Mohammad Javad Shayegan^*, Rosa Akhtari

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1251-1272, 2024, DOI:10.32604/csse.2024.052587 - 13 September 2024

Abstract After the spread of COVID-19, e-learning systems have become crucial tools in educational systems worldwide, spanning all levels of education. This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data, making it an attractive resource for predicting student performance. In this study, we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets. The stacking method was employed for modeling in this research. The proposed model utilized weak learners, including nearest neighbor, decision tree, random forest, enhanced gradient, simple Bayes, More >

Dongyang Ou, Yongjian Ren, Congfeng Jiang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2043-2067, 2024, DOI:10.32604/cmes.2023.029987 - 29 January 2024

Abstract Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents a quality of service (QoS) prediction-based scheduling model (QPSM) for co-located workloads. The performance prediction of QPSM consists of two parts: the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based… More >

Xinzheng Wang^1,2,*, Bing Guo¹, Yan Shen³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1183-1206, 2024, DOI:10.32604/cmes.2023.029552 - 17 November 2023

Abstract Predicting students’ academic achievements is an essential issue in education, which can benefit many stakeholders, for instance, students, teachers, managers, etc. Compared with online courses such as MOOCs, students’ academic-related data in the face-to-face physical teaching environment is usually sparsity, and the sample size is relatively small. It makes building models to predict students’ performance accurately in such an environment even more challenging. This paper proposes a Two-Way Neural Network (TWNN) model based on the bidirectional recurrent neural network and graph neural network to predict students’ next semester’s course performance using only their previous course More > Graphic Abstract

Yunru Wu¹, Xiangbo Liu¹, Haibo Huang^1,2,*, Yudong Wu¹, Weiping Ding^1,2, Mingliang Yang^1,2,*

Sound & Vibration, Vol.57, pp. 73-95, 2023, DOI:10.32604/sv.2023.044601 - 10 November 2023

Abstract Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH (Noise, Vibration, and Harshness). When analyzing the NVH performance of the vehicle body, the traditional SEA (Statistical Energy Analysis) simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions. In order to effectively solve these shortcomings, based on the analysis of the vehicle noise transmission path, a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established. Combined with the data-driven method, More >

Ying Bai^1,*, Xiaoti Ren², Hong Li¹

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2999-3018, 2023, DOI:10.32604/iasc.2023.040124 - 11 September 2023

Abstract The combination of the Industrial Internet of Things (IIoT) and digital twin (DT) technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance. However, conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information. The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model. In this paper, a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state. Firstly, a global real-time feedback and the dynamic adjustment mechanism… More >

Yuqin Wang^1,2,3,*, Luxiang Zhou³, Mengle Han¹, Lixiang Shen¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.9, pp. 2215-2228, 2023, DOI:10.32604/fdmp.2023.027188 - 16 May 2023

Abstract The main structural parameters of the IR100-80-100A type chemical centrifugal pump have been optimized by means of an orthogonal test approach. The centrifugal pump has been modeled using the CFturbo software, and 16 sets of orthogonal-test schemes have been defined on the basis of 4 parameters, namely, the blade number, blade outlet angle, impeller outlet diameter, and impeller outlet width. Such analysis has been used to determine the influence of each index parameter on the pump working efficiency and identify a set of optimal combinations of such parameters. The internal flow field in the centrifugal More > Graphic Abstract

Fawad Nasim^1,2,*, Muhammad Adnan Yousaf¹, Sohail Masood^1,2, Arfan Jaffar^1,2, Muhammad Rashid³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2865-2877, 2023, DOI:10.32604/iasc.2023.034258 - 15 March 2023

Abstract Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We… More >

Chen Wei-wei¹, He Wei^1,2,*, Zhu Hai-long¹, Zhou Guo-hui¹, Mu Quan-qi¹, Han Peng¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6119-6143, 2023, DOI:10.32604/cmc.2023.035743 - 28 December 2022

Abstract The prediction of processor performance has important reference significance for future processors. Both the accuracy and rationality of the prediction results are required. The hierarchical belief rule base (HBRB) can initially provide a solution to low prediction accuracy. However, the interpretability of the model and the traceability of the results still warrant further investigation. Therefore, a processor performance prediction method based on interpretable hierarchical belief rule base (HBRB-I) and global sensitivity analysis (GSA) is proposed. The method can yield more reliable prediction results. Evidence reasoning (ER) is firstly used to evaluate the historical data of More >

Liu Zhang^1,*, Yi-Fei Chen^1,2, Zi-Quan Pei¹, Jia-Wei Yuan², Nai-Qiao Tang¹

Journal on Artificial Intelligence, Vol.4, No.1, pp. 15-26, 2022, DOI:10.32604/jai.2022.027730 - 16 May 2022

Abstract Analyzing and predicting the learning behavior data of students in blended teaching can provide reference basis for teaching. Aiming at weak generalization ability of existing algorithm models in performance prediction, a BP neural network is introduced to classify and predict the grades of students in the blended teaching. L2 regularization term is added to construct the BP neural network model in order to reduce the risk of overfitting. Combined with Pearson coefficient, effective feature data are selected as the validation dataset of the model by mining the data of Chao-Xing platform. The performance of common More >

Pengcheng Liu, Ping Xiang, Qishi Zhou^*, Hai Zhang, Jiefu Tian, Misganu Demis Argaw

Journal of Renewable Materials, Vol.9, No.12, pp. 2223-2239, 2021, DOI:10.32604/jrm.2021.015544 - 22 June 2021

Abstract Bamboo is a renewable natural building material with good mechanical properties. However, due to the heterogeneity and anisotropy of bamboo stalk, a large amount of material performance testing costs are required in engineering applications. In this work, longitudinal compression, bending, longitudinal shear, longitudinal tensile, transverse compression and transverse tensile tests of bamboo materials are conducted, considering the influence of the bamboo nodes. The mechanical properties of the whole bamboo stalk with the wall thickness and outer circumference are explored. Through univariate and multiple regression analysis, the relationship between mechanical properties and wall thickness and perimeter More > Graphic Abstract