Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the precondition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model. Key words One-wheel car model - Active suspension system - Single input rule modules fuzzy reasoning - Pneumatic actuator - Disturbance observer Document code A CLC number TH16

COMPUTER-AIDED BLOCK ASSEMBLY PROCESS PLANNING IN SHIPBUILD-ING BASED ON RULE-REASONING

Computer-aided block assembly process planning based on rule-reasoning are developed in order to improve the assembly efficiency and implement the automated block assembly process planning generation in shipbuilding. First, weighted directed liaison graph （WDLG） is proposed to represent the model of block assembly process according to the characteristics of assembly relation, and edge list （EL） is used to describe assembly sequences. Shapes and assembly attributes of block parts are analyzed to determine the assembly position and matched parts of parts used frequently. Then, a series of assembly rules are generalized, and assembly sequences for block are obtained by means of rule reasoning. Final, a prototype system of computer-aided block assembly process planning is built. The system has been tested on actual block, and the results were found to be quite efficiency. Meanwhile, the fundament for the automation of block assembly process generation and integration with other systems is established.

Alzheimer’s Disease Diagnosis Based on a Semantic Rule-Based Modeling and Reasoning Approach

Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.

Study on Occurrence Rule, Reason and Defense Measures of the Thunderstorm in Liaocheng in the Past 50 Years

[ Objective] The research aimed to study occurrence rule, reason and defense measures of the thunderstorm in Liaocheng in the past 50 years. [Method] By using meteorological observation records at 8 observatories of Uaocheng during 1963 -2012, occurrence rule of the thunderstorm was studied. Occurrence reason and defense measures were also analyzed. [ Result] Annual thunderstorm days presented decreasing trend in Liaocheng. The earliest thunderstorm occurred in February, while the latest thunderstorm occurred in November. Thunderstorm mainly appeared in June, July and August, which occupied 77.6% of that in whole year. Thunderstorm days among each county had small difference. Thunderstorm days in Dong＇e County reached the minimum, which was related to local underlying surface. Occurrence reason of the thunderstorm was analyzed from objective and subjective aspects. By combining the actual situation of Liaocheng, corresponding prevention countermeasures were put forward. [Conclusion] The research could provide reference basis for thunderstorm disaster prevention and reduction in Liaocheng.

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.

A GENERALIZATION OF SIMPSON'S RULE

Let TA(f)=integral form n= to 1/2(P_~n(x) + P_b^n(x))dx and let TM(f)=integral form n= to P_((+b)/2)^(n+1)(x)dx, where P_c^n denotes the Taylor polynomial to f at c of order n, where n is even. TA and TM are reach generalizations of the Trapezoidal rule and the midpoint rule, respectively. and are each exact for all polynomial of degree ≤n+1. We let L(f) = αTM(f) + (1-α)TA(f), where α =(2^(n+1)(n+1))/(2^(n+1)(n+1)+1), to obtain a numerical integration rule L which is exact for all polynomials of degree≤n+3 (see Theorem l). The case n = 0 is just the classicol Simpson's rule. We analyze in some detail the case n=2, where our formulae appear to be new. By replacing P_(+b)/2)^(n+1)(x) by the Hermite cabic interpolant at a and b. we obtain some known formulae by a different ap- proach (see [1] and [2]). Finally we discuss some nonlinear numerical integration rules obtained by taking piecewise polynomials of odd degree, each piece being the Taylor polynomial off at a and b. respectively. Of course all of our formulae can be compounded over subintervals of [a, b].

A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

Prediction systems are an important aspect of intelligent decisions.In engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accuracy of the model.The belief rule base(BRB)can implement nonlinear modeling and express a variety of uncertain information,including fuzziness,ignorance,randomness,etc.However,the BRB system also has two main problems:Firstly,modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy.Secondly,interpretability is not considered in the optimization process of current research,resulting in the destruction of the interpretability of BRB.To balance the accuracy and interpretability of the model,a self-growth belief rule basewith interpretability constraints(SBRB-I)is proposed.The reasoning process of the SBRB-I model is based on the evidence reasoning(ER)approach.Moreover,the self-growth learning strategy ensures effective cooperation between the datadriven model and the expert system.A case study showed that the accuracy and interpretability of the model could be guaranteed.The SBRB-I model has good application prospects in prediction systems.

Combining the Rule of Law with the Rule of Morality——General Secretary Xi Jinping's Important Discourse on the Relationship Between the Rule of Law and Rule by Virtue

Key points:Throughout the ages,rule of law has been an indispensable means of governing a state.However,as General Secretary Xi Jinping has pointed out,it is not enough to govern a state by the rule of law

A Processor Performance Prediction Method Based on Interpretable Hierarchical Belief Rule Base and Sensitivity Analysis

The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the parameters.Furthermore, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.

