Design and analysis of active queue management algorithm based on predictive control by WANG Ping, CHEN Hong, LU Xiao-hui

“…Model predictive control as a novel active queue management（AQM） algorithm was proposed for Internet system with large delay,called MPAQM.Considering the causality of time-delay system,the predicted output was defined.Then,the control requirement was converted to the optimal control objective,and the drop probability was obtained by solving the optimal problem.Furthermore,the delay-independent stability condition of closed-loop system was derived,which gave the guidelines how to select the parameters of MPAQM algorithm to assure the stability and fast convergence of the network system.The performances of MPAQM were evaluated through a series of simulations in NS2 under the single/multiple topology.The simulation results show that the queue length with MPAQM algorithm reaches the desired value with minimal tracking error and lower drop probability.MPAQM algorithm outperforms RED,PI and SPI-RED algorithms in terms of disturbance rejection,stability,and robustness.…”
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Complex Network Algorithm for Glossary Formation Context-Related Predictive Terms by Oleg Popov, Adrian Grosu, Sergey Kramarov

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A Model Predictive Algorithm for Active Control of Nonlinear Noise Processes by Qi-Zhi Zhang, Woon-Seng Gan, Ya-li Zhou

“…Computer simulations are carried out to compare the proposed nonlinear MPC method with the nonlinear Filter-x Least Mean Square (FXLMS) algorithm. The results showed that the convergence speed of the proposed nonlinear MPC algorithm is faster than that of nonlinear FXLMS algorithm. …”
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Genomic and algorithm-based predictive risk assessment models for benzene exposure by Minyun Jiang, Minyun Jiang, Na Cai, Na Cai, Juan Hu, Lei Han, Lei Han, Fanwei Xu, Baoli Zhu, Baoli Zhu, Baoli Zhu, Baoli Zhu, Boshen Wang

“…AimIn this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.Subject and methodsWe sourced GSE9569 and GSE21862 microarray data from the Gene Expression Omnibus. …”
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Research on Adaptive Model Predictive Control Algorithm for Remotely Operated Vehicle by ZHU Yinggu, ZHANG Dinghua, TU Shaoping, SONG Junhui

“…A mathematical simulation system including the nonlinear mathematical model of ROV, the parameter identification algorithm module and the MPC algorithm module were developed. …”
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Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process by Jong Nam Kim, Chun Bae Ma, Hyok Jo, Un Chol Han, Hyon-Tae Pak, Son Il Hong, Ri Myong Kim

“…In this paper, a new switching model predictive control algorithm that can be effectively used for the temperature control of batch polymerization process is developed and its effectiveness is verified by introducing it to industrial batch polyvinyl chloride polymerization process. …”
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Chaos Time Series Prediction Based on Membrane Optimization Algorithms by Meng Li, Liangzhong Yi, Zheng Pei, Zhisheng Gao, Hong Peng

“…This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m) and least squares support vector machine (LS-SVM) (γ,σ) by using membrane computing optimization algorithm. …”
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Predicting Bank Loan Risks Using Machine Learning Algorithms by Maan Alsaleem, Safwan Hasoon

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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

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Application of machine learning algorithms in predicting pyrolytic analysis result by Thi Nhut Suong Le, A. V. Bondarev, L. I. Bondareva, A. S. Monakova, A. V. Barshin

“…In this paper, machine learning regression algorithms are applied for predicting one of the pyrolysis parameters of extracted samples based on the pyrolytic analysis results of the extracted and non-extracted samples. …”
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Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

“…This paper analyses the suitability of several machine learning algorithms for CKD prediction in consideration of health-related parameters like age, blood pressure, and blood glucose levels. …”
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A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…However, a stacking architecture can solve this problem by combining distinct algorithms and models. This study compares the performance of traditional time series models and deep learning algorithms in malaria case prediction and explores the application value of stacking methods in the field of infectious disease prediction.…”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…This article reviews the principles and applicability of various current artificial intelligence algorithmic models for predicting antimicrobial peptides, and explores prediction models specifically designed to address the dilemma facing the application of antimicrobial peptides. …”
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Retracted: Water Quality Prediction Using Artificial Intelligence Algorithms by Applied Bionics and Biomechanics

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Predicting Quail Egg Quality Using Machine Learning Algorithms by BI Yildiz, K Eskioğlu, D Özdemir, M Akşit

“…ABSTRACT This study evaluates the effectiveness of machine learning algorithms in predicting quail egg quality based on nine key parameters, including egg weight, egg width, egg length, yolk height, yolk width, yolk weight, albumen height, albumen width, and albumen length. …”
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Dynamically Predicting the Quality of Service: Batch, Online, and Hybrid Algorithms by Ya Chen, Zhong-an Jiang

“…A general system architecture for such systems continuously collects the user-service invocation records and includes both an online training module and an offline training module for quality prediction. In addition, we introduce matrix factorization-based online and offline training algorithms based on the gradient descent algorithms and demonstrate the fitness of this online/offline algorithm framework to the proposed architecture. …”
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Machine Learning Algorithms in Predicting Prices in Volatile Cryptocurrency Markets by Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez

“…This study aims to develop a predictive model for cryptocurrency prices in highly volatile markets. …”
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Comparing text classification algorithms with n-grams for mediation prediction by Retzi Y. Lewu, Kusrini Kusrini, Ainul Yaqin

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Advancing wildfire prediction in Nepal using machine learning algorithms by Saugat Sapkota, Khagendra Prasad Joshi, Sajesh Kuikel, Dipesh Kuinkel, Biplov Bhandari, Yanhong Wu, Haijian Bing, Suresh Marahatta, Deepak Aryal, S-Y Simon Wang, Binod Pokharel

“…To improve wildfire prediction and preparedness, this study evaluated four advanced machine learning algorithms—Random Forest, Radial Basis Function Neural Network, Artificial Neural Network, and Support Vector Machine—using comprehensive dataset (2001–2023) of meteorological, topographical, anthropogenic, locational, and vegetation variables. …”
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Prediction of high-risk pregnancy based on machine learning algorithms by Xinyu Pi, Junzhi Wang, Liangliang Chu, Guochun Zhang, Wenli Zhang

“…Abstract This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. …”
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