Concurrency and Computation-Practice & Experience最新文献_第8页

Non-orthogonal multiple access-based task processing and energy optimization in vehicular edge computing networks 车载边缘计算网络中基于非正交多址的任务处理和能量优化

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-10 DOI: 10.1002/cpe.8222

Lei Shi, Zepeng Li, Shuangliang Zhao, Yuqi Fan, Dingjun Qian

{"title":"Non-orthogonal multiple access-based task processing and energy optimization in vehicular edge computing networks","authors":"Lei Shi, Zepeng Li, Shuangliang Zhao, Yuqi Fan, Dingjun Qian","doi":"10.1002/cpe.8222","DOIUrl":"10.1002/cpe.8222","url":null,"abstract":"<div>\u0000 \u0000 <p>Vehicular edge computing (VEC) is envisioned as a promising approach to process explosive vehicle tasks, where vehicles can choose to upload tasks to nearby edge nodes for processing. However, since the communication between vehicles and edge nodes is via wireless network, which means the channel condition is complex. Moreover, in reality, the arrival time of each vehicle task is stochastic, so efficient communication methods should be designed for VEC. As one of the key communication technologies in 5G, non-orthogonal multiple access (NOMA) can effectively increase the number of simultaneous transmission tasks and enhance transmission performance. In this article, we design a NOMA-based task allocation scheme to improve the VEC system. We first establish the mathematical model and divide the allocation of tasks into two processes: the transmission process and the computation process. In the transmission process, we adopt the NOMA technique to upload the tasks in batches. In the computation process, we use a high response-ratio strategy to determine the computation order. Then we define the optimization objective as maximizing task completion rate and minimizing task energy consumption, which is an integer nonlinear problem with lots of integer variables and cannot be solved directly. Through further analysis, we design a heuristics algorithm which we name as the AECO (average energy consumption optimization) algorithm. By using the AECO, we obtain the optimal allocation strategy by constantly adjusting the optimal variables. Simulation results demonstrate that our algorithm has a significant number of advantages.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587809","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

A noise-tolerant fuzzy-type zeroing neural network for robust synchronization of chaotic systems 用于混沌系统稳健同步的容噪模糊型归零神经网络

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-09 DOI: 10.1002/cpe.8218

Xin Liu, Lv Zhao, Jie Jin

{"title":"A noise-tolerant fuzzy-type zeroing neural network for robust synchronization of chaotic systems","authors":"Xin Liu, Lv Zhao, Jie Jin","doi":"10.1002/cpe.8218","DOIUrl":"10.1002/cpe.8218","url":null,"abstract":"<div>\u0000 \u0000 <p>As a significant research issue in control and science field, chaos synchronization has attracted wide attention in recent years. However, it is difficult for traditional control methods to realize synchronization in predefined time and resist external interference effectively. Inspired by the excellent performance of zeroing neural network (ZNN) and the wide application of fuzzy logic system (FLS), a noise-tolerant fuzzy-type zeroing neural network (NTFTZNN) with fuzzy time-varying convergent parameter is proposed for the synchronization of chaotic systems in this paper. Notably the fuzzy parameter generated from FLS combined with traditional convergent parameter embedded into this NTFTZNN can adjust the convergence rate according to the synchronization errors. For the sake of emphasizing the advantages of NTFTZNN model, other three sets of contrast models (FTZNN, VPZNN, and PTZNN) are constructed for the purpose of comparison. Besides, the predefined-time convergence and noise-tolerant ability of NTFTZNN model are distinctly demonstrated by detailed theoretical analysis. Furthermore, synchronization simulation experiments including two chaotic systems with different dimensions are provided to verify the related mathematical theories. Finally, the schematic of NTFTZNN model for chaos synchronization is accomplished completely through Simulink, further accentuating its effectiveness and potentials in practical applications.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576357","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

Enhancing healthcare security: Time-based authentication for privacy-preserving IoMT sensor monitoring framework leveraging blockchain technology 加强医疗安全：利用区块链技术为保护隐私的 IoMT 传感器监控框架提供基于时间的身份验证

