International Journal of Information Technologies and Systems Approach最新文献_第5页

An Effective Emotional Analysis Method of Consumer Comment Text Based on ALBERT-ATBiFRU-CNN 基于ALBERT ATBiFRU CNN的消费者评论文本情感分析方法

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-06-08 DOI: 10.4018/ijitsa.324100

Mei Yang

{"title":"An Effective Emotional Analysis Method of Consumer Comment Text Based on ALBERT-ATBiFRU-CNN","authors":"Mei Yang","doi":"10.4018/ijitsa.324100","DOIUrl":"https://doi.org/10.4018/ijitsa.324100","url":null,"abstract":"To address the challenges of insufficient feature extraction for text sentiment analysis in the e-commerce big data environment, the author proposes a deep learning-based emotion analysis method of consumer comment text. Firstly, the author obtained the contextualized word vectors by using a pretrained language model called A Lite Bidirectional Encoder Representations From Transformers (ALBERT). Secondly, the researcher used the bidirectional gate recurrent unit (BiGRU) model to capture the semantic information through the combination of positive and negative directions, measure the emotional polarity information of each text as a whole, and then catch the local characteristic information of the text using the convolutional neural network (CNN) model. Finally, the author calculated the weight distribution through the attention mechanism. The experiments on a publicly available consumer review dataset showed that the recall, precision, and F1-score of the proposed text emotion analysis method were 0.9417, 0.9552, and 0.9484, respectively, which are higher than the existing methods. Therefore, the proposed method is of great significance in capturing the emotions of consumers on e-commerce platforms.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43324586","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

Research on Big Data-Driven Urban Traffic Flow Prediction Based on Deep Learning 基于深度学习的大数据驱动城市交通流量预测研究

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-06-02 DOI: 10.4018/ijitsa.323455

Xiao Qin

{"title":"Research on Big Data-Driven Urban Traffic Flow Prediction Based on Deep Learning","authors":"Xiao Qin","doi":"10.4018/ijitsa.323455","DOIUrl":"https://doi.org/10.4018/ijitsa.323455","url":null,"abstract":"This paper introduces an innovative approach for the urban traffic flow prediction (TFP) that utilizes big data and deep learning (D-L) to improve accuracy, reducing the incidence of large errors commonplace in traditional methods. By implementing this method, sustainable urban developments are able to be achieved more effectively in the future. First, an Attention-CNN-GRU-ResNet (ACGR) TFP model is built with the D-L network by gridding the urban traffic flow (TF) into a three-dimensional S-T tensor sequence. An attention-based GRU is then introduced to combine spatial and channel attention in the traditional GRU, and the time dependence and spatio-temporal (S-T) heterogeneity of TF in each subset are effectively extracted. Finally, a ResNet module is introduced to capture the S-T dependency, which helps avoid the deep network degradation caused by excessive layers. Results show the proposed method generates the minimum value in RMSE, MAE, and MAPE with 18.32, 10.66, and 5.34, respectively. This research provides a new idea to alleviate data sparsity and consider the difference of input features and offers a novel approach to solve the S-T learning tasks associated with modeling.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46072437","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

Intelligent System of Internet of Things-Oriented BIM in Project Management 面向物联网的BIM项目管理智能系统

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-06-01 DOI: 10.4018/ijitsa.323803

Jingjing Chen

{"title":"Intelligent System of Internet of Things-Oriented BIM in Project Management","authors":"Jingjing Chen","doi":"10.4018/ijitsa.323803","DOIUrl":"https://doi.org/10.4018/ijitsa.323803","url":null,"abstract":"At present, edge computing is more and more widely used in the development process of various industries. With the stable development of social industrial structure, the development scale of enterprises is gradually expanding, the project production cycle is getting longer and longer, and the project information and project elements are also getting more and more. Under the traditional project management mode, the project elements are independent from each other, the participants are difficult to interact, and the information content is relatively dispersed, which has seriously hindered the improvement of the efficiency and level of enterprise project management. The emergence of intelligent the BIM (building information modeling) project management system provides technical support for the realization of the overall project management objectives, but there are still large limitations in actual use, mainly reflected in the poor flexibility of attraction and error prone. In order to solve the dilemma of enterprise project management, based on the analysis of the characteristics of project management and the functional requirements of the system, this article proposes an intelligent system of BIM in project management oriented to the internet of things. In order to verify the effectiveness of the system, this article conducts system tests from the aspects of project management efficiency, system security, and user experience. The results show that the average intelligent system error level of internet of things-oriented BIM in project management is about 0.310. It can be seen from this result that, on the basis of internet of things technology, various project elements and information within the system have achieved effective integration and promoted the deep intelligent development of project management.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46805480","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

Early Warning of Companies' Credit Risk Based on Machine Learning 基于机器学习的企业信用风险预警

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-06-01 DOI: 10.4018/ijitsa.324067

Benyan Tan, Yujie Lin

引用次数: 0

Multilabel Classifier Chains Algorithm Based on Maximum Spanning Tree and Directed Acyclic Graph 基于最大生成树和有向无环图的多标签分类器链算法

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-06-01 DOI: 10.4018/ijitsa.324066

