Cybernetics and Systems最新文献

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Fractional-Ant Lion Optimization Algorithm for Privacy Protection in Cloud with MapReduce Framework 基于MapReduce框架的云隐私保护分数蚂蚁优化算法
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-20 DOI: 10.1080/01969722.2023.2166263
S. Nagendra Prabhu, P. Kalpana, D. B. Jagannadha Rao, Vijayakumar Polepally
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引用次数: 0
Hybrid Optimization-Based Multi-Path Routing for Dynamic Cluster-Based MANET 基于混合优化的动态集群MANET多路径路由
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-20 DOI: 10.1080/01969722.2023.2166249
Rajaram A., B. A
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引用次数: 4
A Secure Machine Learning-Based Optimal Routing in Ad Hoc Networks for Classifying and Predicting Vulnerabilities 基于机器学习的Ad Hoc网络安全最优路由分类与漏洞预测
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-20 DOI: 10.1080/01969722.2023.2166241
Ajay Reddy Yeruva, Esraa Saleh Alomari, S. Rashmi, Anurag Shrivastava, M. Kathiravan, A. Chaturvedi
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引用次数: 16
Optimal Strategy Selection under Fuzzy Environment for Strategic Planning Methodology Selection: A SWOT Approach 模糊环境下战略规划方法选择的最优战略选择:SWOT方法
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-19 DOI: 10.1080/01969722.2023.2166255
Mansour Abedian, Maryam Hejazi
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引用次数: 1
A Centralization Measure for Social Networks Assessment 一种社会网络评价的集中化方法
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-18 DOI: 10.1080/01969722.2022.2162737
Rafał Palak, Krystian Wojtkiewicz
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引用次数: 0
Mining Association Rules from a Single Large Graph 从单个大型图中挖掘关联规则
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-18 DOI: 10.1080/01969722.2022.2162740
Bao Huynh, Lam B. Q. Nguyen, D. Nguyen, N. Nguyen, H. Nguyen, Tuyn Pham, Tri Pham, Loan T. T. Nguyen, Trinh D. D. Nguyen, Bay Vo
{"title":"Mining Association Rules from a Single Large Graph","authors":"Bao Huynh, Lam B. Q. Nguyen, D. Nguyen, N. Nguyen, H. Nguyen, Tuyn Pham, Tri Pham, Loan T. T. Nguyen, Trinh D. D. Nguyen, Bay Vo","doi":"10.1080/01969722.2022.2162740","DOIUrl":"https://doi.org/10.1080/01969722.2022.2162740","url":null,"abstract":"","PeriodicalId":55188,"journal":{"name":"Cybernetics and Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42061854","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}
引用次数: 0
Innovative Soft-Computing Solutions for Industrial and Environmental Problems 针对工业和环境问题的创新软计算解决方案
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-18 DOI: 10.1080/01969722.2023.2167336
Álvaro Herrero, Carlos Cambra, Secil Bayraktar, A. Jiménez, E. Corchado
{"title":"Innovative Soft-Computing Solutions for Industrial and Environmental Problems","authors":"Álvaro Herrero, Carlos Cambra, Secil Bayraktar, A. Jiménez, E. Corchado","doi":"10.1080/01969722.2023.2167336","DOIUrl":"https://doi.org/10.1080/01969722.2023.2167336","url":null,"abstract":"Novel solutions, based on soft-computing techniques, are proposed in the present issue. All of them target open problems in the environmental and industrial domains. Thanks to the intelligent systems that are presented, the addressed problems are solved in innovative ways, advancing the present solutions. Deep learning is proposed in the first paper for predicting energy consumption in the residential domain. The target is explaining the impact of the input attributes on the prediction by taking into account the long-term and short-term properties of the time-series forecasting. The model consists of several components: two encoders represent the power information for prediction and explanation, a decoder predicts the power demand from the concatenated outputs of encoders, and an explainer identifies the most significant attributes for predicting the energy consumption. Several experiments on a benchmark dataset of household electric energy demand show that the proposed method explains the prediction appropriately with the most influential input attributes in the long-term and short-term dependencies. There is a trade off between the gain of the time-series explanation of the result and the