International Journal of Crowd Science最新文献_第6页

Optimizing Service Efficacy in 5G HetNets: An Adaptive Acceleration PSO Approach 优化 5G HetNets 中的服务效率：自适应加速 PSO 方法

International Journal of Crowd Science Pub Date : 2024-09-16 DOI: 10.26599/IJCS.2024.9100024

Guowen Li;Wenbo Hu;Yang Zhao;Xudong Lu

{"title":"Optimizing Service Efficacy in 5G HetNets: An Adaptive Acceleration PSO Approach","authors":"Guowen Li;Wenbo Hu;Yang Zhao;Xudong Lu","doi":"10.26599/IJCS.2024.9100024","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100024","url":null,"abstract":"The dense deployment of Femto Base Stations (FBS) assisting Macro Base Stations (MBS) in a Heterogeneous Network (HetNet) resolves the coverage issue of 5G signal transmission. However, the imprudent layout of FBSs results in extensive energy consumption and increased signal interference among base stations. Regulating the transmission power of each base station in the HetNets through the main controller or MBS is essential to maximize the power efficiency of the entire HetNets while adhering to the constraints of basic signal throughput and fairness. To address this challenge, this paper proposes an Adaptive Acceleration Particle Swarm Optimization (AA-PSO) algorithm. This algorithm dynamically determines the inertia weight based on each particle's optimal position and the global optimal position, and introduces the concept of time-varying parameters to control the learning rate, thus managing the search range and convergence speed of the particle swarm. The results demonstrate that the AA-PSO algorithm can efficiently determine the optimal transmission power of each base station in the HetNets, reduce interference between MBS and FBSs, as well as among FBSs, and ultimately improve the service efficacy of the entire network.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"168-175"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681262","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235873","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

Index Prediction Model Based on LASSO-PCA and Deep Learning 基于 LASSO-PCA 和深度学习的指数预测模型

International Journal of Crowd Science Pub Date : 2024-09-16 DOI: 10.26599/IJCS.2024.9100013

Bo Xu;Xinpu Su;Yijun He

{"title":"Index Prediction Model Based on LASSO-PCA and Deep Learning","authors":"Bo Xu;Xinpu Su;Yijun He","doi":"10.26599/IJCS.2024.9100013","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100013","url":null,"abstract":"Predicting financial market trends poses significant challenges due to the complex, dynamic, and often chaotic nature of the market, especially when dealing with data featuring a multitude of characteristics. In this research, we propose an effective data mining approach that combines Least Absolute Shrinkage and Selection Operator (LASSO) and Principal Component Analysis (PCA) for two-stage feature dimensionality reduction, resulting in a refined dataset. To enhance the model's capacity to capture medium- and long-term index trends, we implement a sliding time window approach, utilizing data from the preceding 60 trading days. Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) models are employed to predict the return rate of Securities Bank of China (399986) over a 30-day trading period. We conducted a comprehensive comparative analysis involving our proposed model and established methods, namely, LASSO, PCA, and Hybrid Recurrent Neural Networks (RNN). Our empirical findings unequivocally demonstrate the superior performance of our model in terms of both prediction accuracy and stability. Specifically, our model exhibits significantly higher predictive accuracy when forecasting the return rate of Securities Bank of China (399986) over a 30-day trading period, all while maintaining enhanced stability. These results underscore the exceptional efficacy of our approach within the realm of financial market time series forecasting, thus providing robust support for further research and practical applications within this domain.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"176-183"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235874","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

ECG Signal Processing and Automatic Classification Algorithms 心电信号处理和自动分类算法

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2023.9100026

Xiaonuo Yang;Yueting Chai

引用次数: 0

Heterogeneous Electric Vehicle Routing Problem with Multiple Compartments and Multiple Trips for the Collection of Classified Waste 用于收集分类垃圾的多车厢多行程异构电动汽车路线问题

International Journal of Crowd Science Pub Date : 2024-08-19

引用次数: 0

Role of Technology Self-Efficacy and Digital Alliance in Digital Mental Health Tool Acceptance Among University Students in Singapore 技术自我效能感和数字联盟在新加坡大学生接受数字心理健康工具中的作用

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2024.9100001

Toh Hsiang Benny Tan;Sufang Lim;Chan Hua Nicholas Vun

引用次数: 0

Optimizing the Service Efficacy of Crowd Ratings in Curbing Fake News Dissemination on Social Media 优化群众评分在遏制社交媒体假新闻传播中的服务功效

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2024.9100020

Qian Liu;Yang Lyu;Jian Tang;Weiguo Fan

{"title":"Optimizing the Service Efficacy of Crowd Ratings in Curbing Fake News Dissemination on Social Media","authors":"Qian Liu;Yang Lyu;Jian Tang;Weiguo Fan","doi":"10.26599/IJCS.2024.9100020","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100020","url":null,"abstract":"Curbing the dissemination of fake news in social media has been a major issue in recent years. Previous studies have suggested that the general public can recognize fake news, showing the feasibility of applying crowd ratings to identify fake news. However, the effectiveness of crowd ratings for curbing the dissemination of fake news is uncertain. This study constructed an online experimental platform to simulate Sina Microblog and designed a crowd rating strategy to compare and validate the difference between the absence vs. the presence of crowd ratings, and crowd ratings vs. expert ratings, in curbing the dissemination of fake news. We found that the presence of crowd ratings inhibited users' dissemination of fake news compared to the absence of crowd ratings. Moreover, there was no significant difference between the suppression effects of crowd ratings and expert ratings, both of which were effective in curbing the dissemination of fake news. Crowd rating uses collective intelligence to intervene in users' perceptions and behaviors at the onset of fake news dissemination, providing a cost-effective and efficient solution to combat the spread of fake news on social media.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 3","pages":"110-121"},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10638683","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013373","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