行贿犯罪案件的司法证明问题——对《刑法修正案(十二)》的证据法思考

《刑法修正案(十二)》体现了“受贿行贿一起查”的精神,但是行贿犯罪案件的无被害人犯罪、无可勘验的犯罪现场和大多数案件无目击证人的“三无”特点,决定了行贿案件的司法证明面临较大难题:一对一证据、主要依靠言词证据定案、非法证据较难排除、司法证明错误难以被检验、受贿案件的事实认定对行贿案件具有较强的证明力等五个方面。缓解证明困难,主要从11个方面进行论述:一是注重收集《刑法修正案(十二)》规定的行贿犯罪“从重”处罚的证据;二是利用认罪认罚提供的制度空间,对行贿人进行激励,换取其认罪认罚;三是注重收集客观化证据;四是对“再生证据”的创造和运用;五是注意录像固定言词证据;六是关键证人应当出庭作证,其证言内容须接受法庭检验;七是行贿人和受贿人均予否认情况下的事实认定问题;八是行贿人与受贿人供述不一致情况下的事实认定问题;九是行贿人翻供的事实认定问题;十是对行贿犯罪案件不能适用推定降低证明标准,受贿案件证明中运用的是推理而非推定;十一是经验法则在行贿案件证明中的运用问题。

形式背景上近似推理生成决策蕴涵研究

基于形式背景获取决策蕴涵、概念规则等知识是数据分析、机器学习的重要研究内容之一.首先,利用属性逻辑语义对决策蕴涵的特性进行刻画.其次,在经典二值逻辑框架下分析决策蕴涵、概念规则的基于全蕴涵三I推理思想及分离规则(Modus ponens,MP)和逆分离规则(Modus tonens,MT)的近似推理模式的特征,证明决策蕴涵的MP、MT近似推理结论是决策蕴涵,概念规则的MP、MT近似推理结论是概念规则等结论.引进属性逻辑公式的伪距离,在属性逻辑伪距离空间中分析推理对象范围参数变化对决策蕴涵MP、MT近似推理结论的影响.最后,提出若干通过MP、MT近似推理生成决策蕴涵、概念规则及拟决策蕴涵的模式和方法,数值实验验证了所提方法的有效性.

刑事案件事实认定中经验法则的运用

经验法则是证据评价的依据、建立证据与事实之间联系的桥梁以及事实认定合理性的检验标准,在刑事案件事实认定中经验法则的运用不可或缺。经验法则的适当选取是其规范运用的前提和基础,对于指向一致的经验法则应以盖然性程度为选取的基准,而内容迥异的经验法则则以具体条件的符合性为选取标准。裁判文书应当展示经验法则的内容,并结合案件的事实与证据论证经验法则选取的准确性与运用的合理性;对于控辩双方援引的经验法则,裁判文书应区别情况选择回应的方式,以增强裁判结论的正当性。对于经验法则运用的错误,可以通过启动第二审程序、审判监督程序实现救济。经验法则的规范运用有赖于控辩双方运用经验法则的公开与论辩、人民陪审员制度功能的充分发挥、直接审理原则的彻底贯彻等程序支撑规则。

司法裁判如何安置“社会命题”?

司法裁判中的法律论证要同时运用“规则命题”和“社会命题”。社会命题既能够作为裁判理由增强判决的说服力,又能够成为裁判依据的内容辅助发挥依法裁判的功能。按照说理效果的不同,可区分出法官有强法定义务援引的社会命题,法官有弱法定义务参照的社会命题,以及法官仅有道德义务去参考的社会命题。不同类型的社会命题与规则命题在法律论证的外部证成层面呈现不同的结构关联:一方面,社会命题可以通过实质理由、解释依据或替补性法源的方式与规则命题相融合;另一方面,社会命题也可能与规则命题发生冲突,在依规则裁判优先的前提下通过设定差异化的论证负担来创制例外。由此,社会命题与规则命题共同致力于实现司法裁判的“二阶正确性”。

庆历新政失败的主要原因:士大夫与天子“共治天下”的破裂

庆历新政是宋朝士大夫与天子“共治天下”的一次可贵实践。其失败的主要原因,不是由于保守派势力强大,或由于党争,而是由于范仲淹、富弼等士大夫与宋仁宗“共治天下”的破裂。具体表现在宋仁宗认为范仲淹、富弼等士大夫是朋党,结党营私,朋比为奸;认为范仲淹“密请建立皇太弟侄”,捕风捉影地怀疑范仲淹、富弼等士大夫“欲谋废立”,企图废黜仁宗,另立皇帝;捕风捉影地怀疑范仲淹、富弼等士大夫勾结契丹和登、莱金坑无赖凶恶数万人,起兵叛乱,直接对仁宗的皇位和专制独裁统治构成极大威胁。如此,士大夫与天子“共治天下”必然破裂,宋仁宗不再支持范仲淹、富弼等士大夫实施庆历新政,庆历新政必然失败。

