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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An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

“…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

“…Then, using the improved model XGBoost of the Gradient Boosting Decision Tree (GBDT), the traffic is classified and predicted. The network angle distinguishes between normal traffic and abnormal Origin‐Destination (OD) flows containing LDoS attacks, thereby achieving the purpose of detecting LDoS attacks. …”
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Decision Tree Model for Rockburst Prediction Based on Microseismic Monitoring by Hongbo Zhao, Bingrui Chen, Changxing Zhu

“…In this study, a decision tree was used to extract the knowledge of rockburst from microseismic monitoring data. The predictive model of rockburst was built based on microseismic monitoring data using a decision tree algorithm. …”
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Probabilistic prediction of fatigue damage based on linear fracture mechanics by M. Krejsa, L. Koubova, J. Flodr, J. Protivinsky, Q. T. Nguyen

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Prediction of multi-type membrane proteins in human by an integrated approach. by Guohua Huang, Yuchao Zhang, Lei Chen, Ning Zhang, Tao Huang, Yu-Dong Cai

“…Although some computational tools predicting membrane protein types have been developed, most of them can only recognize one kind of type. …”
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Research on HMM based link prediction method in heterogeneous network by Rong QIAN, Jianting XU, Kejun ZHANG, Hongyu DONG, Fangyuan XING

“…In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM⁽¹⁾) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM⁽²⁾) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.…”
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Invariant set theory for predicting potential failure of antibiotic cycling by Alejandro Anderson, Matthew W. Kinahan, Alejandro H. Gonzalez, Klas Udekwu, Esteban A. Hernandez-Vargas

“…Collateral sensitivity, where resistance to one drug confers heightened sensitivity to another, offers a promising strategy for combating antimicrobial resistance, yet predicting resultant evolutionary dynamics remains a significant challenge. …”
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Prediction and optimization of struvite recovery from wastewater by machine learning by TONG Ying, JIANG Shaojian, KANG Bingyan, LENG Lijian*, LI Hailong

“…The Extreme Gradient Boosting Algorithm (XGBoost) and Random Forest (RF) models were used for single-objective and multi-objective prediction of the recovery rates of N and P, respectively. …”
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Turbofan engine health status prediction with artificial neural network by Slawomir Szrama, Tomasz Lodygowski

“… The main purpose of this study is to present the concept of the aircraft turbofan engine health status prediction with artificial neural network augmentation process. …”
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Risk prediction and analysis of gallbladder polyps with deep neural network by Kerong Yuan, Xiaofeng Zhang, Qian Yang, Xuesong Deng, Zhe Deng, Xiangyun Liao, Weixin Si

“…This algorithm utilizes the aforementioned risk factors to predict the nature of gallbladder polyps. …”
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Probabilistic prediction of fatigue damage based on linear fracture mechanics by M. Krejsa, L. Koubova, J. Flodr, J. Protivinsky, Q. T. Nguyen

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Temporal Backtracking and Multistep Delay of Traffic Speed Series Prediction by Licheng Qu, Minghao Zhang, Zhaolu Li, Wei Li

“…With a real traffic data set, the coordinate descent algorithm was employed to search and determine the optimal backtracking length of traffic sequence, and multistep delay predictions were performed to demonstrate the relationship between delay steps and prediction accuracies. …”
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Prediction of success in assisted reproductive technology with the help of morphology of the testis by N. G. Kulchenko

“…Based on the study, a diagnostic algorithm of patients with male infertility is proposed, which allows to predict the success of ART taking into account morphological changes in the testicle.Conclusion. …”
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