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-09 DOI: 10.1002/cpe.8213

Aashima Sharma, Sanmeet Kaur, Maninder Singh

{"title":"Enhancing healthcare security: Time-based authentication for privacy-preserving IoMT sensor monitoring framework leveraging blockchain technology","authors":"Aashima Sharma, Sanmeet Kaur, Maninder Singh","doi":"10.1002/cpe.8213","DOIUrl":"10.1002/cpe.8213","url":null,"abstract":"<div>\u0000 \u0000 <p>The rapid progression of the Internet of Things and its increasing use in healthcare has generated considerable concerns over the safeguarding and privacy of vital medical data. In response to these issues, blockchain has surfaced as a possible remedy, offering transparent, immutable, and decentralized storage. Nevertheless, conventional blockchain-based systems still encounter constraints in maintaining anonymity, confidentiality, and privacy. Hence, this article suggests a framework based on a secure consortium blockchain that prioritizes data privacy and employs time-based authentication to streamline patient data monitoring. First, we employ time-based authentication to verify the identities of authorized users. This process utilizes the NIK-512 hashing algorithm in conjunction with passwords and registered timestamps, which strengthens the confidentiality of data. Patient information undergoes encryption before transmission within the network. Further, our framework introduces a sensor registration service that the trusted node employs to assign a distinct identity to each sensor connected to a patient. The implementation of data processing and filtering techniques at the edge layer serves the purpose of mitigating disturbances that may occur during the collection of sensor-based data. Finally, a comprehensive evaluation of performance and security has been carried out with various metrics. The findings indicate that the proposed solution effectively enhances the management of Internet of Medical Things data by providing improved privacy and security.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576360","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

Multi-objective GA to schedule task graphs on heterogeneous voltage frequency islands 在异构电压频率孤岛上调度任务图的多目标 GA

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-09 DOI: 10.1002/cpe.8217

Sanchit, Navjot Singh, Jagpreet Singh

{"title":"Multi-objective GA to schedule task graphs on heterogeneous voltage frequency islands","authors":"Sanchit, Navjot Singh, Jagpreet Singh","doi":"10.1002/cpe.8217","DOIUrl":"10.1002/cpe.8217","url":null,"abstract":"<div>\u0000 \u0000 <p>Energy consumption of multiprocessor's system is increasing day by day. The capability of multiprocessor systems and high compute-intensive tasks play a major role in increasing energy consumption. Voltage frequency island (VFI) architecture partitioned the cores into groups for which voltage/frequency can be controlled by a single switch. VFI plays a major role in optimizing the energy consumption. We have generated the initial population by using the slot technique to VFI architecture. The genetic algorithm studied by many researchers to solve scheduling problems. So we combined the genetic algorithm with the VFI-enabled architecture and slot approach called VFIGen. Then apply the VFIGen algorithm to optimize the energy consumption. When comparing the results of the proposed one with the existing state-of-art we achieved the performance gain by <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>28</mn>\u0000 <mo>%</mo>\u0000 </mrow>\u0000 <annotation>$$ 28% $$</annotation>\u0000 </semantics></math> to <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>39</mn>\u0000 <mo>%</mo>\u0000 </mrow>\u0000 <annotation>$$ 39% $$</annotation>\u0000 </semantics></math>.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141665611","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

Interval many-objective dynamic charging planning in wireless rechargeable sensor networks 无线充电传感器网络中的间隔多目标动态充电规划

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-08 DOI: 10.1002/cpe.8150

Yu Zhang, Tianhao Zhao, Linjie Wu, Zhihua Cui

{"title":"Interval many-objective dynamic charging planning in wireless rechargeable sensor networks","authors":"Yu Zhang, Tianhao Zhao, Linjie Wu, Zhihua Cui","doi":"10.1002/cpe.8150","DOIUrl":"10.1002/cpe.8150","url":null,"abstract":"<div>\u0000 \u0000 <p>Charging path planning in wireless sensor networks (WSNs) refers to designing an efficient charging path for sensor nodes in the network. However, most charging schemes mainly consider the planning of charging paths and pay little attention to the impact of uncertainties, such as road conditions and environment on the planning of charging paths, as well as ignoring the charging problem of new nodes in need of charging. Road conditions and the environment directly affect the energy consumption of wireless charging vehicles (WCVs) during traveling. To address the aforementioned challenges, this article proposes an interval many-objective charging path scheme model, the WCV consumption is an uncertain value, it will change according to the environment, and road conditions, so we represent it as an interval parameter with upper and lower bounds. An interval high-dimensional multi-objective model with target energy consumption, path distance, number of dead nodes, and communication delay is constructed. Second, to implement this model, an interval SPEA2 algorithm (I-SPEA2) that introduces an environmental response mechanism is proposed. I-SPEA2 treats individual target interval values as ranges of values on a two-dimensional coordinate axis, forming a quadrilateral, calculates individual size probabilities based on the area to determine the dominant relationship, and combines fixed distance and interval overlap to eliminate redundant individuals. The simulation results show that the interval dynamic model is effective in prolonging the lifecycle of WSN as well as the proposed algorithm reduces the mortality rate of the nodes by 15%, 28%, 13%, 16%, and 21% compared with other algorithms.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 19","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578112","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

