An improved reduction algorithm based on the degree of attribute discernibility

This paper deals with the problem of attribute discernibility reduction and proposes some new concepts to rough set theory （RST） based on the discernibility matrix of Skowron, such as secondary core, regeneration matrix and the degree of attribute discernibility （DAD）. This paper puts forward an attribute reduction algorithm based on maximum discernibility degree, which opens up an effective way of gaining minimum attribute reduction of decision table. The efficacy of this algorithm has been verified by practical application in a diagnostic system of loader, which substantially decreases information gathering requirement and lowers the overall cost with no loss of accuracy.

A Method for Data Classification Based on Discernibility Matrix and Discernibility Function

A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification.

Attribute reduction algorithm based on discernibility for decision table

The attribute reduction algorithms of decision table based on discernible matrix are required to construct discernible matrix, which reduces efficiency of algorithms. In this paper, the relationship between attribute discernible matrix and its discernibility is first established for general information systems. Based on the idea that the equivalent discernible matrix has a same attribute reduction, existing matrices are modified and a formula of attribute discernibility associated with algebraic reduction for decision table is proposed. A heuristic attribute reduction algorithm based on attribute discernibility is presented. Experimental results indicate that the algorithm can more easily explore an optimal or sub-optimal reduction, and is efficient.

改良Aldrete量表和DPART在全身麻醉术后复苏病人中的应用效果比较

目的:探讨中文版DPART量表与改良Aldrete量表对全身麻醉病人术后复苏效果的评估效果。方法:以全身麻醉术后入麻醉复苏室(PACU)接受治疗的病人为研究对象,按手术日期先后顺序分为改良Aldrete组和DPART组。改良Aldrete组105例病人采用改良Aldrete作为出室评估工具,DPART组109例病人采用DPART作为出室评估工具,比较两组病人PACU停留时间、出室时疼痛评分、镇静躁动得分、苏醒期躁动发生率、恶心呕吐评分和护士对于两种量表的可行性、实用性评价。结果:DPART组PACU停留时间长于改良Aldrete组(P<0.05),但出室时疼痛评分、恶心呕吐评分低于改良Aldrete组(P<0.05);两组出室时镇静躁动得分及苏醒期躁动发生率比较差异无统计学意义(P>0.05);DPART组量表的可行性评分低于改良Aldrete组(P<0.05),实用性评分高于改良Aldrete组(P<0.05)。结论:应用中文版DPART量表评估PACU病人,病人PACU停留时间较使用改良Aldrete量表评估延长,但病人出室时各项体征表现较好,更有利于保障全身麻醉术后病人安全转出PACU。

Reduction Algorithms Based on Discernibility Matrix:The Ordered Attributes Method

In this paper, we present reduction algorithms based on the principle of Skowron's discernibility matrix - the ordered attributes method. The completeness of the algorithms for Pawlak reduct and the uniqueness for a given order of the attributes are proved. Since a discernibility matrix requires the size of the memory of U2, U is a universe of objects, it would be impossible to apply these algorithms directly to a massive object set. In order to solve the problem, a so-called quasi-discernibility matrix and two reduction algorithms are proposed. Although the proposed algorithms are incomplete for Pawlak reduct, their opimal paradigms ensure the completeness as long as they satisfy some conditions. Finally we consider the problem on the reduction of distributive object sets.

Generalized binary discernibility matrix for attribute reduction in incomplete information systems

To extract and express the knowledge hidden in information systems, discernibility matrix and its extensions were introduced and applied successfully in many real life applications. Binary discernibility matrix, as a representative approach, has many interesting superior properties and has been rapidly developed to find intuitive and easy to understand knowledge. However, at present, the binary discernibility matrix is mainly adopted in the complete information system. It is a challenging topic how to achieve the attribute reduction by using binary discernibility matrix in incomplete information system. A form of generalized binary discernibility matrix is further developed for a number of representative extended rough set models that deal with incomplete information systems. Some useful properties and criteria are introduced for judging the attribute core and attribute relative reduction. Thereafter, a new algorithm is formulated which supports attribute core and attribute relative reduction based on the generalized binary discernibility matrix. This algorithm is not only suitable for consistent information systems but also inconsistent information systems. The feasibility of the proposed methods was demonstrated by worked examples and experimental analysis.

