Appl. Comput. Intell. Soft Comput.最新文献_第10页

Locality sensitive hashing-driven multifactorial evolutionary algorithms for multitask optimization 多任务优化的局部敏感哈希驱动多因子进化算法

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4123154

Tuo-Bin Yu, Yu-Hui Zhang, Yue-jiao Gong, Yuan Li

引用次数: 0

Time-Leveled Hypersoft Matrix, Level Cuts, Operators, and COVID-19 Collective Patient Health State Ranking Model 时间级超软矩阵、级别切割、操作符和COVID-19集体患者健康状态排序模型

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.1155/2022/2388284

Shazia Rana, M. Saeed, Badria Almaz Ali Yousif, F. Smarandache, H. A. Khalifa

{"title":"Time-Leveled Hypersoft Matrix, Level Cuts, Operators, and COVID-19 Collective Patient Health State Ranking Model","authors":"Shazia Rana, M. Saeed, Badria Almaz Ali Yousif, F. Smarandache, H. A. Khalifa","doi":"10.1155/2022/2388284","DOIUrl":"https://doi.org/10.1155/2022/2388284","url":null,"abstract":"This article is the first step to formulate such higher dimensional mathematical structures in the extended fuzzy set theory that includes time as a fundamental source of variation. To deal with such higher dimensional information, some modern data processing structures had to be built. Classical matrices (connecting equations and variables through rows and columns) are a limited approach to organizing higher dimensional data, composed of scattered information in numerous forms and vague appearances that differ on time levels. To extend the approach of organizing and classifying the higher dimensional information in terms of specific time levels, this unique plithogenic crisp time-leveled hypersoft-matrix (PCTLHS matrix) model is introduced. This hypersoft matrix has multiple parallel layers that describe parallel universes/realities/information on some specific time levels as a combined view of events. Furthermore, a specific kind of view of the matrix is described as a top view. According to this view, i-level cuts, sublevel cuts, and sub-sublevel cuts are introduced. These level cuts sort the clusters of information initially, subject-wise then attribute-wise, and finally time-wise. These level cuts are such matrix layers that focus on one required piece of information while allowing the variation of others, which is like viewing higher dimensional images in lower dimensions as a single layer of the PCTLHS matrix. In addition, some local aggregation operators are designed to unify i-level cuts. These local operators serve the purpose of unifying the material bodies of the universe. This means that all elements of the universe are fused and represented as a single body of matter, reflecting multiple attributes on different time planes. This is how the concept of a unified global matter (something like dark matter) is visualized. Finally, to describe the model in detail, a numerical example is constructed to organize and classify the states of patients with COVID-19.","PeriodicalId":8218,"journal":{"name":"Appl. Comput. Intell. Soft Comput.","volume":"19 1","pages":"2388284:1-2388284:14"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89268493","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 personalized classification model using similarity learning via supervised autoencoder 基于监督式自编码器的相似性学习个性化分类模型

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4117247

H. Jo, C. Jun

引用次数: 1

Variable neighborhood search for the discounted {0-1} knapsack problem 折现{0-1}背包问题的变邻域搜索

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4062902

C. Wilbaut, R. Todosijević, S. Hanafi, A. Fréville

引用次数: 0

Multi-objective scheduling of a single mobile robot based on the grey wolf optimization algorithm 基于灰狼优化算法的单移动机器人多目标调度

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4058009

Milica Petrović, Aleksandar Jokic, Z. Miljković, Z. Kulesza

引用次数: 7

Optimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting 基于PSO-CS方法的农产品期货日价最优预测组合

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4089138

Liling Zeng, Liwen Ling, Dabin Zhang, Wentao Jiang

引用次数: 5

Compressing convolutional neural networks with hierarchical Tucker-2 decomposition 基于分层Tucker-2分解的卷积神经网络压缩

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-11-01 DOI: 10.2139/ssrn.4031519

