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 model predictive control (MPC) method and its fast optimization solution method based on operator partition quadratic programming were studied and deduced. …”
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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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PREDICTIVE CONTROL SYSTEM SYNTHESIS OF DISTRICT HEATING SYSTEM by Dobrotin S.A., Prokopchuk E.L.

Subjects: “…predictive control…”
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Explainable Predictive Factors for Inter-Agency Partnership Success by Nicola Drago, Goncalo Afonso Braz, Tullio Vardanega

“…With bootstrap sampling, instead, we computed confidence intervals. Our rating predictions were rather good. Explainable AI models achieved a Matthews Correlation Coefficient of 0.749. …”
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House Market Prediction Using Machine Learning by Nicușor-Andrei ANDREI

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Prediction of the corrosion rates of subsea pipelines via KPCA by Shiqi Xu, Changhe Huang, Hongda Zhao

Subjects: “…KPCA algorithm…”
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A congestion prediction method based on trajectory mining algorithm by Liu Dongjiang, Li Leixiao, Li Jie

“…So many traffic congestion prediction methods have been proposed. Almost all these methods are based on traffic flow prediction algorithm. …”
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Water Quality Prediction Based on Hybrid Deep Learning Algorithm by Bhagavathi Perumal, Niveditha Rajarethinam, Anusuya Devi Velusamy, Venkatesa Prabhu Sundramurthy

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A Stock Prediction Model Based on Cart and Boosting Algorithm by WANG Yu, CHEN De-yun, TANG Yuan-xin

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Research on Pressurizer Pressure Control Based on Adaptive Prediction Algorithm by Hong Qian, Yuan Yuan, Yu Wang, Gaofeng Jiang, Ting Yang

“…To tackle the problem, an adaptive predictive control method for pressurizer pressure is devised in this paper. …”
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Predicting Voluntary Auditor Change Using the Water Cycle Algorithm by Erfan Safdel, Hoda Eskandar, Hassan Yazdifar

“…Additionally, these algorithms were run 10 times to ensure the reliability of the results.ResultsIn almost all implementations and based on all 4 performance evaluation criteria, the Water Cycle Algorithm is more suitable than logistic regression for predicting auditor change. …”
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A Prediction Algorithm for Coexistence Problem in Multiple-WBAN Environment by Zilong Jin, Yoonjeong Han, Jinsung Cho, Ben Lee

“…Therefore, this paper presents a learning-based algorithm to efficiently predict the coexistence condition in a multiple-WBAN environment. …”
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Noise-tolerant Grover's algorithm via success-probability prediction by Jian Leng, Fan Yang, Xiang-Bin Wang

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Time series data aggregation algorithm with synchronous prediction for WBAN by Ru-yan WANG, Mei-ling ZHAI, Da-peng WU

“…Due to the nonlinearity and nonstationarity of the physiological data sensed by WBAN,data aggregation cannot be effectively achieved according to the time-domain trend of data.Therefore,a novel time series data aggregation algorithm with synchronous prediction was proposed.By preprocessing the original sensing data with the multi-resolution analysis,the inherent characteristics of the physiological data can be obtained to establish a light-weight synchronous prediction model at both the sensor and sink.Numerical results show that the proposed aggregation algorithm can achieve a favorable prediction precision and a low energy consumption rate by eliminating the in-network data redundancy.…”
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The Successful Prediction of Waterflooding Using a Feed-Forward Algorithm by Qunazatul Shima Batubara*, Tomi Erfando

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Slot-predicting based ALOHA algorithm for RFID anti-collision by LI Meng, QIAN Zhi-hong, ZHANG Xu, WANG Yi-jun

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Fast intra prediction algorithm applied in QS enhancement layer by WANG Da-yong1 SHU Jian2

“…A fast intra coding algorithm was proposed which was suitable for enhancement layer in quality salability.Base on the coding structure of quality scalability,our algorithm used the relationships between layers,the relationships between rate distortion and modes,and temporal and spatial relationships to predict the modes and coding order to be ap-plied,with an early termination determined by the relationships between quantization parameters and modes,residual co-efficients,and rate distortion.The experimental results show that the encoding speed of the proposed algorithm can be improved by 70%,with negligible coding loss.…”
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Time series data aggregation algorithm with synchronous prediction for WBAN by Ru-yan WANG, Mei-ling ZHAI, Da-peng WU

“…Due to the nonlinearity and nonstationarity of the physiological data sensed by WBAN,data aggregation cannot be effectively achieved according to the time-domain trend of data.Therefore,a novel time series data aggregation algorithm with synchronous prediction was proposed.By preprocessing the original sensing data with the multi-resolution analysis,the inherent characteristics of the physiological data can be obtained to establish a light-weight synchronous prediction model at both the sensor and sink.Numerical results show that the proposed aggregation algorithm can achieve a favorable prediction precision and a low energy consumption rate by eliminating the in-network data redundancy.…”
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