocation and Replication for Enhancing E-Learning in Distributed Database Environment</span>,” <i>Computational Intelligence</i> <span>37</span> no. <span>1</span> (<span>2021</span>): <span>253</span>–<span>272</span>, \u0000https://doi.org/10.1111/coin.12401.</p><p>The above article, published online on 31 August 2020 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191012","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","authors":"","doi":"10.1111/coin.70067","DOIUrl":"https://doi.org/10.1111/coin.70067","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>S.G.R. Chinnaraj</span>, <span>R. Kuppan</span>, “ <span>Optimal Sizing and Placement of Multiple Renewable Distribution Generation and DSTATCOM in Radial Distribution Systems Using Hybrid Lightning Search Algorithm-Simplex Method Optimization Algorithm</span>,” <i>Computational Intelligence</i> <span>37</span> no. <span>4</span> (<span>2021</span>): <span>1673</span>–<span>1690</span>, \u0000https://doi.org/10.1111/coin.12402.</p><p>The above article, published online on 23 September 2020 in Wiley Online Library (\u0000wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191011","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","authors":"","doi":"10.1111/coin.70065","DOIUrl":"https://doi.org/10.1111/coin.70065","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>M.A. Khan</span>, <span>K.A. Abuhasel</span>, “ <span>Advanced Metameric Dimension Framework for Heterogeneous Industrial Internet of Things</span>,” <i>Computational Intelligence</i> <span>37</span> no. <span>3</span> (<span>2021</span>): <span>1367</span>–<span>1387</span>, \u0000https://doi.org/10.1111/coin.12378.</p><p>The above article, published online on 13 July 2020 in Wiley Online Library (\u0000wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors disagree with the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191161","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","authors":"","doi":"10.1111/coin.70064","DOIUrl":"https://doi.org/10.1111/coin.70064","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>A. Ancy Mergin</span>, <span>M.S. Godwin Premi</span>, “ <span>Implementation Analysis of Pixel-Level Image Processing Based on Multiscale Transforms</span>,” <i>Computational Intelligence</i> <span>37</span> <span>no. 3</span> (<span>2021</span>): <span>1415</span>–<span>1427</span>, \u0000https://doi.org/10.1111/coin.12384.</p><p>The above article, published online on 03 August 2020 in Wiley Online Library (\u0000wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191013","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","authors":"","doi":"10.1111/coin.70066","DOIUrl":"https://doi.org/10.1111/coin.70066","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>K. A. Abuhasel</span>, <span>M. Khadr</span>, <span>M.M. Alquraish</span>, “ <span>Analyzing and Forecasting COVID-19 Pandemic in the Kingdom of Saudi Arabia using ARIMA and SIR Models</span>,” <i>Computational Intelligence</i> <span>38</span> no. <span>3</span> (<span>2022</span>): <span>770</span>–<span>783</span>, \u0000https://doi.org/10.1111/coin.12407.</p><p>The above article, published online on 05 October 2020 in Wiley Online Library (\u0000wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors disagree with the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191162","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","authors":"","doi":"10.1111/coin.70070","DOIUrl":"https://doi.org/10.1111/coin.70070","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>R. Mathi</span>, <span>S. Jayalalitha</span>, “ <span>Influence of Renewable Energy Sources on the Scheduling on Thermal Power Stations and its Optimization for <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>CO</mtext>\u0000 <mn>2</mn>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {mathrm{CO}}_2 $$</annotation>\u0000 </semantics></math> Reduction</span>,” <i>Computational Intelligence</i> <span>38</span> no. <span>3</span> (<span>2022</span>): <span>903</span>–<span>920</span>, https://doi.org/10.1111/coin.12477.</p><p>The above article, published online on 10 October 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191010","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","authors":"","doi":"10.1111/coin.70069","DOIUrl":"https://doi.org/10.1111/coin.70069","url":null,"abstract":"<p>\u0000 <b>RETRACTION</b>: <span>C. Wang</span>, <span>Y. Dong</span>, <span>Y. Xia</span>, <span>G. Li</span>, <span>O. Sanjuan Martinez</span>, <span>R. Gonzalez Crespo</span>, “ <span>Management and Entrepreneurship Management Mechanism of College Students Based on Support Vector Machine Algorithm</span>,” <i>Computational Intelligence</i> <span>38</span> no. <span>3</span> (<span>2022</span>): <span>842</span>–<span>854</span>, \u0000https://doi.org/10.1111/coin.12430.