Report for Type 2 Bayes-Fuzzy Estimation in No-Data Problem

It is well known that the system (1 + 1) can be unequal to 2, because this system has both observation error and system error. Furthermore, we must provide our mustered service within our cool head and warm heart, where two states of nature are existing upon us. Any system is regarded as the two-dimensional variable error model. On the other hand, we consider that the fuzziness is existing in this system. Though we can usually obtain the fuzzy number from the possibility theory, it is not fuzzy but possibility, because the possibility function is as same as the likelihood function, and we can obtain the possibility measure by the maximal likelihood method (i.e. max product method proposed by Dr. Hideo Tanaka). Therefore, Fuzzy is regarded as the only one case according to Vague, which has both some state of nature in this world and another state of nature in the other world. Here, we can consider that Type 1 Vague Event in other world can be obtained by mapping and translating from Type 1 fuzzy Event in this world. We named this estimation as Type 1 Bayes-Fuzzy Estimation. When the Vague Events were abnormal (ex. under War), we need to consider that another world could exist around other world. In this case, we call it Type 2 Bayes-Fuzzy Estimation. Where Hori et al. constructed the stochastic different equation upon Type 1 Vague Events, along with the general following probabilistic introduction method from the single regression model, multi-regression model, AR model, Markov (decision) process, to the stochastic different equation. Furthermore, we showed that the system theory approach is Possibility Markov Process, and that the making decision approach is Sequential Bayes Estimation, too. After all, Type 1 Bays-Fuzzy estimation is the special case in Bayes estimation, because the pareto solutions can exist in two stochastic different equations upon Type 2 Vague Events, after we ignore one equation each other (note that this is Type 1 case), we can obtain both its system solution and its decision solution. Here, it is noted that Type 2 Vague estimation can be applied to the shallow abnormal decision problem with possibility reserved judgement. However, it is very important problem that we can have no idea for possibility reserved judgement under the deepest abnormal envelopment (ex. under War). Expect for this deepest abnormal decision problem, Bayes estimation can completely cover fuzzy estimation. In this paper, we explain our flowing study and further research object forward to this deepest abnormal decision problem.

Fuzzy multi-criteria decision-making method-based operational assessment of Chinese electricity markets

The evaluation of the electricity market is crucial for fostering market construction and development.An accurate assessment of the electricity market reveals developmental trends,identifies operational issues,and contributes to stable and healthy market growth.This study investigated the characteristics of electricity markets in different provinces and synthesized a comprehensive set of evaluation indicators to assess market effectiveness.The evaluation framework,comprising nine indicators organized into two tiers,was constructed based on three aspects:market design,market efficiency,and developmental coordination.Furthermore,a novel fuzzy multi-criteria decision-making evaluation model for electricity market performance was developed based on the Fuzzy-BWM and fuzzy COPRAS methodologies.This model aimed to ensure both accuracy and comprehensiveness in market operation assessment.Subsequently,empirical analyses were conducted on four typical provincial-level electricity markets in China.The results indicate that Guangdong’s electricity market performed best because of its effective balance of stakeholder interests and adherence to contractual integrity principles.Zhejiang and Shandong ranked second and third,respectively,whereas Sichuan exhibited the poorest market performance.Sichuan’s electricity market must be improved in terms of market design,such that market players can obtain a fairly competitive environment.The sensitivity analysis of the constructed indicators verified the effectiveness of the evaluation model proposed in this study.Finally,policy recommendations were proposed to facilitate the sustainable development of China’s electricity markets with the objective of transforming them into efficient and secure markets adaptable to the evolution of novel power systems.

Evaluation on Environment State of Breeding Area in Shuidong Bay by Using Fuzzy Comprehensive Evaluation Method

Fuzzy comprehensive evaluation method was used to develop a standard model to analyze and evaluate nearness degree of water environment quality at breeding area of Shuidong Bay in China.Results showed that certain environment contamination factors in some areas seriously exceeded the standard value and led to the whole water quality at the third class level.The measurements should be taken to promote the sustainable development of breeding area in Shuidong Bay.

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models:Taking Bohai Bay as an example

The future inundation by storm surge on coastal areas are currently ill-defined.With increasing global sealevel due to climate change,the coastal flooding by storm surge is more and more frequently,especially in coastal lowland with land subsidence.Therefore,the risk assessment of such inundation for these areas is of great significance for the sustainable socio-economic development.In this paper,the authors use Elevation-Area method and Regional Ocean Model System(ROMS)model to assess the risk of the inundation of Bohai Bay by storm surge.The simulation results of Elevation-Area method show that either a 50-year or 100-year storm surge can inundate coastal areas exceeding 8000 km^(2);the numerical simulation results based on hydrodynamics,considering ground friction and duration of the storm surge high water,show that a 50-year or 100-year storm surge can only inundate an area of over 2000 km^(2),which is far less than 8000 km^(2);while,when taking into account the land subsidence and sea level rise,the very inundation range will rapidly increase by 2050 and 2100.The storm surge will greatly impact the coastal area within about 10-30 km of the Bohai Bay,in where almost all major coastal projects are located.The prompt response to flood disaster due to storm surge is urgently needed,for which five suggestions have been proposed based on the geological background of Bohai Bay.This study may offer insight into the development of the response and adaptive plans for flooding disasters caused by storm surge.