Investigation on AQ11, ID3 and the Principle of Discernibility Matrix

The principle of discernibility matrix serves as a tool to discuss and analyze two algorithms of traditional inductive machine learning, AQ11 and ID3. The results are: (1) AQ11 and its family can be completely specified by the principle of discernibility matrix; (2) ID3 can be partly, but not naturally, specified by the principle of discernibility matrix; and (3) The principle of discernibility matrix is employed to analyze Cendrowska sample set, and it shows the weaknesses of knowledge representation style of decision tree in theory.

在线健康平台信息质量与可读性计量分析

[目的/意义]在线健康平台信息质量与可读性水平的高低直接影响着社会大众对健康信息的利用效果。对在线健康平台信息质量水平与可读性进行计量分析,有助于揭示在线健康平台信息的现状及可改进之处,这对今后更为有效地帮助社会大众构建和提升健康信息素养具有重要意义。[方法/过程]本文运用DISCERN健康信息质量评价工具,并改进现有中文健康信息可读性计算公式对在线健康平台信息代表样本进行质量与可读性分析研究。[结果/结论]研究发现,目前我国在线健康平台信息整体质量接近中等水平,信息间可读性值差异显著,且与质量水平存在正相关关系。此外,不同来源平台与不同提供主体间的健康信息在质量与可读性上均有差异。

Attribute Reduction of Neighborhood Rough Set Based on Discernment

For neighborhood rough set attribute reduction algorithms based on dependency degree,a neighborhood computation method incorporating attribute weight values and a neighborhood rough set attribute reduction algorithm using discernment as the heuristic information was proposed.The reduction algorithm comprehensively considers the dependency degree and neighborhood granulation degree of attributes,allowing for a more accurate measurement of the importance degrees of attributes.Example analyses and experimental results demonstrate the feasibility and effectiveness of the algorithm.

Some Considerations about Fuzzy Logic Based Decision Making by Autonomous Intelligent Actor

The article presents an approach toward an implementation of a fuzzy logic-based decision-making process by Autonomous Intelligent Actor (AIA) (© A. Tserkovny), when an input information is defined for its “strategic targeting” by a human operator in terms of a fuzzy incident geometry, whereas its “tactical” behavior (a navigation in space) is directed by fuzzy conditional inference rules. For implementing both elements of AIA decision-making a fuzzy logic [1] for formal geometric reasoning with extended objects is used. This fuzzy logic based fuzzification of axioms of an incidence geometry and a predicate apparatus [2] for AIA space orientation are also presented. The approach, offered in the article, extends predicates of a counter positioning of two objects and their mutual navigation into their fuzzy counterparts. The latter allows AIA to make certain “tactical” decisions.

F-interference law generation and its feature recognition

By using two-directional S-rough sets, the concepts of （f, f）-interference generation and （f, f）- interference law generation of knowledge, F-interference generation and F-interference law generation of two-directional S-rough sets are proposed. Based on the concepts above, the relation theoreras between F-interference loss and F-interference degree, the relation theorems between F-interference loss law and F-interference degree law, the dis- cernibility theorems between F-interference and F-interference law are presented. At last, the recognition criterion of F-interference law and its application are given.

Automatic web services classification based on rough set theory

With development of web services technology, the number of existing services in the internet is growing day by day. In order to achieve automatic and accurate services classification which can be beneficial for service related tasks, a rough set theory based method for services classification was proposed. First, the services descriptions were preprocessed and represented as vectors. Elicited by the discernibility matrices based attribute reduction in rough set theory and taking into account the characteristic of decision table of services classification, a method based on continuous discernibility matrices was proposed for dimensionality reduction. And finally, services classification was processed automatically. Through the experiment, the proposed method for services classification achieves approving classification result in all five testing categories. The experiment result shows that the proposed method is accurate and could be used in practical web services classification.