数据抓取行为的正当性判断——反思实质性替代规则

实质性替代规则经过十余年的发展,已经成为判断数据抓取行为是否正当的基本规则之一。但是,这一从司法审判经验中发展出来的规则具有误导性,特别是该规则经过抽象而进入到各种规范性文件中时,这一问题尤其显著。实质性替代规则本质上是对同业竞争、直接竞争关系的强调,这不仅和反不正当竞争法弱化竞争关系的趋势相悖,也没有对行为的正当性有充分说明。实际上,数据抓取行为的本质是对他人成果的利用,在肯定可以适当抓取的前提下,正当性的基础应当以是否超越合理限度为标准;这需要在个案中进行判断,充分考虑抓取数据的数量、数据类型以及抓取行为造成的运维成本等因素。

基于逻辑规则的图谱推理在烟草生产工艺防差错中的应用

文章研究了基于逻辑规则的图谱推理在烟草生产工艺防差错中的应用。通过挖掘烟草生产工艺中用户的操作习惯、设备的控制逻辑特性、生产设备的属性、产品工艺风险点的属性以及生产设备控制逻辑和工艺事故之间的关系等已有信息,进行调查并建立逻辑规则。结合实际案例分析,验证了该方法的有效性和实用性,其支持提高工艺防差错识别的速度和精度。研究结果对于提高烟草生产工艺的稳定性和可靠性具有重要意义,并为其他类似行业的防差错提供了有益的参考。

零件加工隐性工艺知识获取方法研究

随着制造业数字化工艺的深入应用,如何高效利用积累的工艺知识,已成为提升工艺设计效率与质量的关键,然而隐性工艺知识却存在难以获取、描述与转化的技术瓶颈,严重阻碍智能化工艺设计模式推广。为此,提出了一种复杂零件加工的隐性工艺知识获取方法。首先,利用等宽法对结构化工艺数据进行离散化处理,构建基于文本挖掘的隐性工艺知识获取流程,并通过产生式规则对隐性工艺知识表达;然后,基于案例推理和规则推理融合的知识推理方法,并采用最近邻算法实现隐性工艺知识的识别;最后,以船用柴油机缸盖类复杂加工零件为验证对象,对加工隐性工艺知识获取方法进行了有效验证。

一阶逻辑定理证明器中的无效子句删除策略

在一阶逻辑定理证明器中,子句预处理是不可或缺的步骤,而子句的消去规则是预处理中极其重要的部分。传统的基于纯文字规则的子句消去方法在理论上存在子句删除过多的问题,在算法实现上又存在子句删除不充分的情况。为了提高子句删除的精确率,在理论上,基于纯文字规则对子句进行再分类。第一类称为无效子句,该类子句不能通过等词替换与某个子句形成互补对,此类子句应完全删除;第二类为相对无效子句,该类子句无法与当前子句集中的子句形成互补对,但能进行等词替换,此类子句应在参与演绎后综合考虑是否删除。在算法实现中,考虑到子句的消去应是动态的过程,当前消去的子句会影响已判断的子句的无效性,提出一种用于判定子句无效性的递归遍历算法。将上述子句约简规则应用于证明器CSE1.5(Contradiction Separation Extension 1.5)中,以2019—2022的CADE(Conference on Automated DEduction)自动定理证明(ATP)系统竞赛中一阶逻辑问题组为测试对象。在300 s内,应用所提算法的CSE1.5_IC比原始CSE1.5总共多证明了27个问题。在两个版本证明器共同证明的所有FNE(FOF theorems without Equality)测试例中,CSE1.5_IC比CSE1.5平均每个问题多约简了28个子句,平均求解时间减少了7.07 s。实验结果表明,所提无效子句约简算法是一种有效的预处理方式,能够提高一阶逻辑子句集的约简精确率,同时能够提高自动定理证明器的证明能力和缩短证明时间。

基于知识图谱的网络攻击预测方法研究及应用

针对网络攻击知识图谱,同时引入了时序信息,提出一种基于知识图谱的网络攻击预测方案,并对其进行应用。通过对网络攻击知识图谱进行规则学习和应用,能够有效地得到网络攻击事件预测结果,为网络安全运维人员提供决策支持。以企业提供的网络安全运维知识图谱为例,将文中研究的方法应用到企业安全检测系统,结果证明该方法具有充分的准确性和可行性,同时为后续研究提供了思路。

三级审核肠外营养处方规则的建立和效果评价

目的:通过建立药师三级审核肠外营养医嘱规则,提高肠外营养医嘱合格率,促进肠外营养合理、规范的使用。方法:不同岗位药师全员参与三个审核层级的肠外营养医嘱人工审核干预模式,建立标准化、简单化的肠外营养审核规则,降低审核难度,提高审核效率。结果:实施后,肠外营养医嘱合格率由71.09%提高到95.59%,其中工业化多腔袋合格率达到100%。肠外营养成分单纯性、阳离子浓度、糖脂比、热氮比、给药途径等有明显改善。结论:药师参与三级审核肠外营养模式,可降低单一层级审核风险,促进不同岗位的药师联动,提高审核准确性和审核效率,降低肠外营养不合理使用带来的风险。