Systems and Soft Computing最新文献_第3页

The application of improved DTW algorithm in sports posture recognition 改进的 DTW 算法在运动姿势识别中的应用

Systems and Soft Computing Pub Date : 2024-10-16 DOI: 10.1016/j.sasc.2024.200163

Changjiang Niu

{"title":"The application of improved DTW algorithm in sports posture recognition","authors":"Changjiang Niu","doi":"10.1016/j.sasc.2024.200163","DOIUrl":"10.1016/j.sasc.2024.200163","url":null,"abstract":"<div><div>Sports posture recognition plays a crucial role in modern sports science and training. Posture recognition and analysis plays a positive role in improving sports quality and ensuring sports safety. However, existing recognition technologies still have poor recognition and accuracy in large amounts of posture data. Therefore, to further improve the performance of the existing posture recognition techniques, this study assumes that postures during movement can be effectively represented through the time series of skeletal key points, and the local similarity of these postures can be captured through the Dynamic Time Warping (DTW) algorithm. Based on this assumption, the existing DTW algorithm is improved by introducing the K-Nearest Neighbor (KNN) algorithm and combining it with Principal Component Analysis (PCA) for feature dimensionality reduction. A novel algorithmic model for postures recognition is proposed. The experimental results showed that the improved algorithm performed well in postures recognition rate and accuracy. Especially, when the k value was 5, the recognition rate reached up to 89%, and the accuracy reached 87%. Compared with the existing algorithm, the improved KNN-DTW algorithm has significant improvement in accuracy and computational efficiency. In summary, the new algorithm shows significant advantages in terms of accuracy and stability, providing a powerful tool for the analysis of athletic postures in the field of sports. Meanwhile, this research result has important application prospects in fields such as sports training, sports medicine, and virtual reality.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200163"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and implementation of J2EE-based statement feature recognition in English teaching system optimization 基于 J2EE 的语句特征识别在英语教学系统优化中的设计与实现

Systems and Soft Computing Pub Date : 2024-10-16 DOI: 10.1016/j.sasc.2024.200162

Lina Wang

{"title":"Design and implementation of J2EE-based statement feature recognition in English teaching system optimization","authors":"Lina Wang","doi":"10.1016/j.sasc.2024.200162","DOIUrl":"10.1016/j.sasc.2024.200162","url":null,"abstract":"<div><div>With the development of Internet technology, network English teaching system came into being and developed rapidly. Based on optimized J2EE, this paper presents the implementation of sentence feature recognition in the English teaching system. Optimize the load balancing algorithm on the basis of cloud computing technology, and improve the teaching service providing ability of online teaching system based on J2EE. The technology integration of Sturts2, Spring, and Batis was realized to realize the persistence layer, business layer, and presentation layer respectively through the three frameworks. Then, the technology of Struts2 and Spring, Spring, and Batis software is integrated to analyze and build the current popular SSI lightweight framework, and RBAC is used to provide a security mechanism for the SSI framework. It establishes that the information system should adopt the mixed architecture of B/S architecture and C/S architecture, and then design the overall functional structure of the system with students, teachers, and administrators as the main users from the perspective of users. This paper analyzes and explains the overall structure of the J2Ee-based English teaching system, briefly introduces the overall framework of the whole website, and introduces the main functions of each functional module of the website. Finally, the English teaching system based on optimized J2EE statement feature recognition is implemented and tested. In the performance test of file resource query service with virtual 10–100 users and 20 times submitted by each user, the response time of the system is <1.5 s, the success rate reaches 100 %, and the CPU utilization is also <5 %. The memory usage is relatively high. When 2000 queries are concurrent, the memory usage reaches >160 M.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200162"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development 推进可持续交通：利用机器学习技术和预测性应用开发对电动汽车充电周期进行动态预测建模