Measurement and Optimization of Metro Network Service Efficacy 测量和优化地铁网络服务效率

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2024.9100015

Leiju Qiu;Xiao Sun;Yong Tu;Yang Zhao

引用次数: 0

Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition 用于低资源命名实体识别的反向注意力知识转移

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2023.9100014

Shengfei Lyu;Linghao Sun;Huixiong Yi;Yong Liu;Huanhuan Chen;Chunyan Miao

{"title":"Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition","authors":"Shengfei Lyu;Linghao Sun;Huixiong Yi;Yong Liu;Huanhuan Chen;Chunyan Miao","doi":"10.26599/IJCS.2023.9100014","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100014","url":null,"abstract":"In recent years, great success has been achieved in many tasks of natural language processing (NLP), e.g., named entity recognition (NER), especially in the high-resource language, i.e., English, thanks in part to the considerable amount of labeled resources. More labeled resources, better word representations. However, most low-resource languages do not have such an abundance of labeled data as high-resource English, leading to poor performance of NER in these low-resource languages due to poor word representations. In the paper, we propose converse attention network (CAN) to augment word representations in low-resource languages from the high-resource language, improving the performance of NER in low-resource languages by transferring knowledge learned in the high-resource language. CAN first translates sentences in low-resource languages into high-resource English using an attention-based translation module. In the process of translation, CAN obtains the attention matrices that align word representations of high-resource language space and low-resource language space. Furthermore, CAN augments word representations learned in low-resource language space with word representations learned in high-resource language space using the attention matrices. Experiments on four low-resource NER datasets show that CAN achieves consistent and significant performance improvements, which indicates the effectiveness of CAN.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 3","pages":"140-148"},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10638678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013156","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

Heterogeneous Electric Vehicle Routing Problem with Multiple Compartments and Multiple Trips for the Collection of Classified Waste 用于收集分类垃圾的多车厢多行程异构电动汽车路线问题

International Journal of Crowd Science Pub Date : 2024-08-19 DOI: 10.26599/IJCS.2023.9100030

Zhishuo Liu;Lujing Sun;Xingquan Zuo;Haoxiang Li

{"title":"Heterogeneous Electric Vehicle Routing Problem with Multiple Compartments and Multiple Trips for the Collection of Classified Waste","authors":"Zhishuo Liu;Lujing Sun;Xingquan Zuo;Haoxiang Li","doi":"10.26599/IJCS.2023.9100030","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100030","url":null,"abstract":"This paper studies the collection of classified waste using electric commercial vehicles (ECVs). The fleet of ECVs is heterogeneous, and ECVs have separated compartments, namely, they have different capacities for each type of waste. Each ECV is allowed to deliver multiple times and can be recharged more than once in public recharging stations during its route. A mathematical model is proposed for the heterogeneous electric vehicle routing problem with multiple compartments, multiple trips, and time windows (HEVRP-MCMT). The objective of the problem is to minimize the vehicle fixed cost and variable energy consumption cost. A hybrid ant colony optimization (ACO) with variable neighborhood search (VNS) is developed and applied to a number of problem instances and a real-life instance. Numerical results show that, for small-scale problem instances, our approach finds better or the same optimal solutions in a significantly shorter computational time than CPLEX; for large-scale problem instances, our approach outperforms two meta-heuristics. Experiments on a real-life problem instance show that using a fleet of multicompartment vehicles can save considerable cost compared with using single-compartment vehicles only.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 3","pages":"130-139"},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10638679","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013158","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

A Survey of Personalized Medicine Recommendation 个性化医疗建议调查

International Journal of Crowd Science Pub Date : 2024-03-14 DOI: 10.26599/IJCS.2023.9100013

Fanglin Zhu;Lizhen Cui;Yonghui Xu;Zhe Qu;Zhiqi Shen

{"title":"A Survey of Personalized Medicine Recommendation","authors":"Fanglin Zhu;Lizhen Cui;Yonghui Xu;Zhe Qu;Zhiqi Shen","doi":"10.26599/IJCS.2023.9100013","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100013","url":null,"abstract":"Mining potential and valuable medical knowledge from massive medical data to support clinical decision-making has become an important research field. Personalized medicine recommendation is an important research direction in this field, aiming to recommend the most suitable medicines for each patient according to the health status of the patient. Personalized medicine recommendation can assist clinicians to make clinical decisions and avoid the occurrence of medical abnormalities, so it has been widely concerned by many researchers. Based on this, this paper makes a comprehensive review of personalized medicine recommendation. Specifically, we first make clear the definition of personalized medicine recommendation problem; then, starting from the key theories and technologies, the personalized medicine recommendation algorithms proposed in recent years are systematically classified (medicine recommendation based on multi-disease, medicine recommendation with combination pattern, medicine recommendation with additional knowledge, and medicine recommendation based on feedback) and in-depth analyzed; and this paper also introduces how to evaluate personalized medicine recommendation algorithms and some common evaluation indicators; finally, the challenges of personalized medicine recommendation problem are put forward, and the future research direction and development trends are prospected.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 2","pages":"77-82"},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10530641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924743","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