AUTOMATIC CONTROL AND COMPUTER SCIENCES最新文献_第3页

Efficient Approach for Solving Economic Load Dispatch Problems of Hybrid Renewable Energy System Using Particle Swarm Optimization Algorithm 用粒子群算法求解混合可再生能源系统经济负荷调度问题的有效方法

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-07-04 DOI: 10.3103/S0146411625700117

Nimish Kumar, Rahul Raman

{"title":"Efficient Approach for Solving Economic Load Dispatch Problems of Hybrid Renewable Energy System Using Particle Swarm Optimization Algorithm","authors":"Nimish Kumar,  Rahul Raman","doi":"10.3103/S0146411625700117","DOIUrl":"10.3103/S0146411625700117","url":null,"abstract":"The incorporation of renewable energy (RE) in the economic load dispatch problems (ELDPs) is not an easy task. This paper presents a reliable approach to solve the ELDPs of the hybrid renewable energy system (HRES) that consists of thermal, wind, and solar photovoltaic (PV) generators. The generation cost of RE is negligible, but the renewable operators demand some charge so-called renewable/maintenance/payback cost to run the plant. Therefore, the linear cost function has been implemented for RE generations (REGs). Two cases have been considered based on the cost of REGs, one is no cost for REGs and other is linear cost functions for REGs. The popular optimization technique known as particle swarm optimization (PSO) has been adopted to solve the ELDPs. A test system made of IEEE 30-bus system, solar PV, and wind generator has been considered to investigate the strength of the proposed approach. The simulation results show that the saving of 63.829, 74.99, and 182.937 $/h in one case and the saving of 139.53, 150.468, and 358.883 $/h in another case in the generation cost for a load demand of 283.4 MW are remarkable, when only solar PV, only wind and both solar PV and wind respectively, are in operation.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 2","pages":"127 - 137"},"PeriodicalIF":0.5,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160730","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

HBbITL: A Hierarchical Blockchain Based Secure Intelligent Traffic Light System HBbITL：基于分层区块链的安全智能交通灯系统

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-07-04 DOI: 10.3103/S0146411625700154

Sukanta Chakraborty, Abhishek Majumder

引用次数: 0

Empowering Home Health Care: Precision Unleashed with an Innovative Hybrid Machine Learning Approach for Tailored Patient Classifications 授权家庭医疗保健：利用创新的混合机器学习方法为量身定制的患者分类释放精度

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-07-04 DOI: 10.3103/S014641162570018X

Brahim Issaoui, Issam Zidi, Salim El Khediri, Rehan Ullah Khan

{"title":"Empowering Home Health Care: Precision Unleashed with an Innovative Hybrid Machine Learning Approach for Tailored Patient Classifications","authors":"Brahim Issaoui, Issam Zidi, Salim El Khediri, Rehan Ullah Khan","doi":"10.3103/S014641162570018X","DOIUrl":"10.3103/S014641162570018X","url":null,"abstract":"Governments are actively seeking solutions to address the growing issue of longer waiting times for patients. To reduce the strain on the public sector and its increasing workload, the governmental bodies have established collaborative agreements with private healthcare service providers. While the private sector is expanding, it is not growing rapidly enough to meet the rising demands for healthcare services. Consequently, there is a dire need to explore innovative management techniques aimed at reducing patient wait times, cutting costs, and enhancing the quality of healthcare. In this paper, we propose an innovative solution to tackle the patient classification problem (PCP) using the machine learning paradigm. The proposed approach involves a hybridization of two classifiers, one utilizing the aggregation method and the other employing the support vector machine technique. We compare classification algorithms, including KNN, SVM, SVM + AM, and logistic regression, and evaluate their performance in terms of precision, recall, specificity, F1-score, and overall accuracy. The SVM + AM is found to be the best model for the classification of patients, followed by SVM, KNN, and logistic regression. We believe that such an evaluation will help addressing the challenges associated with patient classification, the medical practitioners, and, in turn, contribute to the overall healthcare system.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 2","pages":"219 - 229"},"PeriodicalIF":0.5,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145162150","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

Estimating Page Ranks with Inductive Capability of Graph Neural Networks and Zone Partitioning in Information Retrieval 基于图神经网络归纳能力和信息检索区域划分的页面排名估计