Systems and Soft Computing Pub Date : 2024-10-13 DOI: 10.1016/j.sasc.2024.200157

Biplov Paneru , Durga Prasad Mainali , Bishwash Paneru , Sanjog Chhetri Sapkota

{"title":"Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development","authors":"Biplov Paneru , Durga Prasad Mainali , Bishwash Paneru , Sanjog Chhetri Sapkota","doi":"10.1016/j.sasc.2024.200157","DOIUrl":"10.1016/j.sasc.2024.200157","url":null,"abstract":"<div><div>The main goal in this research is to train various machine learning models to predict charging cycles in EV Electric Vehicles) battery systems. The considered models are gradient boosting, random forests, decision trees, and linear regression. Each of these was assessed based on its R-squared score, which is an important statistical measure in indicating the variance proportion yielded by the model. In contrast, the Random Forest model significantly improved, with an R-squared value of 0.83, thereby doing an excellent job in capturing nuances of the data. Only surpassed by the Gradient Boosting model at an astonishing R-squared score of 0.87, it is this excellent score that underlines its capability to predict the outcome quite accurately by modeling complex interrelations. In other words, gradient boosting outran the rest and provided the most robust results concerning drivers of students' performance. It also underlines how important choosing a good model is in educational analytics in order to increase the accuracy of the predictions. The use of these models in the proposed EV Battery Charging Cycle Predictor App results in accurate predictions to aid schedule maintenance and energy-related decisions. This research brings light to the future of advanced machine learning methods in enhancing the battery efficiencies of EVs and the development of electric mobility technologies. It is possible that the future work will imply the additional inclusion of real data and the integration of the application to general energy systems.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200157"},"PeriodicalIF":0.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Innovative application of particle swarm algorithm in the improvement of digital enterprise management efficiency 粒子群算法在提高数字化企业管理效率中的创新应用

Systems and Soft Computing Pub Date : 2024-10-12 DOI: 10.1016/j.sasc.2024.200151

Shengnan Zhang

引用次数: 0

Wavelet neural network algorithm for hybrid GA in infrared CO2 gas sensor 用于红外二氧化碳气体传感器混合 GA 的小波神经网络算法

Systems and Soft Computing Pub Date : 2024-10-12 DOI: 10.1016/j.sasc.2024.200145

Jun Wang, Yuanxi Wang

{"title":"Wavelet neural network algorithm for hybrid GA in infrared CO2 gas sensor","authors":"Jun Wang, Yuanxi Wang","doi":"10.1016/j.sasc.2024.200145","DOIUrl":"10.1016/j.sasc.2024.200145","url":null,"abstract":"<div><div>As the economy develops and the environmental impact of the greenhouse effect becomes more apparent, the need for precise measurement of specific gas concentrations in the air has become increasingly pressing. Nevertheless, as a representative of greenhouse gases, CO<sub>2</sub> gas detectors are susceptible to environmental temperature fluctuations, which impairs the accuracy of detection. To address this issue, the research team innovatively combined the genetic algorithm (GA) and the wavelet neural network (WNN) to develop a solution for the temperature compensation problem of the infrared CO<sub>2</sub> gas sensor. The non-dominant sorted genetic algorithm II (NSGA-II) was integrated into the GA to achieve a balance between the accuracy, complexity, and temperature performance of the model through multi-objective optimization. The results showed that compared with other existing models, the GA-WNN model proposed in this study can significantly reduce the difference between the detected values and the actual environmental values under various temperature conditions when processing data. Especially at an ambient temperature of 49 °C, for a true CO<sub>2</sub> concentration of 2000 ppm, the detection value processed by the GA-WNN algorithm was 2046 ppm, with a relative error of only 2.3 %, far lower than the 9.8 % of Faster RCNN algorithm and 11.5 % of WNN algorithm. The contribution of the research is the proposal of a novel temperature compensation method that significantly enhances the precision of infrared CO<sub>2</sub> gas sensors. This is of paramount importance for enhancing the accuracy of gas detection in environmental monitoring and industrial control.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200145"},"PeriodicalIF":0.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated painting color matching technology based on semantic intelligence understanding 基于语义智能理解的自动绘画色彩匹配技术