Assessment Method of Heavy NC Machine Reliability Based on Bayes Theory

It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) results as prior information was proposed to solve the problem. A certain type of heavy NC boring and milling machine was considered as the research subject, and its reliability model was established on the basis of its functional and structural characteristics and working principle. According to the stress-intensity interference theory and the reliability model theory, the GR results of the host machine and its key components were obtained. Then the GR results were deemed as prior information to estimate the probabilistic reliability(PR) of the spindle box, the column and the host machine in the present method. The comparative studies demonstrated that the improved Bayes method was applicable in the reliability assessment of heavy NC machine tools.

Fuzzy Bayes故障诊断原理

小到一部机器,大到一个系统,在运行中出现各类故障是不可避免的。打破故障诊断传统方法的局限,建立一套能进行自动化诊断的人工智能系统,需要在深入分析故障诊断内在机理的基础上,提出一种新的设计自动化故障诊断系统的工作原理。而基于Fuzzy数学原理和Bayes定理的故障诊断原理,可适用于开发出对机械故障、系统故障及人类疾病的自动化诊断系统。

Research on Value Evaluation Method of Investment Project Based on Fuzzy Composite Real Options

Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

FLBS: Fuzzy lion Bayes system for intrusion detection in wireless communication network

An important problem in wireless communication networks (WCNs) is that they have a minimum number of resources, which leads to high-security threats. An approach to find and detect the attacks is the intrusion detection system (IDS). In this paper, the fuzzy lion Bayes system (FLBS) is proposed for intrusion detection mechanism. Initially, the data set is grouped into a number of clusters by the fuzzy clustering algorithm. Here, the Naive Bayes classifier is integrated with the lion optimization algorithm and the new lion naive Bayes (LNB) is created for optimally generating the probability measures. Then, the LNB model is applied to each data group, and the aggregated data is generated. After generating the aggregated data, the LNB model is applied to the aggregated data, and the abnormal nodes are identified based on the posterior probability function. The performance of the proposed FLBS system is evaluated using the KDD Cup 99 data and the comparative analysis is performed by the existing methods for the evaluation metrics accuracy and false acceptance rate (FAR). From the experimental results, it can be shown that the proposed system has the maximum performance, which shows the effectiveness of the proposed system in the intrusion detection.

岩土参数概率分布推断的模糊BAYES方法探讨

探讨了如何在有限的少量样本条件下，利用已有的经验和试验资料确定岩土参数的概率分布。用模糊综合评判方法与ＢＡＹＥＳ理论相结合，给出由小样本试验数据确定岩土参数的概率分布。

基于随机加权法的BAYES精度评定

从工程应用的角度出发 ,在极小现场子样条件下 ,讨论了如何利用验前信息与现场子样来对导弹的命中精度进行评定 ,将随机加权法与BAYES方法结合起来 ,提出了基于随机加权法的BAYES精度评定方法 。

Application of Fuzzy Comprehensive Evaluation Method Based on Entropy Weight Theory in Evaluation of Salt Tolerance of Cotton

[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of cotton. [Method] A sand culture experiment under salt stress of 150 mmol/L of NaCI was designed. The in- dicator weight was determined with the entropy weight fuzzy comprehensive evalu- ation method, based on the salt injury index of indicators. The salt tolerance of cotton was evaluated comprehensively. [Result] At the germination stage, the entropy and weight of salt injury index of germination energy, vigor index, hypocotyl length and fresh weight were highest, followed by germination rate and germination index, and of root length were lowest. At the seedling stage, the entropy and weight of salt injury index of plasma membrane permeability, root vigor and leaf expansion rate were highest, followed by plant height and net photosynthetic rate, and of shoot dry weight and root dry weight were lowest. The salt tolerance of cotton differed a- mong growth stages and cultivars. Among the 11 cultivars, CCRI-44 and CCRI-75 were steadily salt-tolerant at both germination and seedling stages; CCRI-17, Sumi- an 22, Sumian 15 and Dexiamianl had a stable moderate salt tolerance; while Sumian 12 and Simian 3 were steadily salt-sensitive. [Conclusion] The evaluated result was objective and exact, which indicated that this method could be used in comprehensive evaluation of salt tolerance of cotton.