Adversarial autoencoder for continuous sign language recognition 用于连续手语识别的对抗式自动编码器

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-04 DOI: 10.1002/cpe.8220

Suhail Muhammad Kamal, Yidong Chen, Shaozi Li

{"title":"Adversarial autoencoder for continuous sign language recognition","authors":"Suhail Muhammad Kamal, Yidong Chen, Shaozi Li","doi":"10.1002/cpe.8220","DOIUrl":"10.1002/cpe.8220","url":null,"abstract":"<div>\u0000 \u0000 <p>Sign language serves as a vital communication medium for the deaf community, encompassing a diverse array of signs conveyed through distinct hand shapes along with non-manual gestures like facial expressions and body movements. Accurate recognition of sign language is crucial for bridging the communication gap between deaf and hearing individuals, yet the scarcity of large-scale datasets poses a significant challenge in developing robust recognition technologies. Existing works address this challenge by employing various strategies, such as enhancing visual modules, incorporating pretrained visual models, and leveraging multiple modalities to improve performance and mitigate overfitting. However, the exploration of the contextual module, responsible for modeling long-term dependencies, remains limited. This work introduces an <b>A</b>dversarial <b>A</b>utoencoder for <b>C</b>ontinuous <b>S</b>ign <b>L</b>anguage <b>R</b>ecognition, <b>AA-CSLR</b>, to address the constraints imposed by limited data availability, leveraging the capabilities of generative models. The integration of pretrained knowledge, coupled with cross-modal alignment, enhances the representation of sign language by effectively aligning visual and textual features. Through extensive experiments on publicly available datasets (PHOENIX-2014, PHOENIX-2014T, and CSL-Daily), we demonstrate the effectiveness of our proposed method in achieving competitive performance in continuous sign language recognition.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576358","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

Dark channel enhancement research on human ear images based on smartphone photography 基于智能手机摄影的人耳图像暗通道增强研究

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-02 DOI: 10.1002/cpe.8216

Dongxin Lu, Danni Zheng, Lei Kou, Qingfeng Li, Wende Ke

{"title":"Dark channel enhancement research on human ear images based on smartphone photography","authors":"Dongxin Lu, Danni Zheng, Lei Kou, Qingfeng Li, Wende Ke","doi":"10.1002/cpe.8216","DOIUrl":"10.1002/cpe.8216","url":null,"abstract":"<div>\u0000 \u0000 <p>The experienced doctors can alleviate symptoms such as headaches, insomnia, anxiety, and depression by observing the patient's ears and massaging specific areas. In order to achieve remote ear condition diagnosis and guide patients to massage their ears independently through the network, patients can use their mobile phones to take and send photos of ears to doctors. However, due to significant differences in the clarity of photos taken by different mobile phones, as well as susceptibility to haze, lighting, jitter, and low pixels, the quality of photos is poor, which affects the accuracy of remote diagnosis by doctors. This study adopted an image preprocessing method based on He Kaiming's dark channel prior dehazing method to enhance the original ear images captured by mobile phones. The dehazing algorithm was used to remove the haze effect of the ear images, improving image quality and contrast, making the wrinkles, protrusions, pigmentation and other areas of the ear more obvious. The experiment has showed the comparison by adjusting weight from 15% to 95% between two methods—dark channel prior method and the dark channel prior method after preprocessing, which has proven the effectiveness of dehazing method in human ear images taken by mobile phones. The image quality after preprocessing and dehazing is widely recognized and accepted by doctors at hospitals in Hangzhou, China.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548484","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

A genetic algorithm-based virtual machine scheduling algorithm for energy-efficient resource management in cloud computing 基于遗传算法的虚拟机调度算法，用于云计算中的节能资源管理

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-07-02 DOI: 10.1002/cpe.8207