Systems and Soft Computing Pub Date : 2024-10-10 DOI: 10.1016/j.sasc.2024.200158

Jiayin Zhang

引用次数: 0

Innovative strategies for intelligent services in smart libraries in the information age based on linear discriminant analysis 基于线性判别分析的信息时代智慧图书馆智能服务创新策略

Systems and Soft Computing Pub Date : 2024-10-09 DOI: 10.1016/j.sasc.2024.200159

Jinying Wang, Yuhua Liang, Jingjing Ma

{"title":"Innovative strategies for intelligent services in smart libraries in the information age based on linear discriminant analysis","authors":"Jinying Wang, Yuhua Liang, Jingjing Ma","doi":"10.1016/j.sasc.2024.200159","DOIUrl":"10.1016/j.sasc.2024.200159","url":null,"abstract":"<div><div>With the advent of the information age, to provide better services and ensure the security management of libraries, intelligent facial recognition technology has gradually become a hot research direction in library management. Meanwhile, to further improve the comprehensive performance of facial recognition, this study attempts to integrate principal component analysis and linear discriminant analysis on the basis of analyzing the framework of recognition technology. Afterwards, it introduced support vector machines for recognition and classification, and proposed a new recognition model. The experimental results show that the recognition accuracy of the proposed model is up to 97 % in the ORL dataset and 94 % in the Yale dataset. The recognition error rate is as low as 0.1 % when the number of training samples is 215 and the number of iterations is 200. The model has the best recognition performance when the image size is 25 × 25 mm and the number of noises is 10. In addition, the model is particularly effective in recognition on single person color or gray images, with the highest P-value of 98.7 %, the highest R-value of 98.8 %, and the highest F1-value of 97.5 %. These results show that the proposed model significantly improves the accuracy and robustness of face recognition, and provides strong technical support for intelligent service innovation in smart libraries.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200159"},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Takagi-Sugeno fuzzy gain controller for Vehicle-to-Grid (V2G) load frequency control 用于车联网 (V2G) 负载频率控制的高木-菅野模糊增益控制器

Systems and Soft Computing Pub Date : 2024-10-08 DOI: 10.1016/j.sasc.2024.200150

Marayati Marsadek , Farrukh Nagi , Navinesshani Permal , Agileswari AP Ramasamy , Aidil Azwin

{"title":"Takagi-Sugeno fuzzy gain controller for Vehicle-to-Grid (V2G) load frequency control","authors":"Marayati Marsadek , Farrukh Nagi , Navinesshani Permal , Agileswari AP Ramasamy , Aidil Azwin","doi":"10.1016/j.sasc.2024.200150","DOIUrl":"10.1016/j.sasc.2024.200150","url":null,"abstract":"<div><div>Load Frequency Control (LFC) has gained more importance with the introduction of deregulated Renewable Energy Sources (RES) connectivity with the grid. Electrical Vehicles (EVs) can feed electricity back into the grid in Vehicle-to-Grid (V2G) mode to maintain stability. However, the increasing number of EVs penetrating the grid causes frequency instability in the power system. If required, EVs may utilize bi-directional chargers to transfer power back to the grid in the V2G mode while they are charging or in a grid-connected state, restoring the frequency instability of the grid. The frequency restoration response time is important to reset the grid frequency fluctuations in the shortest time possible to avoid shutting down the power system. This paper presents a Takagi-Sugeno (T-S) fuzzy linear output controller for LFC in two-area systems with tie-line control. This work models EV batteries as a single lump of large-capacity battery energy storage systems. The EV's battery system provides ancillary power to the two-area power system to reset it to a steady state after a load disturbance. The T-S fuzzy controller's linear output dependency on its inputs enables it to respond efficiently to load variations in the nonlinear two-area power systems. The proposed controller parameters are evaluated from stability analyses and its robustness is tested with sensitivity analysis. It is compared with other fuzzy controllers, and it demonstrates a fast-settling time and reduced frequency deviation response.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200150"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid data mining and data-driven algorithms for a green logistics transportation network in the post-COVID era: A case study in the USA 后 COVID 时代绿色物流运输网络的混合数据挖掘和数据驱动算法：美国案例研究