S-rough Laws and Its Dependent Separation by F-Interference

By employing function S-rough sets,the concepts of f-interference generation and separation of law,and the F-interference generation and separation of S-rough laws were proposed. Base on the concepts above,the F-interference relation theorems,the F-interference discernibility theorem,the dependent separation theorem by interfereence,and the dependent separation principle by interference were presented; finally the application was given. By employing F-interference dependence and separation of S-rough laws,the changes of characteristic of dynamic systemic regularities could be recognized.

Extended Rough Set Model Based on Prior Probability and Valued Tolerance Relation

Based on equivalence relation,the classical rough set theory is unable to deal with incomplete information systems.In this case,an extended rough set model based on valued tolerance relation and prior probability obtained from incomplete information systems is firstly founded.As a part of the model,the corresponding discernibility matrix and an attribute reduction of incomplete information system are then proposed.Finally,the extended rough set model and the proposed attribute reduction algorithm are verified under an incomplete information system.

Methods for Lower Approximation Reduction in Inconsistent Decision Table Based on Tolerance Relation

It is well known that most of information systems are based on tolerance relation instead of the classical equivalence relation because of various factors in real-world. To acquire brief decision rules from the information systems, lower approximation reduction is needed. In this paper, the lower approximation reduction is proposed in inconsistent information systems based on tolerance relation. Moreover, the properties are discussed. Furthermore, judgment theorem and discernibility matrix are obtained, from which an approach to lower reductions can be provided in the complicated information systems.

Application of fractal theory in detecting low current faults of power distribution system in coal mines

Single-phase low current grounding faults areoften seen in power distribution system of coal mines.These faults are difficult to reliably identify.We propose a new method of single-phase ground fault protection based upon a discernible matrix of the fractal dimension associated with line currents.The method builds on existing selective protection methods.Faulted feeders are distinguished using differences in the zero-sequence transient current fractal dimension.The current signals were first processed through a fast Fourier transform and then the characteristics of a faulted line were identified using a discernible matrix.The method of calculation is illustrated.The results show that the method involves simple calculations, is easy to do and is highly accurate.It is, therefore, suitable for distribution networks having different neutral grounding modes.

Attribute Disturbance of Knowledge and Attribute Disturbance Theorems

By using the dynamic characteristic of one direction S-rough sets（one direction singular rough sets） and dual of one direction S-rough sets（dual of one direction singular rough sets）, the concepts of attribute disturbance of knowledge, the attribute disturbance degree of knowledge, and the disturbance coefficient of knowledge are given. By employing these concepts, the cardinal order theorem of the attribute disturbance knowledge, the unit circle theorem of the attribute disturbance knowledge, and the discernible theorem of the attribute disturbance knowledge are presented.

Knowledge Law and Attribute Disturbance of Law

By employing the knowledge（R-element equivalence class） in one direction S-rough sets and dual of one direction S-rough sets, the concept of knowledge law is given; the generation theorem of knowledge law, the excursion theorem of knowledge law, and the attribute disturbance discernible theorem of knowledge law are proposed. Knowledge law is a new characteristic of S-rough sets.

Trochanteric bursitis information on the internet;can we trust the information presented?

Trochanteric bursitis is one of the most common causes of lateral hip pain in adults.The prevalence of unilateral trochanteric bursitis is 15.0%in women and 8.5%in men.Access to internet based information has increased dramatically and health related information is now one of the most popular searches in online activity,despite this the quality of information can vary.The objective of this paper is to examine the quality and readability of internet based information of trochanteric bursitis.Overall,we have found a high variability among not only the quality but also the readability of information published.Websites that appeared first on each search engine for trochanteric bursitis did not necessarily score better,demonstrating the importance of providing patients with high quality resources.Future articles should use more critical appraisal tools in order to provide the reader with more high quality and readable information.

Computer aided analysis system for drilling

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