</p><p>The above article, published online on 25 December 2020 in Wiley Online Library (\u0000wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144191009","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":"CCNet: A Cross-Channel Enhanced CNN for Blind Image Denoising","authors":"Minling Zhu, Zhixin Xu","doi":"10.1111/coin.70063","DOIUrl":"https://doi.org/10.1111/coin.70063","url":null,"abstract":"<div>\u0000 \u0000 <p>Nowadays, blind image denoising with deep convolutional neural network (CNN) is one of the research hotspots in the field of image denoising. Relying on the convolutional operation and respective field, CNN is excellent in processing local information. However, this also brings the problems of lack of cross-domain interaction and process of global feature information. We incorporate it with transformer's self-attention mechanism and propose a cross-channel enhanced CNN, namely CCNet, for image denoising. CCNet consists of three parts: the backbone encoder (BE), the cross-channel enhancer (CCE), and the backbone decoder (BD). The BE and BD are constructed using the multiscale symmetric network U-Net and use the residual connection block (RCB) as the basic block for image feature extraction and reconstruction. CCE introduces transposed attention, serving as a complement of BE for cross-channel modeling. Meanwhile, we propose a unique gated fusion block (GFB) to fuse the information of these two modules and further feature learning. To improve training, we use random cropping, shuffling, and mixed noise strategies to expand the noise distribution learned by the model, increasing its noise adaptability. Extensive experiments on grayscale images, color images, and real noisy images demonstrate CCNet's strong performance in these tasks.</p>\u0000 </div>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171713","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":"FNN-ONTOCOM: A Hybrid Cost Estimation Approach Using Fuzzy and Neural Network for Ontology Engineering","authors":"Sonika Malik, Sarika Jain, Geetanjali Sharma","doi":"10.1111/coin.70061","DOIUrl":"https://doi.org/10.1111/coin.70061","url":null,"abstract":"<div>\u0000 <p>Ontology engineering is crucial for many areas such as information retrieval systems, data integration facilities, and basic decision support systems. Nevertheless, estimating the cost of ontology engineering projects is notoriously difficult to achieve. This challenge stems from the complexity and evolving nature of such projects. To solve this difficulty, we propose to improve the accuracy of cost estimation through a hybrid methodology that combines Fuzzy Ontology Cost Estimation Model (F-ONTOCOM) and Artificial Neural Networks (ANN). Fuzzy logic is used in our model to capture linguistic variables and other complex relationships within the scope of cost estimation. At the same time, ANN allows for the recognition of complex nonlinear interactions, enhancing the overall accuracy of prediction. This integration of fuzzy logic and neural networks leads to enhancements in the model's robustness, adaptability, and precision. Our approach features a methodology for 148 ontology engineering projects that include, but are not limited to, data scraping and preprocessing, fuzzy inference system design, neural network training, and validation processes. The results showed that the hybrid approach was champion over the traditional estimation approach in terms of effort estimation, Mean Relative Error (MRE), Mean Magnitude of Relative Error (MMRE), and the predictive accuracy over 21 randomly selected ontology projects.</p>\u0000 </div>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140790","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":"Two-Tier Enhanced Hybrid Deep Learning-Based Collaborative Filtering Recommendation System for Online Reviews","authors":"Harsh Khatter, Pooja Singh, Anil Ahlawat, Ajay Kumar Shrivastava","doi":"10.1111/coin.70062","DOIUrl":"https://doi.org/10.1111/coin.70062","url":null,"abstract":"<div>\u0000 \u0000 <p>Collaborative filtering-based recommender systems have recently attracted audiences due to the precise prediction of user interests and provide recommendations accordingly. The user-specific interests are the main requirement to build any recommendation model that produces the desired recommendation list. But the users' interests are sometimes unpredictable due to the fluctuating nature of the arrival of newer products. To resolve this problem and achieve better recommendation outcomes, a two-tier enhanced hybrid collaborative filtering based recommendation system (EHCFR) is constructed in this work based on deep learning. Initially, users in the dataset are segmented based on their age stratification to obtain users' interests based on age. Then, the major features are extracted from the dataset using the word learning enhanced variational auto-encoder (EVAE). These features are provided along with the rating matrix as the input to the deep belief network (DBN) for rating prediction. Based on the predicted ratings, the top N1 recommendation list is generated. Then, a time window strategy is adapted in the model to determine the dynamic fluctuations of user interests. Another list called the top N2 recommendation list is generated based on these fluctuations. Finally, both these lists are concatenated to provide accurate and favorable recommendations to the users. The proposed model is tested on the user dataset and provides competitive performance against the existing state-of-the-art techniques. Also, a reliable comparison is made with the existing popular datasets, such as Movielens 100k and Jester, and the results prove the efficacy of the proposed method.</p>\u0000 </div>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"41 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144148626","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}
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