Study on Chinese spam filtering system based on Bayes algorithm by Haoran LIU, Pan DING, Changjiang GUO, Jinfeng CHANG, Jingchuang CUI

Subjects: “…Bayesian network…”
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Constraint analysis for extended dynamic fault tree by Qi-xuan WU, Jian-feng MA, Cong SUN, Shuai ZHANG, Shuang ZHANG, Tao ZHENG

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Study on Response Probability of Meteorological and Hydrological Drought Characteristics during Drought Recovery Period in Upper Hanjiang River by ZHU Fang, WANG Haiyu, YANG Shaokang, BO Huijuan

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Transcriptome analysis reveals hypoxic response key genes and modules as well as adaptive mechanism of crucian carp (Carassius auratus) gill under hypoxic stress by Mengchao Xing, Mengchao Xing, Zhen Rong, Zhen Rong, Xin Zhao, Xin Zhao, Xiaowei Gao, Xiaowei Gao, Zhiguang Hou, Lihan Zhang, Lihan Zhang, Waiho Khor, Yihuan Xu, Yihuan Xu, Li Chen, Li Chen, Chengbin Wu, Chengbin Wu

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Identifying Key Nodes and Enhancing Resilience in Grain Supply Chains Under Drought Conditions by Shuiwang Zhang, Chuansheng Zhou

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Inferring causal protein signalling networks from single‐cell data based on parallel discrete artificial bee colony algorithm by Jinduo Liu, Jihao Zhai, Junzhong Ji

Subjects: “…Bayesian network…”
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RESEARCH ON RELIABILITY ASSESSMENT METHOD OF MECHANICAL SYSTEM CONSIDERING MULTIPLE FAILURE STATES by HU QiGuo, DU ChunChao, CAO LiJie, SHENG HuiMin

Subjects: “…Interval-valued fuzzy Bayesian network…”
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Energy efficiency as a driver of the circular economy and carbon neutrality in selected countries of Southern Europe: a soft computing approach by Alma Ramčilović Jesih, Goran Šimić, Ljubiša Konatar, Zoran Brljak, Polona Šprajc

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Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features by Aiga Andrijanova, Lasma Bugovecka, Sergejs Isajevs, Donats Erts, Uldis Malinovskis, Andis Liepins

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Covid-19 Verileri için Bayes Ağlari ile Makine Öğrenmesi by Hüseyin Can Yılmaz, Serpil Aktaş

Subjects: “…bayesian networks…”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

Subjects: “…Particle Swarm Optimization, Neural Networks, Logistic Regression, Nave Bayes Classifier, Multilayer Perceptron, Support Vector Machine, BF Tree, Bayesian Networks.…”
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Economic Development Forecast of China’s General Aviation Industry by Hongqing Liao, Zhigeng Fang, Chuanhui Wang, Xiaqing Liu

“…Aiming at solving the problem of system external impact on China’s general aviation industry, combining functional theory and grey system theory, and applying Bayesian network reasoning technology, a grey Bayesian network reasoning prediction model of system impact and system control is established. …”
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An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion by Elad Katz, Wim Verleyen, Colin G. Blackmore, Michael Edward, V. Anne Smith, David J. Harrison

“…The Bayesian network separated individual and collective invading cell groups based on the morphological measurements, with the level of cell-cell contact the most discriminating morphological feature. …”
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Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance by Qi Tang, Huan Wang

“…Meanwhile, a time window is established to control the risk of AGV delay, and a data-driven Bayesian network is constructed to optimize the two-layer scheduling model of automated job shop and AGV. …”
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A Systematic Review and Network Meta-Analysis on the Efficacy of Medications in the Treatment of Chronic Idiopathic Constipation in Japan by Atsushi Nakajima, Ayako Shoji, Kinya Kokubo, Ataru Igarashi

“…We pooled data by random-effects meta-analyses and also performed a Bayesian network meta-analysis to indirectly compare data. …”
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Research of proactive complex event processing method by Shao-feng GENG, Yong-heng WANG, Ren-fa LI, Jia ZHANG

“…Based on the preliminary analysis results of the indeterminate event stream that generated by the sensors and control purpose equipment of CPS,the adaptive dynamic Bayesian network and parallel Markov decision process model were used to support the proactive complex event processing.In order to resolve the vast state space issue of Markov decision process for large CPS,states partition and reward decomposition methods were proposed to parallel the decision making process.The experimental result based on the simulation of traffic network shows that proposed method can process event stream effectively and has favorable scalability.…”
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Deep belief network-based link quality prediction for wireless sensor network by Lin-lan LIU, Jiang-bo XU, Yue LI, Zhi-yong YANG

“…After analyzing the existing link quality prediction models,a link quality prediction model for wireless sensor network was proposed,which was based on deep belief network.Support vector classification was employed to estimate link quality,so as to get link quality levels.Deep belief network was applied in extracting the features of link quality,and softmax was taken to predict the next time link quality.In different scenarios,compared with the model of link quality prediction based on logistic regression,BP neural network and Bayesian network methods,the experimental results show that the proposed prediction model achieves better precision.…”
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Attack detection method based on spatiotemporal event correlation in intranet environment by Wei SUN, Peng ZHANG, Yongquan HE, Lichao XING

“…In view of the fact that a single event as an attack detection feature leads to a higher false positive rate,an intranet attack detection method using Bayesian network model for cross-space event correlation and Kalman filter linear model for cross-temporal event correlation was proposed.Based on the method,a process query system was implemented,which can scan and correlate distributed network events according to the user's high-level process description.Experimental analysis show that the proposed method can significantly reduce the false positive rate of intranet attack detection without increasing the computational overhead.…”
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Link quality prediction model based on Gaussian process regression by Jian SHU, Manlan LIU, Yaqing SHANG, Yubin CHEN, Linlan LIU

“…Link quality is an important factor of reliable communication and the foundation of upper protocol design for wireless sensor network.Based on this,a link quality prediction model based on Gaussian process regression was proposed.It employed grey correlation algorithm to analyze correlation between link quality parameters and packet receive rate.The mean of the link quality indication and the mean of the signal-to-noise were selected as input parameters so as to reduce the computational complexity.The above parameters and packet receive rate were taken to build Gaussian process regression model with combination of covariance function,so that link quality could be predicted.In the stable and unstable scenarios,the experimental results show that the proposed model has better prediction accuracy than the one of dynamic Bayesian network prediction model.…”
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Novel Strategy to Improve the Performance of Localization in WSN by M. Vasim Babu, A. V. Ramprasad

“…In this energy consumption model we use both static and dynamic sensor nodes to monitor the optimized energy of all sensor nodes in which every sensor state can be considered as the dynamic Bayesian network. By using this method the power is assigned in terms of dynamic manner to each sensor over discrete time steps to control the graphical structure of our network. …”
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