Prediction of rolling bearing performance degradation based on whale optimization algorithm and backpropagation model by Jingyue Wang, Yuntong Han, Haotian Wang, Jianming Ding, Cai Yi

“…The dissertation proposes a prediction model that enhances the BP (Backpropagation) neural network using the WOA (Whale Optimization Algorithm) to address the issue of local convergence during prediction. …”
Get full text

Application of machine learning algorithm for prediction of abortion among reproductive age women in Ethiopia by Angwach Abrham Asnake, Alemayehu Kasu Gebrehana, Hiwot Altaye Asebe, Beminate Lemma Seifu, Bezawit Melak Fente, Meklit Melaku Bezie, Mamaru Melkam, Sintayehu Simie Tsega, Yohannes Mekuria Negussie, Zufan Alamrie Asmare

“…Therefore, this study employed machine learning algorithms to predict abortion in Ethiopia and identify its predictors using nationally representative data. …”
Get full text

Constructing and Predicting Solutions for Different Families of Partial Differential Equations: A Reliable Algorithm by Mubashir Qayyum, Amna Khan

“…In this manuscript, a new approach based on the generalized Taylor series and residual function is proposed to predict and analyze Buckmaster and KdV type models. …”
Get full text

Adaptive random early detection algorithm based on network traffic level grade prediction by Debin WEI, Chengsheng PAN, Li YANG, Zuoren YAN

“…In view of the problem that the calculation of average queue length and maximum packet drop probability in random early detection algorithm and its variants reflect the changes of network traffic slowly, an adaptive random early detection algorithm based on network traffic level grade prediction was proposed.Based on the statistical characteristics of self-similar network traffic, the transition probability table of network traffic level grade was established, and a grade prediction method of self-similar network traffic level with low complexity and high accuracy was proposed.Furthermore, the prediction results were applied to calculate the average queue length in equal interval and adjust the maximum packet drop probability.Under the condition of fixed and variable bottleneck link capacity, it is found that regardless of the degree of self-similarity of network traffic, the proposed algorithm can improve the throughput and packet loss rate, especially when the Hurst parameter is large and the traffic is light.…”
Get full text

Green Ground: Construction and Demolition Waste Prediction Using a Deep Learning Algorithm by Wadha N. Alsheddi, Shahad E. Aljayan, Asma Z. Alshehri, Manar F. Alenzi, Norah M. Alnaim, Maryam M. Alshammari, Nouf K. AL-Saleem, Abdulaziz I. Almulhim

“…Different types of waste lack an efficient and accurate method for classification, especially in cases that require the rapid processing of materials. A deep learning prediction model based on a convolutional neural network algorithm was developed to classify and predict the types of construction and demolition waste (CDW). …”
Get full text

Traffic Prediction of Space-Integrated-Ground Information Network Based on Improved LSTM Algorithm by Chengsheng PAN, Yufu WANG, Li YANG

“…The space-integrated-ground information network is easy to interrupt and the traffi c fl uctuation is not stable due to the problems of high traffi c burst and topological time-varying, which makes the traffi c prediction diffi cult much higher than the ground.In order to solve this problem, an improved LSTM algorithm was put forward.Firstly, the traffi c autocorrelation was judged by analyzd the infl uence of the lag variable of traffi c sequence on the predicted value; Secondly, the noise and breakpoint of the training set were eliminated by replacing the interruption with the predicted value; Finally, Dropout algorithm was used to reduce the impact of noise and neural network over fi tting, and accurately predict the traffi c data of the integrated intelligent network.The simulation results showed that in OPNET simulation environment, compared with other algorithms, the accuracy of this algorithm was improved by 59.21%, and the training speed of the algorithm was improved by 11.11%, which could provide eff ective data support for the overall scheduling of the integrated intelligent network.…”
Get full text

Prediction model of laparoendoscopic single-site surgery in gynecology using machine learning algorithm by Jun Ma, Jiani Yang, Shanshan Cheng, Yue Jin, Nan Zhang, Chao Wang, Yu Wang

Get full text

An Intelligent Trajectory Prediction Algorithm for Hypersonic Glide Targets Based on Maneuver Mode Identification by Mingjie Li, Chijun Zhou, Lei Shao, Humin Lei

“…To improve the prediction precision for hypersonic glide targets, based on the analysis of the target’s maneuver characteristic, an intelligent trajectory prediction algorithm based on the maneuver mode identification is proposed in this paper. …”
Get full text

Algorithm of calculation of predicted concentration (PEC) for evaluation of the environmental risk of veterinary medicinal products by Viviana Ciuca, V. V. Safta, Romeo Teodor CRISTINA

“…The paper presents an algorithm for calculating predictable concentrations for environmental factors: soil, water, sediment required for environmental risk assessment of veterinary medicinal products. …”
Get full text

Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete by Muhammad Izhar Shah, Shazim Ali Memon, Muhammad Sohaib Khan Niazi, Muhammad Nasir Amin, Fahid Aslam, Muhammad Faisal Javed

Get full text

Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

Subjects: Get full text

Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model by Hewu Kuang

“…A genetic algorithm BP neural network (GA-BP) optimized by the genetic algorithm is used to shorten the running time of the algorithm and improve the prediction accuracy, but it is easy to fall into local solution. …”
Get full text

An improved algorithm for prediction of vehicle trajectories using short-term goal-driven network by Abdalla Tawfik, Zaki Nossair, Roaa Mubarak

“…Conclusion This article presents an improved algorithm for predicting vehicle trajectories using short-term goals. …”
Get full text

New Energy Regional Power Prediction Algorithm Based on Statistical Upscaling in Ningbo Region by Wei WANG, Bo WANG, Jun ZHANG, Chunliang LU, Xu HE

Subjects: Get full text

A Research Approach to Port Information Security Link Prediction Based on HWA Algorithm by Zhixin Xia, Zhangqi Zheng, Lexin Bai, Xiaolei Yang, Yongshan Liu

“…However, most of the existing link prediction algorithms rely on the node information of the graph structure, which is not applicable in some graph structure data involving privacy. …”
Get full text

Prediction of drug target interaction based on under sampling strategy and random forest algorithm. by Feng Chen, Zhigang Zhao, Zheng Ren, Kun Lu, Yang Yu, Wenyan Wang

Get full text

Retracted: Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Journal of Control Science and Engineering

Get full text

Dynamics of link formation in networks structured on the basis of predictive terms by S. O. Kramarov, O. R. Popov, I. E. Dzhariev, E. A. Petrov

“…In order to model and analyze the information conductivity of complex networks having an irregular structure, it is possible to use percolation theory methods known in solid-state physics to quantify how close the given network is to a percolation transition, and thus to form a prediction model. Thus, the object of the study comprises international information networks structured on the basis of dictionaries of model predictive terms thematically related to cutting-edge information technologies.Methods. …”
Get full text

Complexity Reduction in the Use of Evolutionary Algorithms to Function Optimization: A Variable Reduction Strategy by Guohua Wu, Witold Pedrycz, Haifeng Li, Dishan Qiu, Manhao Ma, Jin Liu

“…Discovering and utilizing problem domain knowledge is a promising direction towards improving the efficiency of evolutionary algorithms (EAs) when solving optimization problems. …”
Get full text

Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

Subjects: “…Energy consumption prediction…”
Get full text