Systems and Soft Computing Pub Date : 2024-10-06 DOI: 10.1016/j.sasc.2024.200156

Sina Abbasi , Seyedeh Saeideh Mousavi , Ebrahim Farbod , Mohammad Yousefi Sorkhi , Mohammad Parvin

{"title":"Hybrid data mining and data-driven algorithms for a green logistics transportation network in the post-COVID era: A case study in the USA","authors":"Sina Abbasi , Seyedeh Saeideh Mousavi , Ebrahim Farbod , Mohammad Yousefi Sorkhi , Mohammad Parvin","doi":"10.1016/j.sasc.2024.200156","DOIUrl":"10.1016/j.sasc.2024.200156","url":null,"abstract":"<div><div>This study examines the problem of item allocation in a post-COVID environment with various products and a large customer base. The number of customers has increased due to the rise of internet access and the growing willingness to shop online. Problems such as the timely delivery of goods or services, the selection and destination of orders in decentralized warehouses, and the allocation of warehouses to customers are difficult to overcome with a large variety of items and many customers. It has been proposed that mathematical modeling in combination with meta-heuristic solution techniques solve these problems. However, solving mathematical models is very time-consuming and labor-intensive because there are many different location situations. Due to computing power and memory capacity advances, researchers have been looking at data-driven solutions to these problems. This study aims to tackle the diversity of commodities and the number of consumers in the post-COVID era by proposing a hybrid data-driven approach that combines data mining and mathematical modeling to solve mathematical location models with high accuracy in less time. This paper was implemented based on data from real cases in the USA.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200156"},"PeriodicalIF":0.0,"publicationDate":"2024-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic ranking function to optimize transshipment costs in intuitionistic Type-2 and Type-1 fuzzy environments 在直观 2 类和 1 类模糊环境中优化转运成本的动态排序函数

Systems and Soft Computing Pub Date : 2024-09-29 DOI: 10.1016/j.sasc.2024.200153

Tarun Kumar , Sadhna Chaudhary , Kapil Kumar , Kailash Dhanuk , M.K. Sharma

{"title":"Dynamic ranking function to optimize transshipment costs in intuitionistic Type-2 and Type-1 fuzzy environments","authors":"Tarun Kumar , Sadhna Chaudhary , Kapil Kumar , Kailash Dhanuk , M.K. Sharma","doi":"10.1016/j.sasc.2024.200153","DOIUrl":"10.1016/j.sasc.2024.200153","url":null,"abstract":"<div><div>In the dynamic realm of organizational logistics, accurately minimizing transportation and transshipment costs is crucial, yet often challenging due to inherent uncertainties. This paper introduces a novel application of fuzzy logic to provide a more precise analysis of these costs. Specifically, it develops an innovative ranking function for trapezoidal fuzzy numbers (TrFNs) for Type-2 and Type-1 fuzzy environments, a tool yet unexplored in existing literature. The main contributions of this paper are the idea that a ranking function for TrFNs can significantly improve decision-maker's freedom in cost analysis due to an adherence on all (a, b, c d) parameters of TrFN. A new decision-oriented ranking method for these fuzzy numbers is developed which consists of an inventive algorithm. The method is also considered for intuitionistic TrFNs and applied to solve transshipment costs in fuzzy area. To verify the proposed methodology's efficiency, effectiveness and accuracy a numerical example in Wolfram Mathematica 9.0 is demonstrated showing superior computational performance over existing methods.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"6 ","pages":"Article 200153"},"PeriodicalIF":0.0,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0