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-07-04 DOI: 10.3103/S0146411625700130

Fargana Abdullayeva, Suleyman Suleymanzade

{"title":"Estimating Page Ranks with Inductive Capability of Graph Neural Networks and Zone Partitioning in Information Retrieval","authors":"Fargana Abdullayeva,  Suleyman Suleymanzade","doi":"10.3103/S0146411625700130","DOIUrl":"10.3103/S0146411625700130","url":null,"abstract":"one of the important features of information retrieval systems is ranking. Ranking performs the function of ranking search results based on relevance to the user’s query. Methods developed in state-of-the-art research still require multiple iterations. In this paper, we proposed to use zone partitioning strategies for computing web page rank parameters in retrieval systems, which implements iterative calculation for only some randomly selected subgraphs (zone). The zone approach is based on the idea to use multiple neural networks to classify rank data in graph-based structures. The crawled web pages are fragmented into three distinct zones. The core zone is used for training graph convolutional network, in this zone, the labels are known. It is covered with an undiscovered zone, where classifiers label node parameters. The most interesting part is the intersection zone, which represents the set of nodes and edges that belong to more than one undiscovered zone. The experiments show that the probability of classifying the true labels in the intersection zones via aggregating the results of multiple classifiers in some cases is higher than in undiscovered zones.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 2","pages":"150 - 163"},"PeriodicalIF":0.5,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145162148","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 Forecasting Model Fuzzy Time Series Type 2 with Hedge Algebraic and Genetic Optimization Algorithm 模糊时间序列2型对冲代数遗传优化预测模型

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S014641162570004X

Nguyen Thi Thu Dung, L. V. Chernenkaya

引用次数: 0

Event-Triggered Orthogonal Estimator Design for Cloud Communication Based Unmanned Aerial Vehicle System 基于云通信的无人机系统事件触发正交估计器设计

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S0146411625700063

Vasanthakumar Sekar, K. Senthilkumar, K. Srinivasan

引用次数: 0

An Effective Security Enhancement Scheme for Postquantum Cryptography Based Blockchain Networks in Cloud Computing 云计算中基于后量子密码的区块链网络安全增强方案

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S0146411625700087

Sripriya Arunachalam

引用次数: 0

Active Control of Vehicle Suspension System with Robust Control 基于鲁棒控制的汽车悬架系统主动控制

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S0146411625700026

Ali Khudhair Al-Jiboory, Zaid S. Hammoudi

引用次数: 0

An Adaptive Fast Sliding Mode Control for Trajectory Tracking of Robotic Manipulators 机械臂轨迹跟踪的自适应快速滑模控制

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S0146411625700099

Zhang Xin, Qing Shaojun

引用次数: 0

Optimal Prediction Model of Default Probability Based on Multiple Machine Learning Methods 基于多种机器学习方法的违约概率最优预测模型

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AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-06-22 DOI: 10.3103/S0146411625700105

Zhanjiang Li, Xueting Ren, Hua Tao

{"title":"Optimal Prediction Model of Default Probability Based on Multiple Machine Learning Methods","authors":"Zhanjiang Li, Xueting Ren, Hua Tao","doi":"10.3103/S0146411625700105","DOIUrl":"10.3103/S0146411625700105","url":null,"abstract":"The prediction of the probability of default can help banks and other financial institutions to effectively identify and assess the potential default risk associated with family farms, thereby reducing losses due to bad debts. Although many methods are available for constructing models for the probability of default, the choice of optimal models is still inconclusive. Taking the survey data of 722 family farms in China Inner Mongolia as the empirical objects, 4 machine learning methods, including binary classification logistic regression, decision tree CART algorithm, random forest, and kernel support vector machine, were used to construct the default probability prediction model for family farms. By comparing and analyzing the four models, we found a better default probability prediction model to help financial institutions better audit the qualifications of family farms and reduce borrowing risks. The results showed that (1) the three models except logistic regression had strong prediction ability, which was higher than 90%, and the classification effect was good; and (2) the random forest model had the best prediction effect, the decision tree was the second, and the logistic regression was the worst.","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 1","pages":"116 - 125"},"PeriodicalIF":0.5,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144419","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