M. Gábor, R. Zdunek

引用次数: 5

Cognitive Wireless Networks Based Spectrum Sensing Strategies: A Comparative Analysis 基于认知无线网络的频谱感知策略比较分析

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-10-30 DOI: 10.1155/2022/6988847

A. Haldorai, Jeevanandham Sivaraj, M. Nagabushanam, M. Roberts

{"title":"Cognitive Wireless Networks Based Spectrum Sensing Strategies: A Comparative Analysis","authors":"A. Haldorai, Jeevanandham Sivaraj, M. Nagabushanam, M. Roberts","doi":"10.1155/2022/6988847","DOIUrl":"https://doi.org/10.1155/2022/6988847","url":null,"abstract":"Because of numerous dormant application fields, wireless sensor networks (WSNs) have emerged as an important and novel area in radio and mobile computing research. These applications range from enclosed system configurations in the home and office to alfresco enlistment in an opponent’s landmass in a strategic flashpoint. Cognitive radio networks (CRNs) can be created by integrating radio link capabilities with network layer operations utilizing cognitive radios. The goal of CRN design is to optimize the general system operations to meet customer requirements at any location worldwide by much more efficiently addressing CRNs instead of simply connecting spectrum utilization. When compared to conventional radio networks, CRNs are more versatile and susceptible to wireless connections. Recent advancements in wireless communication have resulted in increasing spectrum scarcity. As a modern innovation, cognitive radio aims to tackle this challenge by proactively utilizing the spectrum. Because cognitive radio (CR) technology gives assailants additional possibilities than a normal wireless network, privacy in a CRN becomes a difficult challenge. We concentrate on examining the surveillance system at a societal level, in which both defense and monitoring are critical components in assuring the channel’s privacy. The current state of investigation into spectrum sensing and potential risks in cognitive radios is reviewed in this study.","PeriodicalId":8218,"journal":{"name":"Appl. Comput. Intell. Soft Comput.","volume":"78 1","pages":"6988847:1-6988847:14"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83636647","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

Prime ℒ-ideal spaces in hoop algebras 环代数中的质数-理想空间

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-10-25 DOI: 10.1007/s00500-022-07599-3

M. Bakhshi

引用次数: 0

Predictive Model for Diagnosis of Gestational Diabetes in the Kurdistan Region by a Combination of Clustering and Classification Algorithms: An Ensemble Approach 基于聚类和分类算法的库尔德斯坦地区妊娠期糖尿病诊断预测模型:一种集成方法

Appl. Comput. Intell. Soft Comput. Pub Date : 2022-10-22 DOI: 10.1155/2022/9749579

Rasool F. Jader, S. Aminifar

{"title":"Predictive Model for Diagnosis of Gestational Diabetes in the Kurdistan Region by a Combination of Clustering and Classification Algorithms: An Ensemble Approach","authors":"Rasool F. Jader, S. Aminifar","doi":"10.1155/2022/9749579","DOIUrl":"https://doi.org/10.1155/2022/9749579","url":null,"abstract":"Gestational diabetes is a type of high blood sugar that develops during pregnancy. It can occur at any stage of pregnancy and cause problems for both the mother and the baby, during and after birth. The risks can be reduced if they are early detected and managed, especially in areas where only periodic tests of pregnant women are available. Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. This study proposes a combined prediction model to diagnose gestational diabetes. The dataset was obtained from the Kurdistan region laboratories, which collected information from pregnant women with and without diabetes. The suggested model uses the clustering KMeans technique for data reduction and the elbow method to find the optimal k value and the Mahalanobis distance method to find more related cluster to new samples, and the classification methods such as decision tree, random forest, SVM, KNN, logistic regression, and Naïve Bayes are used for prediction. The results showed that using a mix of KMeans clustering, elbow method, Mahalanobis distance, and ensemble technique significantly improves prediction accuracy.","PeriodicalId":8218,"journal":{"name":"Appl. Comput. Intell. Soft Comput.","volume":"20 1","pages":"9749579:1-9749579:11"},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75907365","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: 6