The role of hypoxia-senescence co-related molecular subtypes and prognostic characteristics in hepatocellular carcinoma by Fuqing Chen, Yifan Cai, Xiangmei Chen, Changzhou Chen, Qinliang Fang, Jianming Liu, Yibin Zhang, Jianyin Zhou

“…SVM algorithm was used to classify HCC patients based on HSCRGs. …”
Get full text

Application of Big Data Technology in the EMU Fault Early Warning by WU Zhenyi

“…It uses a method of combining equipment fault mechanism and artificial intelligence algorithm to construct a fault early warning and prediction model of key components of EMU, which reflects the working status of a component with its key physical properties and identify potential faults in advance. …”
Get full text

Research on terminal switch interval based on DTL by Yufei CUI, Jinwu WEI, Siyu PAN, Rongfang ZHANG, Xiao WANG, Zixiang JIA

“…The switching frequency of users was predicted by decision tree algorithm based on the consumption information of user history and the replacement information of mobile terminals, which provided data support for the accurate marketing of mobile terminals and the stock management of users.…”
Get full text

A Fuzzy Simulation Model for Military Vehicle Mobility Assessment by Aby K. George, Harpreet Singh, Macam S. Dattathreya, Thomas J. Meitzler

“…The interest is greater in predicting the mobility for military vehicles. In this paper, authors review various definitions of mobility. …”
Get full text

Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
Get full text

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. by Anna Cichonska, Balaguru Ravikumar, Elina Parri, Sanna Timonen, Tapio Pahikkala, Antti Airola, Krister Wennerberg, Juho Rousu, Tero Aittokallio

“…Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. …”
Get full text

A Recommendation System Based on Regression Model of Three-Tier Network Architecture by Wang Bailing, Huang Junheng, Zhu Dongjie, Hou Xilu

“…The result indicates that our algorithm performs superiorly compared to traditional collaborative filtering algorithm.…”
Get full text

基于序列二次规划理论传动系统中的非对称式盘式制动器制动尖叫研究 by 鲍莉, 王俊峰, 刘振刚

“…In order to study the brake squeal of transmission disc brake,the asymmetric disk brake cooling channel concept is introduced,by SQP optimization algorithm the relevant constraints is established,the asymmetric cooling channel geometry data obtained by the optimization theory is intraduced into the brake squeal prediction model,the relevant characteristics variation rule is analyzed and the relevant model is established to verify the results. …”
Get full text

Learning Quantum Processes with Quantum Statistical Queries by Chirag Wadhwa, Mina Doosti

“…For the former, we present an efficient average-case algorithm along with a nearly matching lower bound with respect to the number of observables to be predicted. …”
Get full text

BLSTM based night-time wildfire detection from video. by Ahmet K Agirman, Kasim Tasdemir

“…To this end, a BLSTM based night-time wildfire event detection from a video algorithm is proposed. It is shown in the experiments that the proposed algorithm attains 95.15% of accuracy when tested against a wide variety of actual recordings of night-time wildfire incidents and 23.7 ms per frame detection time. …”
Get full text

Reliability Evaluation of Cryogenic Shut-Off Valve Based on Weibull Segmented Model by Yi Lu, Jian-Ming Zheng, Ting Chen

“…In order to improve the prediction accuracy of cryogenic shut-off valve failures and quantitatively analyze the distribution law of cryogenic shut-off valve failures, this study establishes a solution model based on genetic algorithm and statistics of cryogenic shut-off valve operating data, which is combined with two Weibull segmented models. …”
Get full text

Determination of the location of sonic boom by Rufin MAKAREWICZ

“…For general case (at arbitrary manoeuvring of aircraft) a procedure algorithm has been defined which permits to predict the boundary of audibility area. …”
Get full text

A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
Get full text

Machine-learning aided calibration and analysis of porous media CFD models used for rotating packed beds by Ahmed M. Alatyar, Abdallah S. Berrouk

“…The algorithm is used to improve CFD predictions of dry pressure drop in rotating packed beds (RPBs) for a wide range of operating conditions. …”
Get full text

Fuzzy logic based adaptive duty cycling for sustainability in energy harvesting sensor actor networks by Sai Krishna Mothku, Rashmi Ranjan Rout

“…In this work, current residual energy, predicted harvesting energy (for a futuristic time slot) and predicted residual energy parameters are considered as fuzzy input variables to estimate duty cycle for a sensor node. …”
Get full text

Definition of complex roots of the fourth degree algebraic equation by V. M. Ilyin

Get full text

Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

“…Seven machine learning models, including Support Virtual Machine (SVM), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Decision Tree (DT), Random Forest Classifier (RFC), Artificial Neural Network (ANN), and Gradient Boosting (GB), were trained and tested using the collected data (n = 750) to identify the most effective method for predicting depression. After rigorous analysis, Random Forest emerged as the best-performing algorithm, exhibiting remarkable accuracy (87%), precision (78%), recall (95%), and f1-score (86%). …”
Get full text

Fluid flow characteristics estimation of a new integrated bifluid/airbased photovoltaic thermal system utilizing a hybrid optimization method by Ghassan A. Bilal, Abdullateef A. Jadallah, Omayma M. Abdulmajeed, Müslüm Arıcı

“…Furthermore, combining two techniques gives the best predictions compared to actual data. The results of the comparison showed a satisfactory correspondence between the predicted and the experimental data. …”
Get full text

Research on the Exchange Rate Forecast of the Pound Sterling and the Dollar Based on Neural Networks by Chen Jiantao, Song Yining

“…During the training phase, the back-propagation algorithm is employed to reduce prediction errors, and rigorous cross-validation techniques are utilized to precisely evaluate the model's performance. …”
Get full text

Novel methods for selecting stock portfolio in conditions of uncertainty and forecasting with RR-DEA, ANFIS, FGP: A case study of Tehran stock exchange. by Mohammadmahdi Taheri, Amir Azizi, Emran Mohammadi, Abbas Saghaei

“…These selected stocks are then moved to the second stage, where the ANFIS algorithm is employed in MATLAB to predict the final closing prices and calculate the prediction error (RMSE). …”
Get full text