边坡稳定性预测的Bayes判别分析方法及应用

边坡稳定性的分析是一个复杂的系统工程问题。基于Bayes判别分析(BDA)理论并结合工程实际,选用边坡岩体的重度黏聚力、摩擦角、边坡角、边坡高度及孔隙压力比等6个指标作为边坡稳定性预测的判别因子,建立边坡稳定性预测的Bayes判别分析模型;以32组边坡实测数据作为学习样本进行训练,建立Bayes线性判别函数;以交差确认估计法对判别准则进行评价以检验模型的优良性,以Bayes线性判别函数计算7个待判样品的Bayes判别函数值。研究表明:Bayes判别分类性能良好,与支持向量机方法有较好的一致性,且预测精度高,交差确认估计的误判率较低,为边坡稳定性预测提供了一种新思路。

基于模糊C均值聚类与Bayes判别的致密油储层分类评价

为解决常规致密油储层因缺乏岩心分析资料而难以进行储层分类评价的难题,通过优选属性参数,应用模糊C均值算法划分致密油储层最优类别,再运用Bayes判别分析法建立储层类别与常规测井属性的关系式,利用常规采油井的测井属性判别储层的类别。现场实践应用表明:利用该方法划分的鄂尔多斯盆地志丹地区长7Ⅱ^6、长7Ⅰ^2射孔砂体储层类别与试油结果一致,研究区203口井储层划分吻合率为89.7%。该研究对高效开发致密油藏具有一定的指导意义。

鱼雷可靠性评定中的 Bayes 方法

Ｂａｙｅｓ方法是在小子样产品可靠性评定中应用较多的一种方法，但产品验前分布确定得是否合理，将直接影响评定结果。在采用Ｂａｙｅｓ方法对鱼雷可靠性进行评定时，常常是将成败型分系统试验的验前分布取为β（０，０）。这种对鱼雷的成败型分系统验前分布的取法是不够科学的。本文从理论上和工程实践上说明了鱼雷产品的成败型分系统验前分布应取为β（１／２，１／２），从而给出了由分系统试验数据折合成系统试验数据的Ｂａｙｅｓ方法修正公式。

基于Bayes Monte Carlo方法的小样本模糊可靠性仿真研究

针对基于Bayes解析方法的小样本模糊可靠性评估过程中存在的先验主观性和后验复杂性缺陷,通过引入贝叶斯蒙特卡罗(Bayes Monte Carlo,BMC)方法、融合信息熵原理与加权思想,建立了小样本模糊可靠性的BMC方法基本框架,给出了基于BMC方法的小样本模糊可靠性仿真流程,设计了相应算法。采用Matlab工具实现了该算法,并对指数寿命分布的小样本模糊可靠性进行了仿真实验。实验结果表明,运用BMC方法对小样本模糊可靠性进行评估能够有效地降低Bayes方法的先验主观性和后验复杂性。

基于Bayes-GO的复杂系统可靠性评估模型

针对复杂系统可靠性评估困难问题,提出一种基于Bayes-GO方法的复杂系统可靠性评估模型。采用Bayes方法融合多源先验信息,建立单元级可靠性模型,再用GO方法综合单元级可靠性参数,获得系统可靠性模型。通过某复杂电子设备可靠性评估实例,验证模型的有效性。结果表明,该方法既有Bayes方法充分利用先验信息的优点,又兼具GO方法直观、简便的特点,在相关领域应用中具有较高的参考价值。

利用相似产品信息的成败型产品Bayes可靠性评估

在成败型产品的可靠性评估中,为提高估计精度,经常利用历史数据来确定先验分布.但在工程实际中,历史样本和样本本质上属于不同的总体,这对可靠性评估结果有着显著影响.为此,采用相似系统分析确定历史样本和样本的相似程度,将其归纳为继承因子;然后,根据历史样本信息确定产品可靠性的历史后验,基于无信息先验得到产品可靠性的更新后验;最后通过继承因子,综合历史后验和更新后验,得到产品可靠性的融合后验,并在此基础上进行可靠性推断.该方法不仅充分利用了相似产品信息,而且突出了产品的独有特性.

岩体结构面倾向参数概率分布函数改进的Bayes推断方法

三峡船闸是世界上最大的船闸。该地区断层及节理比较发育，且具有一定的随机统计性，它对岩体力学性质起重要的控制作用。为了研究节理倾向的概率分布特征，本文引入以Ｂａｙｅｓ 最小熵优度比较检验为基础的概率分布的改进Ｂａｙｅｓ 统计推断方法，基于三峡工程永久船闸节理岩体３３７３ 条结构面的实测参数，就对岩体力学性质起控制作用的各组结构面的倾向参数的概率分布进行了研究。文章最后还讨论了推断的最优分布参数，估计了结构面参数的检验误差范围。

岩石参数Bayes估计中验前样本可信度的研究

针对岩石试验属破坏性试验,不易取得大量样本数据这一特点,提出在利用验前信息对岩石力学参数进行Bayes估计时,应首先考虑验前信息的可信度。通过统计学假设检验中二类错误理论推导了正态分布下验前信息与验后信息的相容性和可信度的公式,并结合康家湾矿的岩石单轴抗压强度数据进行计算。结果表明,运用该公式计算验前信息可信度是可行的,为利用验前信息进行参数估计提供了理论依据。