Wenbiao Zhao, Runxin Li, Zhenhong Shang

{"title":"Multilabel Classifier Chains Algorithm Based on Maximum Spanning Tree and Directed Acyclic Graph","authors":"Wenbiao Zhao, Runxin Li, Zhenhong Shang","doi":"10.4018/ijitsa.324066","DOIUrl":"https://doi.org/10.4018/ijitsa.324066","url":null,"abstract":"The classifier chains algorithm is aimed at solving the multilabel classification problem by composing the labels into a randomized label order. The classification effect of this algorithm depends heavily on whether the label order is optimal. To obtain a better label ordering, the authors propose a multilabel classifier chains algorithm based on a maximum spanning tree and a directed acyclic graph. The algorithm first uses Pearson's correlation coefficient to calculate the correlation between labels and constructs the maximum spanning tree of labels, then calculates the mutual decision difficulty between labels to transform the maximum spanning tree into a directed acyclic graph, and it uses topological ranking to output the optimized label ordering. Finally, the authors use the classifier chains algorithm to train and predict against this label ordering. Experimental comparisons were conducted between the proposed algorithm and other related algorithms on seven datasets, and the proposed algorithm ranked first and second in six evaluation metrics, accounting for 76.2% and 16.7%, respectively. The experimental results demonstrated the effectiveness of the proposed algorithm and affirmed its contribution in exploring and utilizing label-related information.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44095451","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

Application of Automatic Completion Algorithm of Power Professional Knowledge Graphs in View of Convolutional Neural Network 基于卷积神经网络的电力专业知识图自动完成算法的应用

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-05-23 DOI: 10.4018/ijitsa.323648

Guangqian Lu, Hui Li, Mei Zhang

引用次数: 0

Construction and Application of Power Data Operation Monitoring Platform Based on Knowledge Map Reasoning 基于知识地图推理的电力数据运行监测平台的构建与应用

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-05-23 DOI: 10.4018/ijitsa.323566

Zhao Yao, Yong Hu, Xingzhi Peng, Jiapan He, Xuming Cheng

引用次数: 0

Optimization of Cogging Torque Based on the Improved Bat Algorithm 基于改进Bat算法的齿槽转矩优化

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-05-18 DOI: 10.4018/ijitsa.323442

Wenbo Bai, Huajun Ran

{"title":"Optimization of Cogging Torque Based on the Improved Bat Algorithm","authors":"Wenbo Bai, Huajun Ran","doi":"10.4018/ijitsa.323442","DOIUrl":"https://doi.org/10.4018/ijitsa.323442","url":null,"abstract":"Permanent magnet motors have the advantages of high output torque, high efficiency, and low noise, but the cogging effect is obvious. The 24-slot 4-pole surface-mounted permanent magnet synchronous motor is taken as an example to reduce the cogging torque of permanent magnet synchronous motors. Firstly, the generation mechanism of cogging torque is analysed based on the energy method, and the pole arc coefficient, air gap length, magnetic pole eccentricity, permanent magnet thickness, and slot opening width are determined as optimisation parameters. Then, a cogging torque optimisation method is further proposed based on the Taguchi method and the response surface method, and the bat algorithm with the Lévy flight feature is applied to obtain the optimal solution for the response surface model. Finally, finite element software is used to simulate the optimal motor model. The experimental results show that the efficiency of the motor solved by optimal parameters is increased by 1.6%, the cogging torque is reduced by 82.16%, and the torque ripple is reduced by 8.2%. The optimisation of cogging torque in this paper avoids fluctuations in torque, reduces motor vibration and noise, and improves the control characteristics of the permanent magnet motors drive system, operational reliability, and low-speed performance in the motor speed control system and high accuracy positioning in the position control system.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45075282","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

Demand Forecast of Railway Transportation Logistics Supply Chain Based on Machine Learning Model 基于机器学习模型的铁路运输物流供应链需求预测

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-05-18 DOI: 10.4018/ijitsa.323441

Pengyu Wang, Yaqiong Zhang, Wanqing Guo

引用次数: 0

Prediction of Ultimate Bearing Capacity of Oil and Gas Wellbore Based on Multi-Modal Data Analysis in the Context of Machine Learning 机器学习下基于多模态数据分析的油气井筒极限承载力预测

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-05-12 DOI: 10.4018/ijitsa.323195

Qiang Li

{"title":"Prediction of Ultimate Bearing Capacity of Oil and Gas Wellbore Based on Multi-Modal Data Analysis in the Context of Machine Learning","authors":"Qiang Li","doi":"10.4018/ijitsa.323195","DOIUrl":"https://doi.org/10.4018/ijitsa.323195","url":null,"abstract":"As important research for drilling engineering, the prediction of oil and gas shaft lining conditions is changing from the traditional method based on the mechanism model to the intelligent prediction method combining the mechanism model with the data model. Therefore, this paper establishes a stacking integrated model for predicting the uniaxial compression strength (UCS) of rock based on four basic parameters that can reflect the characteristics of rock mass. At the same time, the expectation-maximation (EM) algorithm is used to optimize the hidden Markov models (HMM), and a fuzzy random model of the ultimate bearing capacity of oil and gas shaft lining is established. The uncertain distribution of main parameters of rock mass is analyzed, and the corresponding fuzzy random distribution law is obtained. The experimental results show that the stacking integration algorithm is of great help to improve the prediction effect of rock mass compressive strength. The EM-HMM model has the advantages of small error, high efficiency, and fast convergence after two fuzzy random processes. Using this algorithm is helpful to analyze the stress state and parameter response mechanism of the shaft lining, dynamically generate optimized parameters, and provide technical support for reducing the incidence of complex drilling accidents, shortening the well construction period and lowering the drilling cost.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42538598","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