prediction performance (slightly degraded). The second contribution also addresses a challenge in the energy field, as a thermal solar generation system is studied. The performance of four clustering techniques, with the objective of achieving strong hybrid models in supervised learning tasks, are compared. A real dataset is studied to validate several cluster methods when subsequently applying a regression technique to predict the output temperature of the system. With the objective of defining the quality of each clustering method, two approaches have been followed. The first one is based on three unsupervised learning metrics (Silhouette, Calinski-Harabasz and Davies-Bouldin) while the second one employs the most common error measurements for a regression algorithm (the MultiLayer Perceptron). Basurto et al. predict, by Supervised Machine Learning, the success of Private Participation Projects in the Telecom sector. Widely acknowledged classifiers (k Nearest Neighbors, Support Vector Machines, and Random Forest) are applied to an open dataset from the World Bank. The results on this highly imbalanced dataset are greatly improved by the application of data balancing techniques. It includes some standard ones (Random Oversampling, Random Undersampling, and SMOTE), together with some other advanced ones (Density-Based SMOTE and Borderline SMOTE). The satisfactory results validate the proposed application of classifiers on the dataset improved by data-balancing techniques. Supply chain network design (SCND) is the process for designing and modeling the supply chain, trying to minimize the costs generated by the location of facilities and the flow of product between the selected facilities. The aim of the fourth contribution is to investigate a particular SCND, ","PeriodicalId":55188,"journal":{"name":"Cybernetics and Systems","volume":"54 1","pages":"267 - 269"},"PeriodicalIF":1.7,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47192789","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}
引用次数: 0
An Automated Detection of DDoS Attack in Cloud Using Optimized Weighted Fused Features and Hybrid DBN-GRU Architecture 基于优化加权融合特征和混合DBN-GRU架构的云DDoS攻击自动检测
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-16 DOI: 10.1080/01969722.2022.2157603
Ahamed Ali Samsu Aliar, Moorthy Agoramoorthy, J. Y
{"title":"An Automated Detection of DDoS Attack in Cloud Using Optimized Weighted Fused Features and Hybrid DBN-GRU Architecture","authors":"Ahamed Ali Samsu Aliar, Moorthy Agoramoorthy, J. Y","doi":"10.1080/01969722.2022.2157603","DOIUrl":"https://doi.org/10.1080/01969722.2022.2157603","url":null,"abstract":"","PeriodicalId":55188,"journal":{"name":"Cybernetics and Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43325565","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}
引用次数: 0
Pomegranate Leaf Disease Detection Using Supervised and Unsupervised Algorithm Techniques 有监督和无监督算法在石榴叶病检测中的应用
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-13 DOI: 10.1080/01969722.2023.2166192
M. Nirmal, Pramod P. Jadhav, Santoshi A. Pawar
{"title":"Pomegranate Leaf Disease Detection Using Supervised and Unsupervised Algorithm Techniques","authors":"M. Nirmal, Pramod P. Jadhav, Santoshi A. Pawar","doi":"10.1080/01969722.2023.2166192","DOIUrl":"https://doi.org/10.1080/01969722.2023.2166192","url":null,"abstract":"","PeriodicalId":55188,"journal":{"name":"Cybernetics and Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42507554","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}
引用次数: 1
Intelligent Collectives: Impact of Independence on Collective Performance 智能集体:独立性对集体绩效的影响
IF 1.7 4区 计算机科学
Cybernetics and Systems Pub Date : 2023-01-13 DOI: 10.1080/01969722.2022.2162735
Van Du Nguyen, Hai Bang Truong
{"title":"Intelligent Collectives: Impact of Independence on Collective Performance","authors":"Van Du Nguyen, Hai Bang Truong","doi":"10.1080/01969722.2022.2162735","DOIUrl":"https://doi.org/10.1080/01969722.2022.2162735","url":null,"abstract":"","PeriodicalId":55188,"journal":{"name":"Cybernetics and Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48693623","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}
引用次数: 0
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