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Visual detection of rice rows based on bayesian decision theory and robust regression least squares method

International Journal of Agricultural and Biological Engineering 2021年第1期14卷 199-206页

作者： Jing He Ying Zang Xiwen Luo Runmao Zhao Jie He Jinkang Jiao Key Laboratory of Key Technology on Agricultural Machine and Equipment Ministry of EducationSouth China Agricultural UniversityGuangzhou 510642China

Paddy field management is complicated and labor intensive.Correct row detection is important to automatically track rice rows.In this study,a novel method was proposed for accurate rice row recognition in paddy field transplanted by machine before the disappearance of row information.Firstly,bayesian decision theory based on the minimum error was used to classify the period of collected images into three periods(T1:0-7 d;T2:7-28 d;T3:28-45 d),and resulting in the correct recognition rate was 97.03%.Moreover,secondary clustering of feature points was proposed,which can solve some problems such as row breaking and tilting.Then,the robust regression least squares method(RRLSM)for linear fitting was proposed to fit rice rows to effectively eliminate interference by outliers.Finally,a credibility analysis of connected region markers was proposed to evaluate the accuracy of fitting lines.When the threshold of credibility was set at 40%,the correct recognition rate of fitting lines was 96.32%.The result showed that the method can effectively solve the problems caused by the presence of duckweed,high-density inter-row weeds,broken rows,tilting(±60°),wind and overlap.

关键词： rice rows detection bayesian decision theory clustering RRLSM credibility analysis automatic tracking

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A Receiver-Forwarding decision Scheme Based on bayesian for NDN-VANET

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China Communications 2020年第8期17卷 106-120页

作者： Xian Guo Yuxi Chen Laicheng Cao Di Zhang Yongbo Jiang School of Computer and Communication Lanzhou University of TechnologyLanzhou 730050China

Named Data Network(NDN) has caused wide concerns in VANET community because NDN uses a content-centric mechanism that naming content rather than the host. However, integrating NDN into VANET(NDN-VANET) also faces several challenges including consumer/provider mobile, broadcast storm problem and so on. In this paper, we propose a bayesian-based Receiver Forwarding decision(BRFD) scheme to mitigate the broadcast storm problem incurred by interest packets in NDN-VANET. In the BRFD, vehicles received an interest packet are required to make forwarding decisions based on bayesian decision theory according to current network conditions obtained by neighbor interaction. However, the receiver-forwarding decision in BRFD can also cause a conflict issue because multiple vehicles forward copies of the same packet at the same time. So a back-off mechanism is introduced in BRFD. Experimental results show that the BRFD algorithm has better performance in several aspects in contrast to probability-based forwarding scheme and "bread crumb" routing.

关键词： named-data networking content routing bayesian decision theory broadcast storm VANET

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Optimal procurement strategy of fresh produce retailer under stochastic product qualification and market demand

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Journal of Control and decision 2021年第2期8卷 192-200页

作者： Zhouyang Liang Hongwei Liu Meihua Zuo Hui Zhu Yonghua Zuo School of Management Guangdong University of TechnologyGuangzhouPeople’s Republic of China School of Architecture and Civil Engineering Huizhou UniversityHuizhouPeople’s Republic of China School of Management Guangzhou UniversityGuangzhouPeople’s Republic of China School of Mathematics and Information Science Jiangxi Normal UniversityNanchangPeople’s Republic of China Jiangxi Institute of Economic Development NanchangPeople’s Republic of China

Consider an optimal procurement strategy for fresh produce,which is a type of perishable product.Due to the different quality provided by each manufacturer,the fresh produce qualification rates are dissimilar.Simultaneously,consumers demand is influenced by the freshness and price of products,as a result,the demand in the market is not fixed.In this scenario,how a particular retailer should develop an optimal procurement strategy will be a core issue in supply chain management.In order to address the above questions,the bayesian approach is adopted to explore retailer optimal procurement strategies with uncertainty about product supply and market demand.Finally,simulation data are used to analyse the results of the proposed model and expected non-random model to illustrate the validity and feasibility of the proposed model.

关键词： Fresh produce optimal procurement strategy stochastic product qualification uncertainty of supply and demand bayesian decision theory

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An Analysis of the Value of Additional Information Provided by Water Quality Measurement Network

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Journal of Water Resource and Protection 2016年第8期8卷 767-776页

作者： François Destandau Amadou Pascal Diop GESTE UMR MA 8101 Engees-Irstea Strasbourg France

European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.

关键词： bayesian decision theory Eutrophication Value of Information Water Quality Monitoring Network Water Resource Management

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基于敌意风险分析方法的多阶段反恐设备选址模型

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管理科学 2020年第11期

作者：刘思马良张惠珍

恐怖袭击一直是人类安全的重要威胁之一。随着当前恐怖袭击在全球的频发，对反恐问题的研究更加急迫。针对反恐设施选址问题，考虑资源分配的多阶段性以及动态性，根据贝叶斯决策理论和序贯博弈思想，构建了多阶段反恐设施的敌意风险分... 详细信息

恐怖袭击一直是人类安全的重要威胁之一。随着当前恐怖袭击在全球的频发，对反恐问题的研究更加急迫。针对反恐设施选址问题，考虑资源分配的多阶段性以及动态性，根据贝叶斯决策理论和序贯博弈思想，构建了多阶段反恐设施的敌意风险分析决策模型。讨论在城市多个设施点离散选址的不同情况下，通过预防性和修复性的资源分配将恐怖袭击的损失降低到最小。以上海市区县网络为例进行编程仿真测试，结果表明，模型可给出不同给定资源设定下的最优选址方案，是一种有效并切实可行的分析方法。

关键词：反恐设备选址敌意风险分析贝叶斯决策理论多阶段优化理论　　anti-terrorist facilities location adversarial risk analysis bayesian decision theory multi-stage optimizations

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