Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC by Hongwei Guo, Xiangsuo Fan, Lei Min

“…To address this problem, the paper proposes a Euclidean distance-based weighted prediction algorithm as an additional candidate in the merge mode. …”
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A hybrid VMD-LSTM-SVR model for landslide prediction by Nianhong Wang, Meijun Wang, Jun Zhang

“…This study employs the Long Short-Term Memory (LSTM) neural network and Support Vector Regression (SVR), combined with the Variational Mode Decomposition (VMD) algorithm, to construct predictive models. Initially, the VMD algorithm decomposes the landslide displacement time series into trend, periodic, and stochastic components. …”
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DBO-DELM Method for Predicting Rolling Forces in Cold Rolling by LI Xiaoyang, PIAO Chunhui, WANG Xuelei, ZHANG Mingzhi

“…Aiming at the problems of many assumptions, large computational errors and poor generalisation performance of the traditional rolling force prediction model, a cold rolling force prediction model (DBO-DELM) using the dung beetle optimizer algorithm (DBO) to optimise the deep extreme learning machine (DELM) is proposed. …”
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A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
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PREDICTION OF UNFAVORABLE OUTCOMES OF PREGNANCY BASED ON BIOCHEMICAL SCREENING IN TRIMESTER by I. O. Makarov, E. V. Yudina, E. I. Borovkova, I. V. Martynova, E. I. Kirpikova

“…The international and national approaches to the algorithm of carrying out of prenatal screening and conceptualization about prediction of pregnancy complications based on results of biochemical screening of serum concentrations of β-hCG and PAPP-A, are reviewed…”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…In this research, several machine learning predictive models based on extra trees, decision tree, support vector machine, random forest, multilayer perceptron artificial neural network, K-nearest neighbors, convolutional neural network, ensemble learning, and adaptive boosting using a dataset gathered from a coke plant are developed to predict CRI. …”
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Predicting carbohydrate quality in a global database of packaged foods by Eric Antoine Scuccimarra, Alexandre Arnaud, Marie Tassy, Marie Tassy, Kim-Anne Lê, Fabio Mainardi

“…Knowledge of specific carbohydrate in packaged food, such as added and free sugars, could help further investigate this link, however this information is generally not available.ObjectiveTo develop an algorithm to predict the content of free sugars in a global database of packaged foods and beverages; and test the applicability of the algorithm to assess carbohydrate quality in packaged food products from different countries and monitor the evolution over time. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…In comparison to six alternative models, the TBESO-BP model demonstrates superior accuracy and lower error values.DiscussionThe TBESO-BP model emerges as a precise tool for predicting subclinical mastitis in dairy cows. The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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Study on AdaBoost-based link quality prediction mechanism by Jian SHU, Man-lan LIU, Wei ZHENG

“…The link quality was vulnerable to the complexity environment in wireless sensor network.Obtaining link quality information in advance could reduce energy consumption of nodes.After analyzing the existing link quality prediction methods,AdaBoost-based link quality prediction mechanism was put forward.Link quality samples in deferent scenarios were collected.Density-based unsupervised clustering algorithm was employed to classify training samples into deferent link quality levels.The AdaBoost with SVM-based component classifiers was adopted to build link quality prediction mechanism.Experimental results show that the proposed mechanism has better prediction precision.…”
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A speech compression method without utilizing signal prediction by Ikuo Matsuo, Kazuo Ueda, Yoshitaka Nakajima

“…Previous speech compression methods for practical purposes had been based on signal prediction, taking the auditory functions into account but overlooking features specific to speech signals. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…To further refine the predictive model, three feature selection methods—successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA)—were assessed. …”
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A SVM Based Spectrum Prediction Scheme for Cognitive Radio by Yuan Xu, Huaxiang Lu, Xu Chen

“…The results show that by avoiding invalid prediction, the spectrum utilization can also be improved, and the forecasting accuracy is better than model based on back propagation（BP）, thus the proposed algorithm is practicable and flexible for spectrum prediction in cognitive radio.…”
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Prediction and modeling of connectivity probability in vehicular Ad Hoc networks by Huimin WANG, Haitao ZHAO

“…Recently，with the rapid development of vehicular communication technology，IoV（internet of vehicles）as one of the applications of IoT（internet of things），is attracting more and more attention as well as its basic applications.The algorithm of predicting the connectivity probability based on highway model was proposed.Also，the joint distribution of vehicles on highway was studied，and the equation calculating the boundaries of connectivity probability on one road segment was analyzed quantitatively.The diagram presenting the relationship between the connectivity probability on one road segment and the average number of vehicles in each tuple was depicted by Rstudio.As a consequence，the model of connectivity probability on one path was achieved by calculating the products of the connectivity probability on all road segments along one path.The analysis result shows that the connectivity probability on one path can be improved by increasing the communication range or the density of vehicles.…”
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Prediction of Blast Crushing Lumpiness Based on CPO-BP Modeling by Xuebin Xie, Chuanqi Huang

“…Currently, the central task of predicting rock fragmentation is becoming increasingly important in the field of rock mechanics and engineering blasting. …”
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LAPM: The Location Aware Prediction Model in Human Sensing Systems by Ruiyun Yu, Pengfei Wang, Shiyang Liao

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Corrosion area detection and depth prediction using machine learning by Eun-Young Son, Dayeon Jeong, Min-Jae Oh

“…Four different color maps and regression algorithm were used to predict corrosion depths and their performance was compared. …”
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TCN-GRU Based on Attention Mechanism for Solar Irradiance Prediction by Zhi Rao, Zaimin Yang, Xiongping Yang, Jiaming Li, Wenchuan Meng, Zhichu Wei

“…The global horizontal irradiance (GHI) is the most important metric for evaluating solar resources. The accurate prediction of GHI is of great significance for effectively assessing solar energy resources and selecting photovoltaic power stations. …”
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A Prediction of Solar Cycle Maxima Using Visibility Graphs by Eduardo Flández, Víctor Muñoz

“…We apply a complex network approach to analyze the time series of five solar parameters, and propose a strategy to predict the number of sunspots for the next solar maximum, and when this maximum will occur. …”
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Usage of Neural Network to Predict Aluminium Oxide Layer Thickness by Peter Michal, Alena Vagaská, Miroslav Gombár, Ján Kmec, Emil Spišák, Daniel Kučerka

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PREDICTION AND DAMAGE ANALYSIS OF THE POSTBUCKLING FOR MULTI-SPAR COMPOSITE BOX by YUAN Fei, CHAI YaNan, ZHANG AYing

“…At last,a good agreement between tests and numerical prediction was observed.…”
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