Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…With the development of financial technology, the traditional experience-based and single-network credit default prediction model can no longer meet the current needs. …”
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An Inference Framework of Markov Logic Network for Link Prediction in Heterogeneous Networks by Zhongbin Li, Kun Yue, Lixing Yu, Jiahui Wang

“…The presence of multiplex edges and sparse links often hampers the efficacy of link prediction (LP) tasks. By harnessing the expressive power of Markov logic network (MLN) formulations, multiplex edges can be unified to enhance LP effectiveness. …”
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Prediction of Train Arrival Delay Using Hybrid ELM-PSO Approach by Xu Bao, Yanqiu Li, Jianmin Li, Rui Shi, Xin Ding

“…Next, an ELM with one hidden layer is developed to predict train arrival delays by considering these characteristics mentioned before as input features. …”
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Modelling and Prediction of Random Delays in NCSs Using Double-Chain HMMs by Yuan Ge, Yan Zhang, Wengen Gao, Fanyong Cheng, Nuo Yu, Jincenzi Wu

“…This paper is concerned with the modelling and prediction of random delays in networked control systems. …”
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Automatic determination of the frequency behaviour of the larynx tone by the method of linear prediction by Andrzej DZIURNIKOWSKI

“…This paper presents a method of automatically tracing the frequency of the larynx tone, based on a numerical implementation of the method of linear prediction on a digital computer. It also discusses the algorithm for the practical implementation of this method, derived by the author, and presents the results obtained from the analysis of a continuous speech signal with a duration of approximately 2 seconds.…”
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The Impact of Prediction Models on Energy-Aware Resource Management in FaaS Platforms by Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto

“…Moreover, resource allocation performed through the EA-RM algorithm reduces the energy consumption by ~12-45% on average w.r.t. competitors, and is proven to be more robust w.r.t. the accuracy of the prediction model used.…”
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Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The ANN was tested on independent data and demonstrated exceptional performance, achieving 96% accuracy for effective porosity and 98% for permeability predictions in sandstone formations. This efficient algorithm eliminates the need for core sample analysis, reducing costs and time while improving prediction reliability, making it a valuable tool for subsurface characterization and resource exploration.…”
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Development and Validation of a Dynamic Prediction Model for Massive Hemorrhage in Trauma by Chengyu Guo, Maolin Tian, Minghui Gong, Fei Pan, Hui Han, Chunping Li, Tanshi Li

“…This study developed and validated a group of dynamic prediction models based on vital sign time-series data and a deep-learning algorithm to assist medical staff in the early diagnosis and dynamic prediction of a future massive hemorrhage in trauma.…”
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An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…Abstract To address the issue of serious inefficiency in the traditional manual evaluation methods of rock core integrity, a deep learning-based algorithm named IDA-RCF (Intelligent detection algorithm for Rock Core Fissure) is proposed in this paper, which realizes the automatic evaluation of rock core integrity in accordance with the fissure identification results. …”
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CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer by Manman LI, Yigang FU, Yong XIAO, Wang CHEN, Feng FENG, Guodong XU

“…Objective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). …”
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Use Self-Training Random Forest for Predicting Winter Wheat Yield by Yulin Shen, Benoît Mercatoris, Qingzhi Liu, Hongxun Yao, Zongpeng Li, Zhen Chen, Wensheng Wang

“…The effectiveness of supervised ML heavily depends on having a large, accurate, and diverse annotated dataset, which poses a challenge in applying ML for yield prediction. To address this issue, we developed a self-training random forest algorithm capable of automatically expanding the annotated dataset. …”
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Convolution of the physical point cloud for predicting the self-assembly of colloidal particles by Seunghoon Kang, Young Jin Lee, Kyung Hyun Ahn

“…This paper presents a novel algorithm for predicting the kinetic and thermodynamic pathways of colloidal systems. …”
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Fast Prediction for Roll Motion of a Damaged Ship Based on SVR by LIU Han, SU Yan, ZHANG Guoqiang

“…Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.…”
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EMUs Electrical Connector Life Prediction Based on Accelerated Degradation Data by Jie MA, Lide WANG, Chuan YUE, Ping SHEN, Ji QIU

“…Using physical model of life prediction and data processing algorithm and accelerated degradation data modeling process based on degradation distribution, the reliability and life evaluation of EMUs electrical connectors were realized. …”
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Comparison of traffic flow prediction based on AR model and BP model by Tingting ZHANG, Wuxiong ZHANG, Dong PEI, Cheng ZHAO, Han YU

“…Based on Shanghai’s traffic flow data，the performance of the two different models was compared using auto regressive（AR）model and back-propagation（BP） network model，and the corresponding prediction result was given. Research finds that both of the two models can efficiently predict the traffic data，but they have different prediction accuracy for the data of different periods. …”
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Design and Implementation of Stock Market Prediction System for Used Cars in Nigeria by A. A. Ibrahim, A. A. Alabi, O. A. Ayilara-Adewale, F. R. Olokun-Olukotun

“…Hence, the objective of this study was to design and implement a stock market price prediction system for used cars in Nigeria using machine learning techniques, the extra tree algorithm and support vector machine (SVM). …”
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Traffic prediction and load balancing based on in-band network telemetry data by ZHANG Xu, ZHAO Chenxi, FENG Chuan, WEN Ting, LIU Wei, GUO Lei

“…The control module dynamically adjusted service flow paths using SRv6 technology, based on the prediction results from the analysis module. Simulation results show that the proposed model outperforms other methods in prediction accuracy and successfully achieves congestion avoidance.…”
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Efficient Prediction of Superlattice and Anomalous Miniband Topology from Quantum Geometry by Valentin Crépel, Jennifer Cano

“…In this article, we develop a versatile and computationally inexpensive method to predict the topological properties of materials subjected to a superlattice potential by combining degenerate perturbation theory with the method of symmetry indicators. …”
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Predicting the Risk of Loneliness in Children and Adolescents: A Machine Learning Study by Jie Zhang, Xinyi Feng, Wenhe Wang, Shudan Liu, Qin Zhang, Di Wu, Qin Liu

“…Background: Loneliness is increasingly emerging as a significant public health problem in children and adolescents. Predicting loneliness and finding its risk factors in children and adolescents is lacking and necessary, and would greatly help determine intervention actions. …”
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