Feng Shi

{"title":"A genetic algorithm-based virtual machine scheduling algorithm for energy-efficient resource management in cloud computing","authors":"Feng Shi","doi":"10.1002/cpe.8207","DOIUrl":"10.1002/cpe.8207","url":null,"abstract":"<div>\u0000 \u0000 <p>To address the unbalanced resource load of a virtual machine cluster, the author proposes an energy-saving virtual machine scheduling algorithm based on resource management cloud computing technology. This article analyzes the current cloud computing and virtual machine scheduling research in the cloud computing environment. It discusses the concept, characteristics, classification, application scenarios, and key cloud computing technologies. A genetic algorithm is used to solve the problem of high energy consumption in the data center. The test results show that in the same original configuration scheme, the migration times based on the greedy algorithm adopted by GA2ND are about 1000, and the migration times of GA1ST are between 200 and 500. The GA2ND migration scheme requires fewer virtual machines. In the result analysis, the experiments compare the proposed algorithms—DVFS, IMC, GA1ST, and GA2ND—with a focus on energy consumption and virtual machine migration. Notably, DVFS serves as a reference for energy efficiency, IMC represents the proposed algorithm without genetic optimization, GA1ST denotes the genetic algorithm under a heterogeneous model, and GA2ND signifies the enhanced genetic algorithm introduced in this article. The comparison aims to assess the energy efficiency and virtual machine migration performance of each algorithm in the context of a simulated cloud computing environment. Therefore, the algorithm proposed in this article can effectively reduce energy consumption and avoid frequent migration of virtual machines.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 22","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505345","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

Boosting semi-supervised learning under imbalanced regression via pseudo-labeling 通过伪标记在不平衡回归条件下促进半监督学习

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-06-30 DOI: 10.1002/cpe.8103

Nannan Zong, Songzhi Su, Changle Zhou

{"title":"Boosting semi-supervised learning under imbalanced regression via pseudo-labeling","authors":"Nannan Zong, Songzhi Su, Changle Zhou","doi":"10.1002/cpe.8103","DOIUrl":"10.1002/cpe.8103","url":null,"abstract":"<div>\u0000 \u0000 <p>Imbalanced samples are widespread, which impairs the generalization and fairness of models. Semi-supervised learning can overcome the deficiency of rare labeled samples, but it is challenging to select high-quality pseudo-label data. Unlike discrete labels that can be matched one-to-one with points on a numerical axis, labels in regression tasks are consecutive and cannot be directly chosen. Besides, the distribution of unlabeled data is imbalanced, which easily leads to an imbalanced distribution of pseudo-label data, exacerbating the imbalance in the semi-supervised dataset. To solve this problem, this article proposes a semi-supervised imbalanced regression network (SIRN), which consists of two components: A, designed to learn the relationship between features and labels (targets), and B, dedicated to learning the relationship between features and target deviations. To measure target deviations under imbalanced distribution, the target deviation function is introduced. To select continuous pseudo-labels, the deviation matching strategy is designed. Furthermore, an adaptive selection function is developed to mitigate the risk of skewed distributions due to imbalanced pseudo-label data. Finally, the effectiveness of the proposed method is validated through evaluations of two regression tasks. The results show a great reduction in predicted value error, particularly in few-shot regions. This empirical evidence confirms the efficacy of our method in addressing the issue of imbalanced samples in regression tasks.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 19","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505346","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

A many objective based feature selection model for software defect prediction 基于多种目标的软件缺陷预测特征选择模型

IF 1.5 4区计算机科学

Concurrency and Computation-Practice & Experience Pub Date : 2024-06-28 DOI: 10.1002/cpe.8153

Qi Mao, Jingbo Zhang, Tianhao Zhao, Xingjuan Cai

{"title":"A many objective based feature selection model for software defect prediction","authors":"Qi Mao, Jingbo Zhang, Tianhao Zhao, Xingjuan Cai","doi":"10.1002/cpe.8153","DOIUrl":"10.1002/cpe.8153","url":null,"abstract":"<div>\u0000 \u0000 <p>Given the escalating magnitude and intricacy of software systems, software measurement data often contains irrelevant and redundant features, resulting in significant resource and storage requirements for software defect prediction (SDP). Feature selection (FS) has a vital impact on the initial data preparation phase of SDP. Nonetheless, existing FS methods suffer from issues such as insignificant dimensionality reduction, low accuracy in classifying chosen optimal feature sets, and neglect of complex interactions and dependencies between defect data and features as well as between features and classes. To tackle the aforementioned problems, this paper proposes a many-objective SDPFS (MOSDPFS) model and the binary many-objective PSO algorithm with adaptive enhanced selection strategy (BMaOPSO-AR2) is proposed within this paper. MOSDPFS selects F1 score, the number of features within subsets, and correlation and redundancy measures based on mutual information (MI) as optimization objectives. BMaOPSO-AR2 constructs a binary version of MaOPSO using transfer functions specifically for binary classification. Adaptive update formulas and the introduction of the R2 indicator are employed to augment the variety and convergence of algorithm. Additionally, performance of MOSDPFS and BMaOPSO-AR2 are tested on the NASA-MDP and PROMISE datasets. Numerical results prove that a proposed model and algorithm effectively reduces feature count while enhancing predictive accuracy and minimizing model complexity.</p>\u0000 </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"36 19","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505349","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